Datasets:
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Parent(s): e051ec0
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Browse files- README.md +129 -162
- UnitCommitment_Trajectory_Test/Project.toml +2 -0
- UnitCommitment_Trajectory_Test/README.md +15 -6
- UnitCommitment_Trajectory_Test/benchmark/scripts/download_matpower_instances.py +191 -0
- UnitCommitment_Trajectory_Test/create_scuc_mps_files.jl +36 -90
- UnitCommitment_Trajectory_Test/docs/src/tutorials/customizing.jl +1 -1
- UnitCommitment_Trajectory_Test/generate_dataset.jl +154 -76
- UnitCommitment_Trajectory_Test/pmax-preprocessing.jl +5 -206
- UnitCommitment_Trajectory_Test/src/UnitCommitment.jl +16 -2
- UnitCommitment_Trajectory_Test/src/import/egret.jl +1 -1
- UnitCommitment_Trajectory_Test/src/instance/modify.jl +242 -0
- UnitCommitment_Trajectory_Test/src/instance/read.jl +3 -3
- UnitCommitment_Trajectory_Test/src/instance/subhourly.jl +271 -0
- UnitCommitment_Trajectory_Test/src/model/formulations/{xxx2005 → ArrCon2004}/powertrajectories.jl +2 -2
- UnitCommitment_Trajectory_Test/src/model/formulations/{xxx2005 → ArrCon2004}/structs.jl +2 -2
- UnitCommitment_Trajectory_Test/src/model/formulations/Gar1962/prod.jl +1 -1
- UnitCommitment_Trajectory_Test/test/test_instance_modification.jl +305 -0
- UnitCommitment_Trajectory_Test/test_main.jl +1 -307
README.md
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- mps
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UnitCommitment_Trajectory/
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├──
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```
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##
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| `test_main.jl` | 模型对比实验脚本。对比基础模型、v1（添加启停轨迹）和 v2（修改最小运行时间）三种配置的求解结果，生成 CSV 报表。 |
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| `pmax-preprocessing.jl` | 预处理函数库。被 `test_main.jl` 调用，实现以下两步逻辑：①按容量（Pmax）筛选机组并写入启停曲线（Part 1）；②修改前 20% 大机组的最小运行时间（Part 2）。 |
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| `Project.toml` | Julia 包管理配置文件。声明了本项目依赖的所有第三方包及版本约束（JuMP、HiGHS、CodecZlib 等）。 |
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| `Manifest.toml` | Julia 依赖锁定文件。精确记录了每个依赖包的版本和哈希值，确保不同机器上的环境完全一致。**请勿手动修改此文件。** |
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| `src/model/` | 模型构建模块。`build.jl` 是入口，根据传入的 `Formulation` 参数调用各子模块，在内存中构建 JuMP 数学模型。 |
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| `src/model/formulations/base/` | 基础公式化组件。包含线路约束（`line.jl`）、机组约束（`unit.jl`）等标准模块。 |
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| `src/model/formulations/xxx2005/` | **本项目新增的核心模块**。实现了发电机启停功率轨迹（Power Trajectories）约束。该约束用曲线精确建模机组在启动和停机阶段逐时段的输出功率，是本数据集区别于普通 UC 数据集的关键特性。 |
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| `src/transform/` | 数据变换模块。包含 `convert_to_subhourly` 函数，负责将 1 小时分辨率（24 时段）的算例转换为 15 分钟分辨率（96 时段）。 |
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```
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instances/
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└── matpower/
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├── case14/ ← IEEE 14 节点测试系统，含 67 个日期的算例文件
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└── case30/ ← IEEE 30 节点测试系统，含 45 个日期的算例文件
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```
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每个文件夹下存放以日期命名的 `.json.gz` 压缩文件（例如 `2017-01-01.json.gz`），每个文件描述了当日的负荷曲线、机组参数和电网拓扑。
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└── case2383wp/ ← 波兰国家电网模型（2383 节点，323 台发电机），含 4 个日期的算例文件
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```
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UnitCommitment_Trajectory_Dataset/
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├── case14/
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│ ├── hourly_noline/ ← case14 的 MPS 文件，1小时粒度，无网络约束
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│ ├── hourly_withline/ ← case14 的 MPS 文件，1小时粒度，含 SCUC 网络约束
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│ ├── subhourly_noline/ ← case14 的 MPS 文件，15分钟粒度，无网络约束
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│ └── subhourly_withline/ ← case14 的 MPS 文件，15分钟粒度，含 SCUC 网络约束
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├── case30/
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│ └── ...（结构同上）
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└── case2383wp/
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└── ...（结构同上）
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```
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### 3.1 四种变体的 MIP 特性对比
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| :--- | :---: | :---: | :--- | :--- |
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| `hourly_noline` | 24 | ✗ | 最小。仅含机组开关（二进制）和出力（连续）变量。 | 入门级 MIP 测试，算法原型验证。 |
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| `hourly_withline` | 24 | ✓ | 中等。在 `noline` 基础上增加大量潮流不等式约束（DCOPF）。 | 标准 SCUC 基准，适合测试割平面效果。 |
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| `subhourly_noline` | 96 | ✗ | 较大。变量数量是 hourly 版本的 4 倍。 | 测试求解器处理高维 MIP 的收敛性能。 |
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| `subhourly_withline` | 96 | ✓ | 最大。同时具备高维变量和密集约束矩阵。 | 最接近现实调度的高难度 MIP 命题。 |
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{算例名}_{日期}_{粒度}_{变体}.mps
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│ │ │ └── withline：包含网络约束 / noline：无网络约束
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│ │ └── s：subhourly（15分钟）/ h：hourly（1小时）
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│ ��── 该条 MPS 对应的负荷场景日期
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## 四、从零复现数据集的完整步骤
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```
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├── UnitCommitment_Trajectory_Test\ ← 包含 generate_dataset.jl 和 src/ 等
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└── UnitCommitment_Trajectory_Dataset\ ← 可以是空文件夹，脚本会自动创建子目录
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```
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> **注意**：`UnitCommitment_Trajectory_Dataset` 文件夹必须与 `UnitCommitment_Trajectory_Test` 处于**同一层级**，否则脚本中的相对路径 `../UnitCommitment_Trajectory_Dataset` 将无法找到输出目录。
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### 步骤 3：初始化 Julia 环境（仅需执行一次）
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julia --project=. -e "using Pkg; Pkg.instantiate()"
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该命令会读取 `Project.toml` 和 `Manifest.toml`，自动下载并安装所有指定版本的依赖包（JuMP、HiGHS、CodecZlib 等）。
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> **常见问题**：若网络较慢或出现 SSL 错误，可尝试设置国内镜像后再执行：
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julia --project=. generate_dataset.jl
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脚本将依次处理 `case14`（67 个文件）、`case30`（45 个文件）和 `case2383wp`（4 个文件），每个算例生成 4 种变体共 **464 个 `.mps` 文件**。
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```
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🚀 开始全量数据集生成任务 (包含大型算例)...
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[case14] 处理进度: 1/67 (2017-01-01)
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[case14] 处理进度: 2/67 (2017-01-02)
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✅ 所有算例生成完毕！
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> **预计耗时**：普通电脑约 10–20 分钟（case2383wp 的大型算例每个文件需较长时间）。
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> **内存要求**：建议至少 8GB 可用内存，生成 case2383wp 的 Subhourly 版本时内存占用峰值约为 4GB。
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### 步骤 5：验证生成结果
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生成完成后，检查 `UnitCommitment_Trajectory_Dataset/` 下是否存在如下结构，且每个变体文件夹内包含对应数量的 `.mps` 文件：
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| 文件夹路径 | 预期文件数 |
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| `case14/hourly_noline/` | 67 |
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| `case14/subhourly_noline/` | 67 |
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| `case14/subhourly_withline/` | 67 |
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| `case30/subhourly_withline/` | 45 |
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| `case2383wp/hourly_noline/` | 4 |
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| `case2383wp/hourly_withline/` | 4 |
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| `case2383wp/subhourly_noline/` | 4 |
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| `case2383wp/subhourly_withline/` | 4 |
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| **合计** | **464** |
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## 五、数据集技术规格
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- **变量命名**：已启用 `variable_names=true`，MPS 文件中的变量使用语义化名称（如 `is_on[generator_name, t]`、`prod_above[s1, generator_name, t]`），而非 `x1, x2` 等匿名编号。
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- **启停轨迹**：所有模型均包含本项目定制的发电机启停功率轨迹约束（`xxx2005` 模块），相比标准 UC 公式，MIP 的可行域更精确，对求解器分支策略的要求更高。
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# UnitCommitment Trajectory MPS 数据集
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本仓库用于从 UnitCommitment.jl 的 Matpower 机组组合（UC）实例生成标准 `.mps` 文件，供混合整数规划（MIP）、机组组合（UC）及安全约束机组组合（SCUC）模型求解器测试与基准研究使用。
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仓库地址：[EridanusQ/UnitCommitment_Trajectory · Datasets at Hugging Face](https://huggingface.co/datasets/EridanusQ/UnitCommitment_Trajectory)
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## 1. 数据规模
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`UnitCommitment_Trajectory_Test/instances/matpower` 下共有 **26** 个 Matpower case，**9487** 个 `.json.gz` 输入实例。每个实例生成 4 个 `.mps`，全量输出预计 **37948** 个文件。
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| Case | 输入实例数 |
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| :-------------- | ---------: |
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| case118 | 365 |
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| case1354pegase | 365 |
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| case13659pegase | 365 |
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| case14 | 365 |
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| case1888rte | 365 |
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| case1951rte | 365 |
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| case2383wp | 365 |
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| case2736sp | 365 |
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| case2737sop | 365 |
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| case2746wop | 365 |
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| case2746wp | 365 |
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| case2848rte | 365 |
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| case2868rte | 365 |
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| case2869pegase | 365 |
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| case30 | 365 |
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| case300 | 365 |
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| case3012wp | 365 |
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| case3120sp | 365 |
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| case3375wp | 365 |
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| case57 | 362 |
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| case6468rte | 365 |
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| case6470rte | 365 |
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| case6495rte | 365 |
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| case6515rte | 365 |
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| case89pegase | 365 |
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| case9241pegase | 365 |
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## 2. 目录结构
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```text
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UnitCommitment_Trajectory/
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├── README.md
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├── UnitCommitment_Trajectory_Test/
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│ ├── Project.toml
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│ ├── Manifest.toml
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│ ├── generate_dataset.jl # 批量生成 MPS 主脚本
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│ ├── create_scuc_mps_files.jl # 单算例调试脚本
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│ ├── instances/
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│ │ └── matpower/ # 原始 .json.gz 输入实例
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│ ├── benchmark/
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│ │ └── scripts/
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│ │ └── download_matpower_instances.py
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│ ├── src/ # 修改版 UnitCommitment.jl 源码
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│ └── ...
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└── UnitCommitment_Trajectory_Dataset/ # 输出的 .mps 文件目录
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```
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> 后文所有命令均在 `UnitCommitment_Trajectory_Test` 目录下执行，路径均相对于该目录。
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## 3. 环境准备
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- **Julia**：建议 1.12 系列。
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- **Python 3**：仅用于下载脚本，无需额外依赖。
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|
| 84 |
+
```powershell
|
| 85 |
+
cd UnitCommitment_Trajectory\UnitCommitment_Trajectory_Test
|
| 86 |
+
julia --project=. -e "using Pkg; Pkg.instantiate()"
|
| 87 |
+
```
|
|
|
|
|
|
|
|
|
|
|
|
|
| 88 |
|
| 89 |
+
## 4. 下载原始 Matpower 输入数据
|
| 90 |
|
| 91 |
+
下载脚本 `benchmark\scripts\download_matpower_instances.py` 从 `https://axavier.org/UnitCommitment.jl/0.4/instances` 获取数据，默认日期范围 `2017-01-01` 至 `2017-12-31`，保存到 `instances/matpower`，已存在且非空的文件会自动跳过。
|
| 92 |
|
| 93 |
+
```powershell
|
| 94 |
+
# 下载全年数据（最常用）
|
| 95 |
+
python benchmark\scripts\download_matpower_instances.py
|
|
|
|
|
|
|
|
|
|
|
|
|
| 96 |
|
| 97 |
+
# 查看支持的 case 列表
|
| 98 |
+
python benchmark\scripts\download_matpower_instances.py --list-cases
|
| 99 |
|
| 100 |
+
# 指定日期范围（示例）
|
| 101 |
+
python benchmark\scripts\download_matpower_instances.py --start-date 2017-01-01 --end-date 2017-01-31
|
| 102 |
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 103 |
|
| 104 |
+
快速检查下载结果：
|
| 105 |
|
| 106 |
+
```powershell
|
| 107 |
+
Get-ChildItem instances\matpower -Recurse -Filter *.json.gz | Measure-Object
|
|
|
|
| 108 |
```
|
| 109 |
|
| 110 |
+
## 5. MPS 输出结构
|
| 111 |
|
| 112 |
+
`generate_dataset.jl` 将结果输出到 `../UnitCommitment_Trajectory_Dataset`（即仓库根目录下的数据集目录）。每个 case 下生成四个变体子目录：
|
| 113 |
|
| 114 |
+
```text
|
| 115 |
+
case_name/
|
| 116 |
+
├── hourly_noline/ # 小时级 UC，无线路约束
|
| 117 |
+
├── hourly_withline/ # 小时级 SCUC，含线路约束
|
| 118 |
+
├── subhourly_noline/ # 子小时 UC，无线路约束
|
| 119 |
+
└── subhourly_withline/ # 子小时 SCUC，含线路约束
|
| 120 |
+
```
|
| 121 |
|
| 122 |
+
文件命名规则：`{case}_{date}_{resolution}_{network}.mps`
|
| 123 |
+
例如：`case30_2017-01-01_h_noline.mps`（`h` = hourly，`s` = subhourly）。
|
| 124 |
|
| 125 |
+
## 6. 单算例测试
|
| 126 |
|
| 127 |
+
用于验证环境与建模流程是否正常：
|
| 128 |
|
| 129 |
+
```powershell
|
| 130 |
+
julia --project=. create_scuc_mps_files.jl
|
| 131 |
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 132 |
|
| 133 |
+
成功后会在当前目录生成四个测试文件：`uc_default_noline.mps` 等。
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 134 |
|
| 135 |
+
## 7. 全量生成 MPS 数据集
|
| 136 |
|
| 137 |
+
### 7.1 基本用法
|
|
|
|
|
|
|
|
|
|
|
|
|
| 138 |
|
| 139 |
+
确认输入数据就绪后，直接运行：
|
| 140 |
|
| 141 |
+
```powershell
|
| 142 |
+
julia --project=. generate_dataset.jl
|
|
|
|
|
|
|
|
|
|
|
|
|
| 143 |
```
|
| 144 |
|
| 145 |
+
脚本会自动扫描 `instances/matpower` 下所有包含 `.json.gz` 的 case。**全量生成非常耗时且占用大量磁盘空间**，大规模 case（如 `case13659pegase`、`case9241pegase`）尤为突出。
|
|
|
|
|
|
|
| 146 |
|
| 147 |
+
### 7.2 只生成指定 Case
|
| 148 |
|
| 149 |
+
```powershell
|
| 150 |
+
$env:UC_CASES = "case14,case30"
|
| 151 |
+
julia --project=. generate_dataset.jl
|
| 152 |
+
Remove-Item Env:\UC_CASES
|
| 153 |
+
```
|
| 154 |
|
| 155 |
+
单 case 同理：`$env:UC_CASES = "case118"`。干跑与指定 case 可组合使用。
|
| 156 |
|
| 157 |
+
## 8. 检查 MPS 输出结果
|
| 158 |
|
| 159 |
+
在 `UnitCommitment_Trajectory_Test` 目录下执行：
|
| 160 |
|
| 161 |
+
```powershell
|
| 162 |
+
# 文件总数
|
| 163 |
+
Get-ChildItem ..\UnitCommitment_Trajectory_Dataset -Recurse -Filter *.mps | Measure-Object
|
| 164 |
```
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 165 |
|
| 166 |
+
## 9. 完整复现流程
|
| 167 |
|
| 168 |
```powershell
|
| 169 |
+
cd UnitCommitment_Trajectory\UnitCommitment_Trajectory_Test
|
| 170 |
|
| 171 |
+
# 1. 初始化 Julia 环境
|
| 172 |
julia --project=. -e "using Pkg; Pkg.instantiate()"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 173 |
|
| 174 |
+
# 2. 下载 Matpower 实例
|
| 175 |
+
python benchmark\scripts\download_matpower_instances.py
|
| 176 |
|
| 177 |
+
# 3. 检查下载数量
|
| 178 |
+
Get-ChildItem instances\matpower -Recurse -Filter *.json.gz | Measure-Object
|
| 179 |
|
| 180 |
+
# 4. 全量生成 MPS
|
| 181 |
julia --project=. generate_dataset.jl
|
|
|
|
|
|
|
|
|
|
| 182 |
|
| 183 |
+
# 5. 检查最终 MPS 文件数
|
| 184 |
+
Get-ChildItem ..\UnitCommitment_Trajectory_Dataset -Recurse -Filter *.mps | Measure-Object
|
| 185 |
```
|
|
|
|
| 186 |
|
| 187 |
+
## 10. 轨迹约束与预处理说明
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 188 |
|
| 189 |
+
本仓库��于修改版 UnitCommitment.jl，增加了启停轨迹约束与实例预处理逻辑。相关代码位于：
|
|
|
|
|
|
|
| 190 |
|
| 191 |
+
- `src/model/formulations`：轨迹约束建模
|
| 192 |
+
- `src/instance/modify.jl`：实例预处理
|
| 193 |
|
| 194 |
+
更详细的说明与测试示例参见 `UnitCommitment_Trajectory_Test/README.md`。
|
| 195 |
|
| 196 |
+
## 11. 引用
|
| 197 |
|
| 198 |
+
原始 UnitCommitment.jl DOI：
|
| 199 |
+
[10.5281/zenodo.4269874](https://doi.org/10.5281/zenodo.4269874)
|
UnitCommitment_Trajectory_Test/Project.toml
CHANGED
|
@@ -6,6 +6,7 @@ version = "0.3.0"
|
|
| 6 |
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
|
| 7 |
CodecZlib = "944b1d66-785c-5afd-91f1-9de20f533193"
|
| 8 |
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
|
|
|
|
| 9 |
Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
|
| 10 |
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
|
| 11 |
GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
|
|
@@ -27,6 +28,7 @@ TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
|
|
| 27 |
Cbc = "1.3.0"
|
| 28 |
CodecZlib = "0.7.8"
|
| 29 |
DataStructures = "0.18.22"
|
|
|
|
| 30 |
Distributed = "1.11.0"
|
| 31 |
Distributions = "0.25.125"
|
| 32 |
GZip = "0.5.2"
|
|
|
|
| 6 |
Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
|
| 7 |
CodecZlib = "944b1d66-785c-5afd-91f1-9de20f533193"
|
| 8 |
DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
|
| 9 |
+
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
|
| 10 |
Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
|
| 11 |
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
|
| 12 |
GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
|
|
|
|
| 28 |
Cbc = "1.3.0"
|
| 29 |
CodecZlib = "0.7.8"
|
| 30 |
DataStructures = "0.18.22"
|
| 31 |
+
Dates = "1.11.0"
|
| 32 |
Distributed = "1.11.0"
|
| 33 |
Distributions = "0.25.125"
|
| 34 |
GZip = "0.5.2"
|
UnitCommitment_Trajectory_Test/README.md
CHANGED
|
@@ -1,8 +1,8 @@
|
|
| 1 |
<h1 align="center">UnitCommitment.jl (Modified Trajectory Version)</h1>
|
| 2 |
|
| 3 |
-
> **NOTA BENE**
|
| 4 |
-
> This is a customized version of the original `UnitCommitment.jl` package.
|
| 5 |
-
>
|
| 6 |
> **主要修改与新增功能 (Modified Features):**
|
| 7 |
> 1. **启停轨迹约束 (Power Trajectories)**: 新增了 `xxx2005` 文件夹及其对应的模型实现，支持机组的 Startup / Shutdown 启停轨迹约束 (`xxx2005.PowerTrajectories()`)。
|
| 8 |
> 2. **预处理修正 (Preprocessing)**: 增加了 `pmax-preprocessing.jl` 脚本，针对特定机组的 Minimum uptime 等参数进行数据筛选与修正逻辑。
|
|
@@ -62,23 +62,26 @@ JuMP.optimize!(model)
|
|
| 62 |
2. 在该文件夹下打开命令行（或终端），输入 `julia` 进入交互模式。
|
| 63 |
3. 按下 `]` 键进入 Pkg 包管理模式（提示符会变为 `pkg>`）。
|
| 64 |
4. 依次执行以下命令：
|
|
|
|
| 65 |
```julia
|
| 66 |
# 激活当前目录的独立环境
|
| 67 |
pkg> activate .
|
| 68 |
-
|
| 69 |
# 实例化安装原项目自带的依赖
|
| 70 |
pkg> instantiate
|
| 71 |
-
|
| 72 |
# 安装本次测试脚本额外需要的依赖包
|
| 73 |
pkg> add JuMP HiGHS GZip
|
| 74 |
pkg> update GZip
|
| 75 |
```
|
|
|
|
| 76 |
5. 按下 `Backspace` (退格键) 退出 Pkg 模式，回到 `julia>` 提示符，或直接关闭窗口。
|
| 77 |
|
| 78 |
### 2. 算例配置 (CASES 选择)
|
| 79 |
|
| 80 |
`test_main.jl` 的顶部定义了一个 `CASES` 数组，列出了需要进行对比测试的数据集。
|
| 81 |
如果您想缩短测试时间，可以打开 `test_main.jl`，利用 `#` 号注释掉暂不需要测试的算例：
|
|
|
|
| 82 |
```julia
|
| 83 |
CASES =[
|
| 84 |
("testdata/case2383wp/2017-07-28.json.gz", "case2383wp"),
|
|
@@ -89,18 +92,23 @@ CASES =[
|
|
| 89 |
### 3. 运行测试
|
| 90 |
|
| 91 |
在命令行中（确保路径为当前文件夹），直接运行：
|
|
|
|
| 92 |
```bash
|
| 93 |
julia test_main.jl
|
| 94 |
```
|
|
|
|
| 95 |
测试脚本将自动针对每个算例依序运行以下三种情况：
|
|
|
|
| 96 |
* **Base**: 基础模型（未添加启停轨迹的原版逻辑）
|
| 97 |
* **v1 (Part 1)**: 添加 Startup / Shutdown 启停曲线的模型
|
| 98 |
* **v2 (Part 2)**: 在 v1 基础上筛选并修正 Minimum uptime 的模型
|
| 99 |
|
| 100 |
### 4. 测试输出结果说明
|
|
|
|
| 101 |
测试完毕后，您可以在 `./test/` 目录下找到所有独立生成的算例结果文件夹（例如 `./test/case2383wp-2017-07-28/`）。
|
| 102 |
|
| 103 |
每个文件夹内包含：
|
|
|
|
| 104 |
1. **中间 JSON 数据集**：
|
| 105 |
* `*-part1.json`：动态添加了 Startup/Shutdown curve 的实例。
|
| 106 |
* `*-part2.json`：在 part1 基础上修正了 Minimum uptime 的实例。
|
|
@@ -114,6 +122,7 @@ julia test_main.jl
|
|
| 114 |
---
|
| 115 |
|
| 116 |
## Original Authors
|
|
|
|
| 117 |
* **Alinson S. Xavier** (Argonne National Laboratory)
|
| 118 |
* **Aleksandr M. Kazachkov** (University of Florida)
|
| 119 |
* **Ogün Yurdakul** (Technische Universität Berlin)
|
|
@@ -149,4 +158,4 @@ SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSE
|
|
| 149 |
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
|
| 150 |
OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
| 151 |
POSSIBILITY OF SUCH DAMAGE.
|
| 152 |
-
```
|
|
|
|
| 1 |
<h1 align="center">UnitCommitment.jl (Modified Trajectory Version)</h1>
|
| 2 |
|
| 3 |
+
> **NOTA BENE**
|
| 4 |
+
> This is a customized version of the original `UnitCommitment.jl` package.
|
| 5 |
+
>
|
| 6 |
> **主要修改与新增功能 (Modified Features):**
|
| 7 |
> 1. **启停轨迹约束 (Power Trajectories)**: 新增了 `xxx2005` 文件夹及其对应的模型实现，支持机组的 Startup / Shutdown 启停轨迹约束 (`xxx2005.PowerTrajectories()`)。
|
| 8 |
> 2. **预处理修正 (Preprocessing)**: 增加了 `pmax-preprocessing.jl` 脚本，针对特定机组的 Minimum uptime 等参数进行数据筛选与修正逻辑。
|
|
|
|
| 62 |
2. 在该文件夹下打开命令行（或终端），输入 `julia` 进入交互模式。
|
| 63 |
3. 按下 `]` 键进入 Pkg 包管理模式（提示符会变为 `pkg>`）。
|
| 64 |
4. 依次执行以下命令：
|
| 65 |
+
|
| 66 |
```julia
|
| 67 |
# 激活当前目录的独立环境
|
| 68 |
pkg> activate .
|
| 69 |
+
|
| 70 |
# 实例化安装原项目自带的依赖
|
| 71 |
pkg> instantiate
|
| 72 |
+
|
| 73 |
# 安装本次测试脚本额外需要的依赖包
|
| 74 |
pkg> add JuMP HiGHS GZip
|
| 75 |
pkg> update GZip
|
| 76 |
```
|
| 77 |
+
|
| 78 |
5. 按下 `Backspace` (退格键) 退出 Pkg 模式，回到 `julia>` 提示符，或直接关闭窗口。
|
| 79 |
|
| 80 |
### 2. 算例配置 (CASES 选择)
|
| 81 |
|
| 82 |
`test_main.jl` 的顶部定义了一个 `CASES` 数组，列出了需要进行对比测试的数据集。
|
| 83 |
如果您想缩短测试时间，可以打开 `test_main.jl`，利用 `#` 号注释掉暂不需要测试的算例：
|
| 84 |
+
|
| 85 |
```julia
|
| 86 |
CASES =[
|
| 87 |
("testdata/case2383wp/2017-07-28.json.gz", "case2383wp"),
|
|
|
|
| 92 |
### 3. 运行测试
|
| 93 |
|
| 94 |
在命令行中（确保路径为当前文件夹），直接运行：
|
| 95 |
+
|
| 96 |
```bash
|
| 97 |
julia test_main.jl
|
| 98 |
```
|
| 99 |
+
|
| 100 |
测试脚本将自动针对每个算例依序运行以下三种情况：
|
| 101 |
+
|
| 102 |
* **Base**: 基础模型（未添加启停轨迹的原版逻辑）
|
| 103 |
* **v1 (Part 1)**: 添加 Startup / Shutdown 启停曲线的模型
|
| 104 |
* **v2 (Part 2)**: 在 v1 基础上筛选并修正 Minimum uptime 的模型
|
| 105 |
|
| 106 |
### 4. 测试输出结果说明
|
| 107 |
+
|
| 108 |
测试完毕后，您可以在 `./test/` 目录下找到所有独立生成的算例结果文件夹（例如 `./test/case2383wp-2017-07-28/`）。
|
| 109 |
|
| 110 |
每个文件夹内包含：
|
| 111 |
+
|
| 112 |
1. **中间 JSON 数据集**：
|
| 113 |
* `*-part1.json`：动态添加了 Startup/Shutdown curve 的实例。
|
| 114 |
* `*-part2.json`：在 part1 基础上修正了 Minimum uptime 的实例。
|
|
|
|
| 122 |
---
|
| 123 |
|
| 124 |
## Original Authors
|
| 125 |
+
|
| 126 |
* **Alinson S. Xavier** (Argonne National Laboratory)
|
| 127 |
* **Aleksandr M. Kazachkov** (University of Florida)
|
| 128 |
* **Ogün Yurdakul** (Technische Universität Berlin)
|
|
|
|
| 158 |
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
|
| 159 |
OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
| 160 |
POSSIBILITY OF SUCH DAMAGE.
|
| 161 |
+
```
|
UnitCommitment_Trajectory_Test/benchmark/scripts/download_matpower_instances.py
ADDED
|
@@ -0,0 +1,191 @@
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
import argparse
|
| 4 |
+
import datetime as dt
|
| 5 |
+
import os
|
| 6 |
+
import re
|
| 7 |
+
import sys
|
| 8 |
+
import time
|
| 9 |
+
import urllib.error
|
| 10 |
+
import urllib.request
|
| 11 |
+
from concurrent.futures import ThreadPoolExecutor, as_completed
|
| 12 |
+
from dataclasses import dataclass
|
| 13 |
+
from pathlib import Path
|
| 14 |
+
|
| 15 |
+
BASE_URL_DEFAULT = "https://axavier.org/UnitCommitment.jl/0.4/instances"
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
@dataclass(frozen=True)
|
| 19 |
+
class Task:
|
| 20 |
+
case: str
|
| 21 |
+
date: dt.date
|
| 22 |
+
url: str
|
| 23 |
+
out_path: Path
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
def _iter_dates(start: dt.date, end: dt.date):
|
| 27 |
+
if end < start:
|
| 28 |
+
raise ValueError("end_date must be >= start_date")
|
| 29 |
+
cur = start
|
| 30 |
+
one = dt.timedelta(days=1)
|
| 31 |
+
while cur <= end:
|
| 32 |
+
yield cur
|
| 33 |
+
cur += one
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
def _default_instances_md_path() -> Path:
|
| 37 |
+
here = Path(__file__).resolve()
|
| 38 |
+
project_root = here.parents[2]
|
| 39 |
+
return project_root / "docs" / "src" / "guides" / "instances.md"
|
| 40 |
+
|
| 41 |
+
|
| 42 |
+
def _parse_matpower_cases_from_instances_md(instances_md_path: Path) -> list[str]:
|
| 43 |
+
text = instances_md_path.read_text(encoding="utf-8")
|
| 44 |
+
pattern = re.compile(r"matpower/(case[^/\s`]+)/\d{4}-\d{2}-\d{2}")
|
| 45 |
+
cases = sorted(set(pattern.findall(text)))
|
| 46 |
+
if not cases:
|
| 47 |
+
raise RuntimeError(f"No MATPOWER cases found in {instances_md_path}")
|
| 48 |
+
return cases
|
| 49 |
+
|
| 50 |
+
|
| 51 |
+
def _download_one(task: Task, timeout_s: float, retries: int, force: bool) -> tuple[str, str | None]:
|
| 52 |
+
task.out_path.parent.mkdir(parents=True, exist_ok=True)
|
| 53 |
+
|
| 54 |
+
if task.out_path.exists() and not force and task.out_path.stat().st_size > 0:
|
| 55 |
+
return ("skipped", None)
|
| 56 |
+
|
| 57 |
+
tmp_path = task.out_path.with_suffix(task.out_path.suffix + ".part")
|
| 58 |
+
req = urllib.request.Request(task.url, headers={"User-Agent": "UnitCommitment downloader"})
|
| 59 |
+
|
| 60 |
+
last_err = None
|
| 61 |
+
for attempt in range(retries + 1):
|
| 62 |
+
try:
|
| 63 |
+
with urllib.request.urlopen(req, timeout=timeout_s) as resp:
|
| 64 |
+
with open(tmp_path, "wb") as f:
|
| 65 |
+
while True:
|
| 66 |
+
chunk = resp.read(1024 * 256)
|
| 67 |
+
if not chunk:
|
| 68 |
+
break
|
| 69 |
+
f.write(chunk)
|
| 70 |
+
os.replace(tmp_path, task.out_path)
|
| 71 |
+
return ("downloaded", None)
|
| 72 |
+
except (urllib.error.URLError, urllib.error.HTTPError, TimeoutError, OSError) as e:
|
| 73 |
+
last_err = e
|
| 74 |
+
try:
|
| 75 |
+
if tmp_path.exists():
|
| 76 |
+
tmp_path.unlink()
|
| 77 |
+
except OSError:
|
| 78 |
+
pass
|
| 79 |
+
if attempt < retries:
|
| 80 |
+
time.sleep(min(10.0, 0.5 * (2**attempt)))
|
| 81 |
+
continue
|
| 82 |
+
return ("failed", f"{type(last_err).__name__}: {last_err}")
|
| 83 |
+
|
| 84 |
+
return ("failed", f"{type(last_err).__name__}: {last_err}")
|
| 85 |
+
|
| 86 |
+
|
| 87 |
+
def _build_tasks(
|
| 88 |
+
base_url: str,
|
| 89 |
+
out_dir: Path,
|
| 90 |
+
cases: list[str],
|
| 91 |
+
start_date: dt.date,
|
| 92 |
+
end_date: dt.date,
|
| 93 |
+
) -> list[Task]:
|
| 94 |
+
tasks: list[Task] = []
|
| 95 |
+
for case in cases:
|
| 96 |
+
for d in _iter_dates(start_date, end_date):
|
| 97 |
+
date_str = d.isoformat()
|
| 98 |
+
url = f"{base_url}/matpower/{case}/{date_str}.json.gz"
|
| 99 |
+
out_path = out_dir / case / f"{date_str}.json.gz"
|
| 100 |
+
tasks.append(Task(case=case, date=d, url=url, out_path=out_path))
|
| 101 |
+
return tasks
|
| 102 |
+
|
| 103 |
+
|
| 104 |
+
def _parse_date(s: str) -> dt.date:
|
| 105 |
+
return dt.date.fromisoformat(s)
|
| 106 |
+
|
| 107 |
+
|
| 108 |
+
def main(argv: list[str]) -> int:
|
| 109 |
+
parser = argparse.ArgumentParser()
|
| 110 |
+
parser.add_argument("--instances-md", type=Path, default=_default_instances_md_path())
|
| 111 |
+
parser.add_argument("--base-url", type=str, default=BASE_URL_DEFAULT)
|
| 112 |
+
parser.add_argument(
|
| 113 |
+
"--out-dir",
|
| 114 |
+
type=Path,
|
| 115 |
+
default=(Path(__file__).resolve().parents[2] / "instances" / "matpower"),
|
| 116 |
+
)
|
| 117 |
+
parser.add_argument("--start-date", type=_parse_date, default=dt.date(2017, 1, 1))
|
| 118 |
+
parser.add_argument("--end-date", type=_parse_date, default=dt.date(2017, 12, 31))
|
| 119 |
+
parser.add_argument("--workers", type=int, default=min(32, (os.cpu_count() or 4) * 4))
|
| 120 |
+
parser.add_argument("--timeout", type=float, default=60.0)
|
| 121 |
+
parser.add_argument("--retries", type=int, default=3)
|
| 122 |
+
parser.add_argument("--force", action="store_true")
|
| 123 |
+
parser.add_argument("--dry-run", action="store_true")
|
| 124 |
+
parser.add_argument("--list-cases", action="store_true")
|
| 125 |
+
args = parser.parse_args(argv)
|
| 126 |
+
|
| 127 |
+
instances_md_path: Path = args.instances_md
|
| 128 |
+
if not instances_md_path.exists():
|
| 129 |
+
raise FileNotFoundError(str(instances_md_path))
|
| 130 |
+
|
| 131 |
+
cases = _parse_matpower_cases_from_instances_md(instances_md_path)
|
| 132 |
+
if args.list_cases:
|
| 133 |
+
for c in cases:
|
| 134 |
+
print(c)
|
| 135 |
+
return 0
|
| 136 |
+
|
| 137 |
+
out_dir: Path = args.out_dir
|
| 138 |
+
tasks = _build_tasks(
|
| 139 |
+
base_url=args.base_url.rstrip("/"),
|
| 140 |
+
out_dir=out_dir,
|
| 141 |
+
cases=cases,
|
| 142 |
+
start_date=args.start_date,
|
| 143 |
+
end_date=args.end_date,
|
| 144 |
+
)
|
| 145 |
+
|
| 146 |
+
print(f"cases={len(cases)} files={len(tasks)} out_dir={out_dir}")
|
| 147 |
+
if args.dry_run:
|
| 148 |
+
for t in tasks[:10]:
|
| 149 |
+
print(f"{t.url} -> {t.out_path}")
|
| 150 |
+
if len(tasks) > 10:
|
| 151 |
+
print("...")
|
| 152 |
+
return 0
|
| 153 |
+
|
| 154 |
+
downloaded = 0
|
| 155 |
+
skipped = 0
|
| 156 |
+
failed = 0
|
| 157 |
+
total = len(tasks)
|
| 158 |
+
t0 = time.time()
|
| 159 |
+
last_print = 0.0
|
| 160 |
+
|
| 161 |
+
with ThreadPoolExecutor(max_workers=max(1, args.workers)) as ex:
|
| 162 |
+
fut_to_task = {
|
| 163 |
+
ex.submit(_download_one, t, args.timeout, args.retries, args.force): t for t in tasks
|
| 164 |
+
}
|
| 165 |
+
for i, fut in enumerate(as_completed(fut_to_task), start=1):
|
| 166 |
+
status, err = fut.result()
|
| 167 |
+
if status == "downloaded":
|
| 168 |
+
downloaded += 1
|
| 169 |
+
elif status == "skipped":
|
| 170 |
+
skipped += 1
|
| 171 |
+
else:
|
| 172 |
+
failed += 1
|
| 173 |
+
task = fut_to_task[fut]
|
| 174 |
+
sys.stderr.write(f"FAILED {task.url} -> {task.out_path} ({err})\n")
|
| 175 |
+
|
| 176 |
+
now = time.time()
|
| 177 |
+
if now - last_print >= 1.0 or i == total:
|
| 178 |
+
elapsed = max(0.001, now - t0)
|
| 179 |
+
rate = i / elapsed
|
| 180 |
+
print(
|
| 181 |
+
f"{i}/{total} downloaded={downloaded} skipped={skipped} failed={failed} rate={rate:.1f}/s"
|
| 182 |
+
)
|
| 183 |
+
last_print = now
|
| 184 |
+
|
| 185 |
+
if failed:
|
| 186 |
+
return 2
|
| 187 |
+
return 0
|
| 188 |
+
|
| 189 |
+
|
| 190 |
+
if __name__ == "__main__":
|
| 191 |
+
raise SystemExit(main(sys.argv[1:]))
|
UnitCommitment_Trajectory_Test/create_scuc_mps_files.jl
CHANGED
|
@@ -1,100 +1,46 @@
|
|
| 1 |
-
# =========================================================================
|
| 2 |
-
# 脚本名称: create_scuc_mps_files.jl
|
| 3 |
-
# 运行环境: D:\e-task\UnitCommitment.jl\dev\
|
| 4 |
-
# 功能目标: 生成 4 个版本的机组组合(UC)优化模型的 MPS 文件
|
| 5 |
-
# =========================================================================
|
| 6 |
-
|
| 7 |
-
# 1. 导入必需的包
|
| 8 |
-
using UnitCommitment
|
| 9 |
using JuMP
|
|
|
|
| 10 |
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
instance_v1 = UnitCommitment.read(base_instance_name)
|
| 24 |
-
|
| 25 |
-
# 【核心操作】：直接清空内存中的线路数据，确保 build_model 不加线路约束
|
| 26 |
-
empty!(instance_v1.scenarios[1].lines)
|
| 27 |
-
|
| 28 |
-
model_v1 = UnitCommitment.build_model(
|
| 29 |
-
instance=instance_v1,
|
| 30 |
-
formulation=UnitCommitment.Formulation(
|
| 31 |
-
transmission=UnitCommitment.ShiftFactorsFormulation(
|
| 32 |
-
precomputed_isf=zeros(0,0), precomputed_lodf=zeros(0,0)
|
| 33 |
-
)
|
| 34 |
),
|
| 35 |
-
variable_names=true
|
| 36 |
)
|
| 37 |
-
JuMP.write_to_file(
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
# ==========================================================
|
| 55 |
-
# 版本 3: Subhourly - 不加线路约束
|
| 56 |
-
# ==========================================================
|
| 57 |
-
println(">>> 正在生成 版本 3/4: Subhourly, 不加线路约束")
|
| 58 |
-
instance_v3_base = UnitCommitment.read(base_instance_name)
|
| 59 |
-
|
| 60 |
-
# 使用你找到的本地函数，把相同的 instance 传两次来充当"今天"和"明天"
|
| 61 |
-
instance_v3 = UnitCommitment.convert_to_subhourly(instance_v3_base, instance_v3_base)
|
| 62 |
-
|
| 63 |
-
# 同样地，清空线路数据以确保无网络约束
|
| 64 |
-
empty!(instance_v3.scenarios[1].lines)
|
| 65 |
-
|
| 66 |
-
model_v3 = UnitCommitment.build_model(
|
| 67 |
-
instance=instance_v3,
|
| 68 |
-
formulation=UnitCommitment.Formulation(
|
| 69 |
-
transmission=UnitCommitment.ShiftFactorsFormulation(
|
| 70 |
-
precomputed_isf=zeros(0,0), precomputed_lodf=zeros(0,0)
|
| 71 |
-
)
|
| 72 |
),
|
| 73 |
-
variable_names=true
|
| 74 |
)
|
| 75 |
-
JuMP.write_to_file(
|
| 76 |
-
println(" -> 成功保存: uc_subhourly_noline.mps\n")
|
| 77 |
-
|
| 78 |
|
| 79 |
-
|
| 80 |
-
|
| 81 |
-
# ==========================================================
|
| 82 |
-
println(">>> 正在生成 版本 4/4: Subhourly, 加线路约束")
|
| 83 |
-
instance_v4_base = UnitCommitment.read(base_instance_name)
|
| 84 |
-
|
| 85 |
-
# 转换为 Subhourly 数据
|
| 86 |
-
instance_v4 = UnitCommitment.convert_to_subhourly(instance_v4_base, instance_v4_base)
|
| 87 |
-
|
| 88 |
-
# 保留线路数据，直接 build 即可包含线路约束
|
| 89 |
-
model_v4 = UnitCommitment.build_model(instance=instance_v4, variable_names=true)
|
| 90 |
-
|
| 91 |
-
JuMP.write_to_file(model_v4, "uc_subhourly_withline.mps")
|
| 92 |
-
println(" -> 成功保存: uc_subhourly_withline.mps\n")
|
| 93 |
|
| 94 |
-
|
| 95 |
-
println("🎉 任务圆满完成！所有 4 个 MPS 文件均已生成！")
|
| 96 |
-
println("==================================================")
|
| 97 |
end
|
| 98 |
|
| 99 |
-
|
| 100 |
-
generate_mps_files()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
using JuMP
|
| 2 |
+
using UnitCommitment
|
| 3 |
|
| 4 |
+
function generate_mps_files(; base_instance_path::String = "instances/matpower/case30/2017-01-01.json.gz")
|
| 5 |
+
instance_hourly = UnitCommitment.read(base_instance_path)
|
| 6 |
+
instance_hourly_noline = deepcopy(instance_hourly)
|
| 7 |
+
empty!(instance_hourly_noline.scenarios[1].lines)
|
| 8 |
+
|
| 9 |
+
model_hourly_noline = UnitCommitment.build_model(
|
| 10 |
+
instance = instance_hourly_noline,
|
| 11 |
+
formulation = UnitCommitment.Formulation(
|
| 12 |
+
transmission = UnitCommitment.ShiftFactorsFormulation(
|
| 13 |
+
precomputed_isf = zeros(0, 0),
|
| 14 |
+
precomputed_lodf = zeros(0, 0),
|
| 15 |
+
),
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
),
|
| 17 |
+
variable_names = true,
|
| 18 |
)
|
| 19 |
+
JuMP.write_to_file(model_hourly_noline, "uc_default_noline.mps")
|
| 20 |
+
|
| 21 |
+
model_hourly_withline = UnitCommitment.build_model(instance = instance_hourly, variable_names = true)
|
| 22 |
+
JuMP.write_to_file(model_hourly_withline, "uc_default_withline.mps")
|
| 23 |
+
|
| 24 |
+
instance_sub = UnitCommitment.convert_to_subhourly(instance_hourly, instance_hourly)
|
| 25 |
+
instance_sub_noline = deepcopy(instance_sub)
|
| 26 |
+
empty!(instance_sub_noline.scenarios[1].lines)
|
| 27 |
+
|
| 28 |
+
model_sub_noline = UnitCommitment.build_model(
|
| 29 |
+
instance = instance_sub_noline,
|
| 30 |
+
formulation = UnitCommitment.Formulation(
|
| 31 |
+
transmission = UnitCommitment.ShiftFactorsFormulation(
|
| 32 |
+
precomputed_isf = zeros(0, 0),
|
| 33 |
+
precomputed_lodf = zeros(0, 0),
|
| 34 |
+
),
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 35 |
),
|
| 36 |
+
variable_names = true,
|
| 37 |
)
|
| 38 |
+
JuMP.write_to_file(model_sub_noline, "uc_subhourly_noline.mps")
|
|
|
|
|
|
|
| 39 |
|
| 40 |
+
model_sub_withline = UnitCommitment.build_model(instance = instance_sub, variable_names = true)
|
| 41 |
+
JuMP.write_to_file(model_sub_withline, "uc_subhourly_withline.mps")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 42 |
|
| 43 |
+
return nothing
|
|
|
|
|
|
|
| 44 |
end
|
| 45 |
|
| 46 |
+
generate_mps_files()
|
|
|
UnitCommitment_Trajectory_Test/docs/src/tutorials/customizing.jl
CHANGED
|
@@ -35,7 +35,7 @@ model = UnitCommitment.build_model(
|
|
| 35 |
isf_cutoff = 0.008,
|
| 36 |
lodf_cutoff = 0.003,
|
| 37 |
),
|
| 38 |
-
power_trajectories =
|
| 39 |
),
|
| 40 |
);
|
| 41 |
|
|
|
|
| 35 |
isf_cutoff = 0.008,
|
| 36 |
lodf_cutoff = 0.003,
|
| 37 |
),
|
| 38 |
+
power_trajectories = ArrCon2004.PowerTrajectories(),
|
| 39 |
),
|
| 40 |
);
|
| 41 |
|
UnitCommitment_Trajectory_Test/generate_dataset.jl
CHANGED
|
@@ -1,89 +1,167 @@
|
|
| 1 |
-
# =========================================================================
|
| 2 |
-
# 脚本名称: generate_dataset.jl (全量增强版)
|
| 3 |
-
# 功能: 自动化生成包含 case14, case30, case2383wp 的全量 MIP 优化模型
|
| 4 |
-
# 说明: 生成的 .mps 文件包含大量二进制变量，专用于混合整数规划 (MIP) 研究
|
| 5 |
-
# 路径: 输出结果将导出至上级目录的 UnitCommitment_Trajectory_Dataset 文件夹
|
| 6 |
-
# =========================================================================
|
| 7 |
-
|
| 8 |
-
using UnitCommitment
|
| 9 |
using JuMP
|
| 10 |
-
using
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
|
|
|
| 17 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 18 |
|
| 19 |
-
|
| 20 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 21 |
|
| 22 |
-
function run_full_generation()
|
| 23 |
-
println("🚀 开始全量数据集生成任务 (包含大型算例)...")
|
| 24 |
-
|
| 25 |
-
# 确保根目录存在
|
| 26 |
mkpath(output_root)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 27 |
|
| 28 |
-
|
| 29 |
-
println("\
|
| 30 |
-
|
| 31 |
-
|
| 32 |
-
for v in variants
|
| 33 |
-
mkpath(joinpath(output_root, case_name, v))
|
| 34 |
end
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 40 |
date_tag = split(file_name, ".")[1]
|
| 41 |
-
src_path = joinpath(
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
| 46 |
-
|
| 47 |
-
instance_v1 = UnitCommitment.read(src_path)
|
| 48 |
-
empty!(instance_v1.scenarios[1].lines)
|
| 49 |
-
model_v1 = UnitCommitment.build_model(
|
| 50 |
-
instance=instance_v1,
|
| 51 |
-
formulation=UnitCommitment.Formulation(
|
| 52 |
-
transmission=UnitCommitment.ShiftFactorsFormulation(precomputed_isf=zeros(0,0), precomputed_lodf=zeros(0,0))
|
| 53 |
-
),
|
| 54 |
-
variable_names=true
|
| 55 |
-
)
|
| 56 |
-
JuMP.write_to_file(model_v1, joinpath(output_root, case_name, "hourly_noline", "$(case_name)_$(date_tag)_h_noline.mps"))
|
| 57 |
-
|
| 58 |
-
# 2. Hourly With-Line
|
| 59 |
-
instance_v2 = UnitCommitment.read(src_path)
|
| 60 |
-
model_v2 = UnitCommitment.build_model(instance=instance_v2, variable_names=true)
|
| 61 |
-
JuMP.write_to_file(model_v2, joinpath(output_root, case_name, "hourly_withline", "$(case_name)_$(date_tag)_h_withline.mps"))
|
| 62 |
-
|
| 63 |
-
# 3. Subhourly No-Line
|
| 64 |
-
instance_v3_base = UnitCommitment.read(src_path)
|
| 65 |
-
instance_v3 = UnitCommitment.convert_to_subhourly(instance_v3_base, instance_v3_base)
|
| 66 |
-
empty!(instance_v3.scenarios[1].lines)
|
| 67 |
-
model_v3 = UnitCommitment.build_model(
|
| 68 |
-
instance=instance_v3,
|
| 69 |
-
formulation=UnitCommitment.Formulation(
|
| 70 |
-
transmission=UnitCommitment.ShiftFactorsFormulation(precomputed_isf=zeros(0,0), precomputed_lodf=zeros(0,0))
|
| 71 |
-
),
|
| 72 |
-
variable_names=true
|
| 73 |
-
)
|
| 74 |
-
JuMP.write_to_file(model_v3, joinpath(output_root, case_name, "subhourly_noline", "$(case_name)_$(date_tag)_s_noline.mps"))
|
| 75 |
-
|
| 76 |
-
# 4. Subhourly With-Line
|
| 77 |
-
instance_v4_base = UnitCommitment.read(src_path)
|
| 78 |
-
instance_v4 = UnitCommitment.convert_to_subhourly(instance_v4_base, instance_v4_base)
|
| 79 |
-
model_v4 = UnitCommitment.build_model(instance=instance_v4, variable_names=true)
|
| 80 |
-
JuMP.write_to_file(model_v4, joinpath(output_root, case_name, "subhourly_withline", "$(case_name)_$(date_tag)_s_withline.mps"))
|
| 81 |
-
|
| 82 |
-
# 及时释放内存 (Julia 的 GC 有时会有延迟)
|
| 83 |
-
model_v1 = model_v2 = model_v3 = model_v4 = nothing
|
| 84 |
end
|
| 85 |
end
|
| 86 |
-
|
|
|
|
|
|
|
| 87 |
end
|
| 88 |
|
| 89 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
using JuMP
|
| 2 |
+
using UnitCommitment
|
| 3 |
+
|
| 4 |
+
const DEFAULT_INPUT_ROOT = "instances/matpower"
|
| 5 |
+
const DEFAULT_OUTPUT_ROOT = "../UnitCommitment_Trajectory_Dataset"
|
| 6 |
+
const VARIANTS = ("hourly_noline", "hourly_withline", "subhourly_noline", "subhourly_withline")
|
| 7 |
+
|
| 8 |
+
function _build_noline_formulation()
|
| 9 |
+
return UnitCommitment.Formulation(
|
| 10 |
+
transmission = UnitCommitment.ShiftFactorsFormulation(
|
| 11 |
+
precomputed_isf = zeros(0, 0),
|
| 12 |
+
precomputed_lodf = zeros(0, 0),
|
| 13 |
+
),
|
| 14 |
+
)
|
| 15 |
+
end
|
| 16 |
+
|
| 17 |
+
function _write_mps(model::JuMP.Model, path::String)
|
| 18 |
+
mkpath(dirname(path))
|
| 19 |
+
JuMP.write_to_file(model, path)
|
| 20 |
+
return nothing
|
| 21 |
+
end
|
| 22 |
+
|
| 23 |
+
function _list_json_gz(case_dir::String)
|
| 24 |
+
files = filter(f -> endswith(f, ".json.gz"), readdir(case_dir))
|
| 25 |
+
sort!(files)
|
| 26 |
+
return files
|
| 27 |
+
end
|
| 28 |
+
|
| 29 |
+
function discover_matpower_cases(input_root::String = DEFAULT_INPUT_ROOT)
|
| 30 |
+
isdir(input_root) || error("Input directory does not exist: $input_root")
|
| 31 |
+
|
| 32 |
+
case_dirs = filter(d -> isdir(joinpath(input_root, d)), readdir(input_root))
|
| 33 |
+
sort!(case_dirs)
|
| 34 |
+
|
| 35 |
+
return [
|
| 36 |
+
(case_name, joinpath(input_root, case_name))
|
| 37 |
+
for case_name in case_dirs
|
| 38 |
+
if !isempty(_list_json_gz(joinpath(input_root, case_name)))
|
| 39 |
+
]
|
| 40 |
+
end
|
| 41 |
+
|
| 42 |
+
function _parse_case_filter()
|
| 43 |
+
raw = strip(get(ENV, "UC_CASES", ""))
|
| 44 |
+
isempty(raw) && return nothing
|
| 45 |
+
return Set(strip.(split(raw, ",")))
|
| 46 |
+
end
|
| 47 |
+
|
| 48 |
+
function _is_truthy_env(name::String)
|
| 49 |
+
value = lowercase(strip(get(ENV, name, "")))
|
| 50 |
+
return value in ("1", "true", "yes", "y")
|
| 51 |
+
end
|
| 52 |
+
|
| 53 |
+
function _selected_cases(input_root::String)
|
| 54 |
+
cases = discover_matpower_cases(input_root)
|
| 55 |
+
selected = _parse_case_filter()
|
| 56 |
+
selected === nothing && return cases
|
| 57 |
+
return filter(case -> case[1] in selected, cases)
|
| 58 |
+
end
|
| 59 |
|
| 60 |
+
function _generate_one_instance!(
|
| 61 |
+
case_name::AbstractString,
|
| 62 |
+
date_tag::AbstractString,
|
| 63 |
+
src_path::AbstractString,
|
| 64 |
+
output_root::AbstractString,
|
| 65 |
+
noline_formulation,
|
| 66 |
)
|
| 67 |
+
inst_hourly = UnitCommitment.read(src_path)
|
| 68 |
+
inst_hourly_noline = deepcopy(inst_hourly)
|
| 69 |
+
empty!(inst_hourly_noline.scenarios[1].lines)
|
| 70 |
+
|
| 71 |
+
model_hourly_noline = UnitCommitment.build_model(
|
| 72 |
+
instance = inst_hourly_noline,
|
| 73 |
+
formulation = noline_formulation,
|
| 74 |
+
variable_names = true,
|
| 75 |
+
)
|
| 76 |
+
_write_mps(
|
| 77 |
+
model_hourly_noline,
|
| 78 |
+
joinpath(output_root, case_name, "hourly_noline", "$(case_name)_$(date_tag)_h_noline.mps"),
|
| 79 |
+
)
|
| 80 |
+
|
| 81 |
+
model_hourly_withline = UnitCommitment.build_model(
|
| 82 |
+
instance = inst_hourly,
|
| 83 |
+
variable_names = true,
|
| 84 |
+
)
|
| 85 |
+
_write_mps(
|
| 86 |
+
model_hourly_withline,
|
| 87 |
+
joinpath(output_root, case_name, "hourly_withline", "$(case_name)_$(date_tag)_h_withline.mps"),
|
| 88 |
+
)
|
| 89 |
+
|
| 90 |
+
inst_sub = UnitCommitment.convert_to_subhourly(inst_hourly, inst_hourly)
|
| 91 |
+
inst_sub_noline = deepcopy(inst_sub)
|
| 92 |
+
empty!(inst_sub_noline.scenarios[1].lines)
|
| 93 |
+
|
| 94 |
+
model_sub_noline = UnitCommitment.build_model(
|
| 95 |
+
instance = inst_sub_noline,
|
| 96 |
+
formulation = noline_formulation,
|
| 97 |
+
variable_names = true,
|
| 98 |
+
)
|
| 99 |
+
_write_mps(
|
| 100 |
+
model_sub_noline,
|
| 101 |
+
joinpath(output_root, case_name, "subhourly_noline", "$(case_name)_$(date_tag)_s_noline.mps"),
|
| 102 |
+
)
|
| 103 |
|
| 104 |
+
model_sub_withline = UnitCommitment.build_model(
|
| 105 |
+
instance = inst_sub,
|
| 106 |
+
variable_names = true,
|
| 107 |
+
)
|
| 108 |
+
_write_mps(
|
| 109 |
+
model_sub_withline,
|
| 110 |
+
joinpath(output_root, case_name, "subhourly_withline", "$(case_name)_$(date_tag)_s_withline.mps"),
|
| 111 |
+
)
|
| 112 |
+
|
| 113 |
+
return nothing
|
| 114 |
+
end
|
| 115 |
+
|
| 116 |
+
function generate_dataset(;
|
| 117 |
+
input_root::String = get(ENV, "UC_INPUT_ROOT", DEFAULT_INPUT_ROOT),
|
| 118 |
+
output_root::String = get(ENV, "UC_OUTPUT_ROOT", DEFAULT_OUTPUT_ROOT),
|
| 119 |
+
)
|
| 120 |
+
cases = _selected_cases(input_root)
|
| 121 |
+
isempty(cases) && error("No cases selected under $input_root. Check UC_CASES or the input directory.")
|
| 122 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 123 |
mkpath(output_root)
|
| 124 |
+
noline_formulation = _build_noline_formulation()
|
| 125 |
+
|
| 126 |
+
total_instances = sum(length(_list_json_gz(case_dir)) for (_, case_dir) in cases)
|
| 127 |
+
println("Input root: $input_root")
|
| 128 |
+
println("Output root: $output_root")
|
| 129 |
+
println("Cases: $(length(cases))")
|
| 130 |
+
println("Instances: $total_instances")
|
| 131 |
+
println("Variants: $(length(VARIANTS))")
|
| 132 |
+
println("MPS files: $(total_instances * length(VARIANTS))")
|
| 133 |
|
| 134 |
+
if _is_truthy_env("UC_DRY_RUN")
|
| 135 |
+
println("\nDry run only. Set UC_DRY_RUN=0 or remove it to generate MPS files.")
|
| 136 |
+
for (case_name, case_dir) in cases
|
| 137 |
+
println(" $case_name: $(length(_list_json_gz(case_dir))) instances")
|
|
|
|
|
|
|
| 138 |
end
|
| 139 |
+
return nothing
|
| 140 |
+
end
|
| 141 |
+
|
| 142 |
+
for (case_index, (case_name, case_dir)) in enumerate(cases)
|
| 143 |
+
files = _list_json_gz(case_dir)
|
| 144 |
+
println("\n[$case_index/$(length(cases))] $case_name ($(length(files)) instances)")
|
| 145 |
+
|
| 146 |
+
for variant in VARIANTS
|
| 147 |
+
mkpath(joinpath(output_root, case_name, variant))
|
| 148 |
+
end
|
| 149 |
+
|
| 150 |
+
for (i, file_name) in enumerate(files)
|
| 151 |
date_tag = split(file_name, ".")[1]
|
| 152 |
+
src_path = joinpath(case_dir, file_name)
|
| 153 |
+
|
| 154 |
+
_generate_one_instance!(case_name, date_tag, src_path, output_root, noline_formulation)
|
| 155 |
+
|
| 156 |
+
GC.gc()
|
| 157 |
+
println(" [$case_name] $i/$(length(files)) $date_tag")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 158 |
end
|
| 159 |
end
|
| 160 |
+
|
| 161 |
+
println("\nDone. output_root=$output_root")
|
| 162 |
+
return nothing
|
| 163 |
end
|
| 164 |
|
| 165 |
+
if abspath(PROGRAM_FILE) == @__FILE__
|
| 166 |
+
generate_dataset()
|
| 167 |
+
end
|
UnitCommitment_Trajectory_Test/pmax-preprocessing.jl
CHANGED
|
@@ -1,208 +1,7 @@
|
|
| 1 |
-
|
| 2 |
-
# Part 1: 直接从JSON提取Pmax，按 90% 位置计算阈值，对前x%合格机组写入轨迹约束，并重排机组列表输出 JSON_v1
|
| 3 |
-
# Part 2: 读取 JSON_v1，对重排后的前10%和10%~20%机组修改 Minimum uptime (h)，输出 JSON_v2
|
| 4 |
|
| 5 |
-
|
| 6 |
-
|
| 7 |
|
| 8 |
-
|
| 9 |
-
|
| 10 |
-
# 输入:
|
| 11 |
-
# json_path : 原始JSON路径
|
| 12 |
-
# top_pct : 添加曲线的比例，默认前10%
|
| 13 |
-
# output_path : 输出的 JSON_v1 路径
|
| 14 |
-
# 输出:
|
| 15 |
-
# JSON_v1 路径（字符串）
|
| 16 |
-
# ─────────────────────────────────────────────────────────────────────────────
|
| 17 |
-
function add_trajectory_curves(
|
| 18 |
-
json_path::String;
|
| 19 |
-
top_pct::Float64 = 0.10,
|
| 20 |
-
output_path::String = replace(json_path, ".json" => "-part1.json"),
|
| 21 |
-
)
|
| 22 |
-
# ── 读取原始JSON ─────────────────────────────────────────────────────────
|
| 23 |
-
json_data = open(json_path) do io
|
| 24 |
-
if endswith(json_path, ".gz")
|
| 25 |
-
decompressor = GzipDecompressorStream(io)
|
| 26 |
-
JSON.parse(decompressor)
|
| 27 |
-
else
|
| 28 |
-
JSON.parse(io)
|
| 29 |
-
end
|
| 30 |
-
end
|
| 31 |
-
|
| 32 |
-
generators = json_data["Generators"]
|
| 33 |
-
|
| 34 |
-
# 仅处理含 "Minimum uptime (h)" 字段的机组
|
| 35 |
-
thermal_names = filter(
|
| 36 |
-
u -> haskey(generators[u], "Minimum uptime (h)"),
|
| 37 |
-
collect(keys(generators))
|
| 38 |
-
)
|
| 39 |
-
n_total = length(thermal_names)
|
| 40 |
-
|
| 41 |
-
# ── 1. 提取每个机组的 Pmax 和 Pmin ───────────────────────────────────────
|
| 42 |
-
# 直接读取 "Production cost curve (MW)" 数组的第一个值(Pmin)和最后一个值(Pmax)
|
| 43 |
-
Pmax_dict = Dict{String, Float64}()
|
| 44 |
-
Pmin_dict = Dict{String, Float64}()
|
| 45 |
-
|
| 46 |
-
for u in thermal_names
|
| 47 |
-
curve_mw = generators[u]["Production cost curve (MW)"]
|
| 48 |
-
Pmin_dict[u] = Float64(curve_mw[1])
|
| 49 |
-
Pmax_dict[u] = Float64(curve_mw[end])
|
| 50 |
-
end
|
| 51 |
-
|
| 52 |
-
# ── 2. 计算下界阈值 (Threshold) ──────────────────────────────────────────
|
| 53 |
-
# 将全网 Pmax 降序排列，取 90% 位置的值
|
| 54 |
-
all_pmax_desc = sort(collect(values(Pmax_dict)), rev=true)
|
| 55 |
-
idx_90 = max(1, ceil(Int, n_total * 0.90))
|
| 56 |
-
pmax_90_val = all_pmax_desc[idx_90]
|
| 57 |
-
|
| 58 |
-
# 阈值 = max(10, 降序第90%位置的值)
|
| 59 |
-
threshold = max(10.0, pmax_90_val)
|
| 60 |
-
|
| 61 |
-
println("── Part 1: 筛选与约束添加 ──")
|
| 62 |
-
println(" 热机组总数: $n_total")
|
| 63 |
-
println(" Pmax 降序第 90% 位置 (第 $idx_90 名) 的值: $pmax_90_val")
|
| 64 |
-
println(" Pmax 筛选下界阈值 (Threshold): $threshold")
|
| 65 |
-
|
| 66 |
-
# ── 3. 主干排序：主键 Minimum uptime 降序，次键 Pmax 降序 ───────────────
|
| 67 |
-
sort!(
|
| 68 |
-
thermal_names,
|
| 69 |
-
by = u -> (
|
| 70 |
-
get(generators[u], "Minimum uptime (h)", 0.0), # 主键：降序
|
| 71 |
-
Pmax_dict[u] # 次键：降序
|
| 72 |
-
),
|
| 73 |
-
rev = true,
|
| 74 |
-
)
|
| 75 |
-
|
| 76 |
-
# ── 4. 顺延挑选并重组数组供 Part 2 使用 ──────────────────────
|
| 77 |
-
qualified_units = String[]
|
| 78 |
-
disqualified_units = String[]
|
| 79 |
-
|
| 80 |
-
for u in thermal_names
|
| 81 |
-
if Pmax_dict[u] >= threshold
|
| 82 |
-
push!(qualified_units, u)
|
| 83 |
-
else
|
| 84 |
-
push!(disqualified_units, u)
|
| 85 |
-
end
|
| 86 |
-
end
|
| 87 |
-
|
| 88 |
-
# 核心重组逻辑：合格的排在最前面(保持原相对顺序)，淘汰的全部扔到末尾
|
| 89 |
-
# 这样 Part 2 按照索引 1~n_top 和 n_top+1~n_second 去读时，拿到的全都是合格机组
|
| 90 |
-
reordered_units = vcat(qualified_units, disqualified_units)
|
| 91 |
-
|
| 92 |
-
# ── 5. 确定名额并向合格的前 n_top 台机组写入轨迹曲线 ─────────────────────
|
| 93 |
-
n_top = max(1, ceil(Int, n_total * top_pct))
|
| 94 |
-
|
| 95 |
-
# 防止合格机组总数少于 n_top 的极端情况
|
| 96 |
-
actual_top_count = min(n_top, length(qualified_units))
|
| 97 |
-
|
| 98 |
-
println("\n── 选中并添加轨迹的机组名单 (前 10% 名额: $n_top) ──")
|
| 99 |
-
for u in reordered_units[1:actual_top_count]
|
| 100 |
-
uptime = get(generators[u], "Minimum uptime (h)", 0)
|
| 101 |
-
pmax = Pmax_dict[u]
|
| 102 |
-
pmin = Pmin_dict[u]
|
| 103 |
-
|
| 104 |
-
# 写入 Startup / Shutdown curve
|
| 105 |
-
generators[u]["Startup curve (MW)"] = [pmin / 2.0, pmin]
|
| 106 |
-
generators[u]["Shutdown curve (MW)"] = [pmin, pmin / 2.0]
|
| 107 |
-
|
| 108 |
-
println(" [写入轨迹] $(rpad(u,10)) Uptime=$uptime Pmax=$(round(pmax, digits=2)) Pmin=$(round(pmin, digits=2))")
|
| 109 |
-
end
|
| 110 |
-
|
| 111 |
-
println("\n── 被 Pmax 阈值淘汰的机组 (展示前几位) ──")
|
| 112 |
-
for u in disqualified_units[1:min(5, length(disqualified_units))]
|
| 113 |
-
uptime = get(generators[u], "Minimum uptime (h)", 0)
|
| 114 |
-
pmax = Pmax_dict[u]
|
| 115 |
-
println(" [不足下界] $(rpad(u,10)) Uptime=$uptime Pmax=$(round(pmax, digits=2)) < 阈值 $threshold")
|
| 116 |
-
end
|
| 117 |
-
|
| 118 |
-
# ── 6. 将重组后的结果存入元数据，交接给 Part 2 ───────────────────────────
|
| 119 |
-
json_data["_sorted_thermal_units"] = reordered_units
|
| 120 |
-
|
| 121 |
-
# ── 7. 写出 JSON_v1 ──────────────────────────────────────────────────────
|
| 122 |
-
open(output_path, "w") do f
|
| 123 |
-
JSON.print(f, json_data, 4)
|
| 124 |
-
end
|
| 125 |
-
println("\nPart 1 完成 → 输出保存至: $output_path")
|
| 126 |
-
|
| 127 |
-
return output_path
|
| 128 |
-
end
|
| 129 |
-
|
| 130 |
-
|
| 131 |
-
# ─────────────────────────────────────────────────────────────────────────────
|
| 132 |
-
# Part 2: 生成 JSON_v2 (修改 Minimum uptime)
|
| 133 |
-
# (注：此处代码根据需求完全保持原样，未做任何核心逻辑改动，无缝衔接 Part 1)
|
| 134 |
-
# ─────────────────────────────────────────────────────────────────────────────
|
| 135 |
-
function modify_min_uptime(
|
| 136 |
-
json_v1_path::String;
|
| 137 |
-
top_pct::Float64 = 0.10,
|
| 138 |
-
output_path::String = replace(json_v1_path, "-part1.json" => "-part2.json"),
|
| 139 |
-
)
|
| 140 |
-
# 读取 JSON_v1
|
| 141 |
-
json_data = JSON.parsefile(json_v1_path)
|
| 142 |
-
generators = json_data["Generators"]
|
| 143 |
-
|
| 144 |
-
# 读取 Part 1 保存的重排结果
|
| 145 |
-
haskey(json_data, "_sorted_thermal_units") ||
|
| 146 |
-
error("缺少 _sorted_thermal_units 元数据，请先运行 Part 1（add_trajectory_curves）")
|
| 147 |
-
|
| 148 |
-
sorted_units = json_data["_sorted_thermal_units"]
|
| 149 |
-
n_total = length(sorted_units)
|
| 150 |
-
|
| 151 |
-
# 计算两个区间的索引边界
|
| 152 |
-
n_top = max(1, ceil(Int, n_total * top_pct))
|
| 153 |
-
n_second = min(n_total, ceil(Int, n_total * top_pct * 2))
|
| 154 |
-
|
| 155 |
-
println("\n── Part 2: Uptime 修改 ──")
|
| 156 |
-
println(" 机组总数: $n_total")
|
| 157 |
-
println(" 前10%区间: 1 ~ $n_top")
|
| 158 |
-
println(" 10%~20%区间: $(n_top+1) ~ $n_second")
|
| 159 |
-
|
| 160 |
-
skipped_top = String[]
|
| 161 |
-
skipped_second = String[]
|
| 162 |
-
modified_top = String[]
|
| 163 |
-
modified_second= String[]
|
| 164 |
-
|
| 165 |
-
# ── 处理前 10% 机组 ──────────────────────────────────────────────────────
|
| 166 |
-
for u in sorted_units[1:n_top]
|
| 167 |
-
uptime = get(generators[u], "Minimum uptime (h)", 1)
|
| 168 |
-
if uptime <= 5
|
| 169 |
-
generators[u]["Minimum uptime (h)"] = uptime * 3
|
| 170 |
-
push!(modified_top, u)
|
| 171 |
-
println("[10% 区间 | ×3 修改] $u uptime: $uptime → $(uptime*3)")
|
| 172 |
-
else
|
| 173 |
-
push!(skipped_top, u)
|
| 174 |
-
println(" [10% 区间 | 跳过] $u uptime=$uptime > 5，不修改")
|
| 175 |
-
end
|
| 176 |
-
end
|
| 177 |
-
|
| 178 |
-
# ── 处理 10% ~ 20% 机组 ──────────────────────────────────────────────────
|
| 179 |
-
if n_top < n_second
|
| 180 |
-
for u in sorted_units[n_top+1:n_second]
|
| 181 |
-
uptime = get(generators[u], "Minimum uptime (h)", 1)
|
| 182 |
-
if uptime <= 5
|
| 183 |
-
generators[u]["Minimum uptime (h)"] = uptime * 2
|
| 184 |
-
push!(modified_second, u)
|
| 185 |
-
println("[20% 区间 | ×2 修改] $u uptime: $uptime → $(uptime*2)")
|
| 186 |
-
else
|
| 187 |
-
push!(skipped_second, u)
|
| 188 |
-
println(" [20% 区间 | 跳过] $u uptime=$uptime > 5，不修改")
|
| 189 |
-
end
|
| 190 |
-
end
|
| 191 |
-
end
|
| 192 |
-
|
| 193 |
-
# ── 删除元数据字段，不写入最终 JSON_v2 ──────────────────────────────────
|
| 194 |
-
delete!(json_data, "_sorted_thermal_units")
|
| 195 |
-
|
| 196 |
-
# ── 写出 JSON_v2 ────────────────────────────────────────────────────────
|
| 197 |
-
open(output_path, "w") do f
|
| 198 |
-
JSON.print(f, json_data, 4)
|
| 199 |
-
end
|
| 200 |
-
|
| 201 |
-
println("\nPart 2 完成 → 输出保存至: $output_path")
|
| 202 |
-
println(" 前10% 已修改(×3): $(length(modified_top)) 个")
|
| 203 |
-
println(" 前10% 已跳过(>5): $(length(skipped_top)) 个")
|
| 204 |
-
println(" 10~20% 已修改(×2): $(length(modified_second)) 个")
|
| 205 |
-
println(" 10~20% 已跳过(>5): $(length(skipped_second)) 个")
|
| 206 |
-
|
| 207 |
-
return output_path
|
| 208 |
-
end
|
|
|
|
| 1 |
+
using UnitCommitment
|
|
|
|
|
|
|
| 2 |
|
| 3 |
+
add_trajectory_curves(args...; kwargs...) =
|
| 4 |
+
UnitCommitment.add_trajectory_curves_to_source_data(args...; kwargs...)
|
| 5 |
|
| 6 |
+
modify_min_uptime(args...; kwargs...) =
|
| 7 |
+
UnitCommitment.modify_min_uptime_in_source_data(args...; kwargs...)
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
UnitCommitment_Trajectory_Test/src/UnitCommitment.jl
CHANGED
|
@@ -23,11 +23,13 @@ include("solution/methods/XavQiuWanThi2019/structs.jl")
|
|
| 23 |
include("solution/methods/ProgressiveHedging/structs.jl")
|
| 24 |
include("model/formulations/WanHob2016/structs.jl")
|
| 25 |
include("solution/methods/TimeDecomposition/structs.jl")
|
| 26 |
-
include("model/formulations/
|
| 27 |
|
| 28 |
include("import/egret.jl")
|
| 29 |
include("instance/read.jl")
|
| 30 |
include("instance/migrate.jl")
|
|
|
|
|
|
|
| 31 |
include("model/build.jl")
|
| 32 |
include("model/formulations/ArrCon2000/ramp.jl")
|
| 33 |
include("model/formulations/base/bus.jl")
|
|
@@ -48,7 +50,7 @@ include("model/formulations/MorLatRam2013/ramp.jl")
|
|
| 48 |
include("model/formulations/MorLatRam2013/scosts.jl")
|
| 49 |
include("model/formulations/PanGua2016/ramp.jl")
|
| 50 |
include("model/formulations/WanHob2016/ramp.jl")
|
| 51 |
-
include("model/formulations/
|
| 52 |
include("model/jumpext.jl")
|
| 53 |
include("solution/fix.jl")
|
| 54 |
include("solution/methods/XavQiuWanThi2019/enforce.jl")
|
|
@@ -76,4 +78,16 @@ include("lmp/conventional.jl")
|
|
| 76 |
include("lmp/aelmp.jl")
|
| 77 |
include("market/market.jl")
|
| 78 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 79 |
end
|
|
|
|
| 23 |
include("solution/methods/ProgressiveHedging/structs.jl")
|
| 24 |
include("model/formulations/WanHob2016/structs.jl")
|
| 25 |
include("solution/methods/TimeDecomposition/structs.jl")
|
| 26 |
+
include("model/formulations/ArrCon2004/structs.jl")
|
| 27 |
|
| 28 |
include("import/egret.jl")
|
| 29 |
include("instance/read.jl")
|
| 30 |
include("instance/migrate.jl")
|
| 31 |
+
include("instance/modify.jl")
|
| 32 |
+
include("instance/subhourly.jl")
|
| 33 |
include("model/build.jl")
|
| 34 |
include("model/formulations/ArrCon2000/ramp.jl")
|
| 35 |
include("model/formulations/base/bus.jl")
|
|
|
|
| 50 |
include("model/formulations/MorLatRam2013/scosts.jl")
|
| 51 |
include("model/formulations/PanGua2016/ramp.jl")
|
| 52 |
include("model/formulations/WanHob2016/ramp.jl")
|
| 53 |
+
include("model/formulations/ArrCon2004/powertrajectories.jl")
|
| 54 |
include("model/jumpext.jl")
|
| 55 |
include("solution/fix.jl")
|
| 56 |
include("solution/methods/XavQiuWanThi2019/enforce.jl")
|
|
|
|
| 78 |
include("lmp/aelmp.jl")
|
| 79 |
include("market/market.jl")
|
| 80 |
|
| 81 |
+
const xxx2005 = ArrCon2004
|
| 82 |
+
|
| 83 |
+
using .Modify: add_trajectory_curves_to_source_data, modify_min_uptime_in_source_data
|
| 84 |
+
export add_trajectory_curves_to_source_data, modify_min_uptime_in_source_data
|
| 85 |
+
|
| 86 |
+
export convert_to_subhourly
|
| 87 |
+
|
| 88 |
+
# Provide the file-path based conversion API from `src/instance/subhourly.jl`,
|
| 89 |
+
# without importing/overwriting the existing instance-object methods.
|
| 90 |
+
convert_to_subhourly(instance_path::AbstractString, next_day_path::AbstractString) =
|
| 91 |
+
Subhourly.convert_to_subhourly(instance_path, next_day_path)
|
| 92 |
+
|
| 93 |
end
|
UnitCommitment_Trajectory_Test/src/import/egret.jl
CHANGED
|
@@ -2,7 +2,7 @@
|
|
| 2 |
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
|
| 3 |
# Released under the modified BSD license. See COPYING.md for more details.
|
| 4 |
|
| 5 |
-
using DataStructures, JSON,
|
| 6 |
|
| 7 |
"""
|
| 8 |
|
|
|
|
| 2 |
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
|
| 3 |
# Released under the modified BSD license. See COPYING.md for more details.
|
| 4 |
|
| 5 |
+
using DataStructures, JSON, GZip
|
| 6 |
|
| 7 |
"""
|
| 8 |
|
UnitCommitment_Trajectory_Test/src/instance/modify.jl
ADDED
|
@@ -0,0 +1,242 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
module Modify
|
| 2 |
+
|
| 3 |
+
using JSON
|
| 4 |
+
using CodecZlib
|
| 5 |
+
|
| 6 |
+
export add_trajectory_curves_to_source_data, modify_min_uptime_in_source_data
|
| 7 |
+
|
| 8 |
+
function read_json_maybe_gz(path::String)
|
| 9 |
+
open(path) do io
|
| 10 |
+
if endswith(path, ".gz")
|
| 11 |
+
decompressor = GzipDecompressorStream(io)
|
| 12 |
+
return JSON.parse(decompressor)
|
| 13 |
+
end
|
| 14 |
+
return JSON.parse(io)
|
| 15 |
+
end
|
| 16 |
+
end
|
| 17 |
+
|
| 18 |
+
function write_json_pretty(path::String, json_data)
|
| 19 |
+
open(path, "w") do f
|
| 20 |
+
JSON.print(f, json_data, 4)
|
| 21 |
+
end
|
| 22 |
+
end
|
| 23 |
+
|
| 24 |
+
normalize_top_ratio(top_pct::Float64) = clamp(top_pct <= 1.0 ? top_pct : (top_pct / 100.0), 0.0, 1.0)
|
| 25 |
+
|
| 26 |
+
function get_eligible_thermal_units(generators)::Vector{String}
|
| 27 |
+
return filter(
|
| 28 |
+
u -> haskey(generators[u], "Minimum uptime (h)") &&
|
| 29 |
+
haskey(generators[u], "Production cost curve (MW)"),
|
| 30 |
+
collect(keys(generators)),
|
| 31 |
+
)
|
| 32 |
+
end
|
| 33 |
+
|
| 34 |
+
function build_unit_metric_dicts(generators, unit_names::Vector{String})
|
| 35 |
+
uptime_dict = Dict{String, Float64}()
|
| 36 |
+
pmax_dict = Dict{String, Float64}()
|
| 37 |
+
pmin_dict = Dict{String, Float64}()
|
| 38 |
+
|
| 39 |
+
for u in unit_names
|
| 40 |
+
curve_mw = generators[u]["Production cost curve (MW)"]
|
| 41 |
+
uptime_dict[u] = Float64(get(generators[u], "Minimum uptime (h)", 0.0))
|
| 42 |
+
pmin_dict[u] = Float64(curve_mw[1])
|
| 43 |
+
pmax_dict[u] = Float64(curve_mw[end])
|
| 44 |
+
end
|
| 45 |
+
return uptime_dict, pmax_dict, pmin_dict
|
| 46 |
+
end
|
| 47 |
+
|
| 48 |
+
function sort_by_uptime_then_pmax(unit_names::Vector{String}, uptime_dict, pmax_dict)
|
| 49 |
+
return sort(copy(unit_names), by = u -> (uptime_dict[u], pmax_dict[u]), rev = true)
|
| 50 |
+
end
|
| 51 |
+
|
| 52 |
+
function sort_by_pmax_then_uptime(unit_names::Vector{String}, uptime_dict, pmax_dict)
|
| 53 |
+
return sort(copy(unit_names), by = u -> (pmax_dict[u], uptime_dict[u]), rev = true)
|
| 54 |
+
end
|
| 55 |
+
|
| 56 |
+
function top_set(sorted_units::Vector{String}, ratio::Float64)
|
| 57 |
+
n_total = length(sorted_units)
|
| 58 |
+
n_total == 0 && return Set{String}()
|
| 59 |
+
n_top = max(1, ceil(Int, n_total * ratio))
|
| 60 |
+
return Set(sorted_units[1:n_top])
|
| 61 |
+
end
|
| 62 |
+
|
| 63 |
+
function build_four_categories(unit_order::Vector{String}, uptime_sorted::Vector{String}, pmax_sorted::Vector{String})
|
| 64 |
+
top_uptime_10 = top_set(uptime_sorted, 0.10)
|
| 65 |
+
top_uptime_20 = top_set(uptime_sorted, 0.20)
|
| 66 |
+
top_uptime_50 = top_set(uptime_sorted, 0.50)
|
| 67 |
+
|
| 68 |
+
top_pmax_10 = top_set(pmax_sorted, 0.10)
|
| 69 |
+
top_pmax_20 = top_set(pmax_sorted, 0.20)
|
| 70 |
+
top_pmax_50 = top_set(pmax_sorted, 0.50)
|
| 71 |
+
|
| 72 |
+
cat1_set = intersect(top_uptime_10, top_pmax_10)
|
| 73 |
+
cat2_set = setdiff(intersect(top_uptime_20, top_pmax_20), cat1_set)
|
| 74 |
+
cat3_set = setdiff(intersect(top_uptime_50, top_pmax_50), union(cat1_set, cat2_set))
|
| 75 |
+
cat4_set = setdiff(Set(unit_order), union(cat1_set, cat2_set, cat3_set))
|
| 76 |
+
|
| 77 |
+
category1 = [u for u in unit_order if u in cat1_set]
|
| 78 |
+
category2 = [u for u in unit_order if u in cat2_set]
|
| 79 |
+
category3 = [u for u in unit_order if u in cat3_set]
|
| 80 |
+
category4 = [u for u in unit_order if u in cat4_set]
|
| 81 |
+
|
| 82 |
+
return category1, category2, category3, category4
|
| 83 |
+
end
|
| 84 |
+
|
| 85 |
+
function add_trajectory_curves_to_source_data(
|
| 86 |
+
json_path::String;
|
| 87 |
+
top_pct::Float64 = 10.0,
|
| 88 |
+
output_path::String = replace(json_path, ".json" => "-part1.json"),
|
| 89 |
+
)
|
| 90 |
+
json_data = read_json_maybe_gz(json_path)
|
| 91 |
+
|
| 92 |
+
generators = json_data["Generators"]
|
| 93 |
+
thermal_names = get_eligible_thermal_units(generators)
|
| 94 |
+
n_total = length(thermal_names)
|
| 95 |
+
|
| 96 |
+
n_total == 0 && begin
|
| 97 |
+
println("── Part 1: 未发现可处理机组，直接写出原始数据 ──")
|
| 98 |
+
write_json_pretty(output_path, json_data)
|
| 99 |
+
return output_path
|
| 100 |
+
end
|
| 101 |
+
|
| 102 |
+
uptime_dict, pmax_dict, pmin_dict = build_unit_metric_dicts(generators, thermal_names)
|
| 103 |
+
|
| 104 |
+
top_ratio = normalize_top_ratio(top_pct)
|
| 105 |
+
top_count = min(n_total, max(1, ceil(Int, n_total * top_ratio)))
|
| 106 |
+
threshold = 10.0
|
| 107 |
+
|
| 108 |
+
println("── Part 1: 筛选与约束添加 ──")
|
| 109 |
+
println(" 热机组总数: $n_total")
|
| 110 |
+
println(" Top X% 参数: $top_pct (Top 数量: $top_count)")
|
| 111 |
+
println(" Pmax 下界阈值 (Threshold): $threshold")
|
| 112 |
+
|
| 113 |
+
uptime_sorted = sort_by_uptime_then_pmax(thermal_names, uptime_dict, pmax_dict)
|
| 114 |
+
pmax_sorted = sort_by_pmax_then_uptime(thermal_names, uptime_dict, pmax_dict)
|
| 115 |
+
|
| 116 |
+
top_uptime_set = Set(uptime_sorted[1:top_count])
|
| 117 |
+
top_pmax_set = Set(pmax_sorted[1:top_count])
|
| 118 |
+
|
| 119 |
+
qualified_units = String[]
|
| 120 |
+
disqualified_units = String[]
|
| 121 |
+
|
| 122 |
+
for u in uptime_sorted
|
| 123 |
+
if (u in top_uptime_set) && (u in top_pmax_set) && (pmax_dict[u] > threshold)
|
| 124 |
+
push!(qualified_units, u)
|
| 125 |
+
else
|
| 126 |
+
push!(disqualified_units, u)
|
| 127 |
+
end
|
| 128 |
+
end
|
| 129 |
+
|
| 130 |
+
reordered_units = vcat(qualified_units, disqualified_units)
|
| 131 |
+
|
| 132 |
+
println("\n── 选中并添加轨迹的机组名单 (交集且 Pmax > $threshold) ──")
|
| 133 |
+
for u in qualified_units
|
| 134 |
+
uptime = uptime_dict[u]
|
| 135 |
+
pmax = pmax_dict[u]
|
| 136 |
+
pmin = pmin_dict[u]
|
| 137 |
+
|
| 138 |
+
generators[u]["Startup curve (MW)"] = [pmin / 2.0, pmin]
|
| 139 |
+
generators[u]["Shutdown curve (MW)"] = [pmin, pmin / 2.0]
|
| 140 |
+
|
| 141 |
+
println(" [写入轨迹] $(rpad(u,10)) Uptime=$uptime Pmax=$(round(pmax, digits=2)) Pmin=$(round(pmin, digits=2))")
|
| 142 |
+
end
|
| 143 |
+
|
| 144 |
+
println("\n── 未满足筛选条件的机组 (展示前几位) ──")
|
| 145 |
+
for u in disqualified_units[1:min(5, length(disqualified_units))]
|
| 146 |
+
uptime = uptime_dict[u]
|
| 147 |
+
pmax = pmax_dict[u]
|
| 148 |
+
in_top_uptime = u in top_uptime_set
|
| 149 |
+
in_top_pmax = u in top_pmax_set
|
| 150 |
+
println(" [未入选] $(rpad(u,10)) Uptime=$uptime Pmax=$(round(pmax, digits=2)) TopUptime=$in_top_uptime TopPmax=$in_top_pmax")
|
| 151 |
+
end
|
| 152 |
+
|
| 153 |
+
json_data["_sorted_thermal_units"] = reordered_units
|
| 154 |
+
|
| 155 |
+
write_json_pretty(output_path, json_data)
|
| 156 |
+
println("\nPart 1 完成 → 输出保存至: $output_path")
|
| 157 |
+
|
| 158 |
+
return output_path
|
| 159 |
+
end
|
| 160 |
+
|
| 161 |
+
function modify_min_uptime_in_source_data(
|
| 162 |
+
json_v1_path::String;
|
| 163 |
+
output_path::String = replace(json_v1_path, "-part1.json" => "-part2.json"),
|
| 164 |
+
)
|
| 165 |
+
json_data = read_json_maybe_gz(json_v1_path)
|
| 166 |
+
generators = json_data["Generators"]
|
| 167 |
+
|
| 168 |
+
sorted_units = get_eligible_thermal_units(generators)
|
| 169 |
+
n_total = length(sorted_units)
|
| 170 |
+
|
| 171 |
+
n_total == 0 && begin
|
| 172 |
+
println("── Part 2: 未发现可处理机组，直接写出原始数据 ──")
|
| 173 |
+
if haskey(json_data, "_sorted_thermal_units")
|
| 174 |
+
delete!(json_data, "_sorted_thermal_units")
|
| 175 |
+
end
|
| 176 |
+
write_json_pretty(output_path, json_data)
|
| 177 |
+
return output_path
|
| 178 |
+
end
|
| 179 |
+
|
| 180 |
+
uptime_dict, pmax_dict, _ = build_unit_metric_dicts(generators, sorted_units)
|
| 181 |
+
uptime_sorted = sort_by_uptime_then_pmax(sorted_units, uptime_dict, pmax_dict)
|
| 182 |
+
pmax_sorted = sort_by_pmax_then_uptime(sorted_units, uptime_dict, pmax_dict)
|
| 183 |
+
|
| 184 |
+
category1, category2, category3, category4 =
|
| 185 |
+
build_four_categories(uptime_sorted, uptime_sorted, pmax_sorted)
|
| 186 |
+
|
| 187 |
+
println("\n── Part 2: Uptime / Downtime 分类修改 ──")
|
| 188 |
+
println(" 机组总数: $n_total")
|
| 189 |
+
println(" Category 1 (top10%∩top10%): $(length(category1))")
|
| 190 |
+
println(" Category 2 (top20%∩top20% \\ cat1): $(length(category2))")
|
| 191 |
+
println(" Category 3 (top50%∩top50% \\ cat1,2): $(length(category3))")
|
| 192 |
+
println(" Category 4 (remaining): $(length(category4))")
|
| 193 |
+
|
| 194 |
+
modified_cat1 = String[]
|
| 195 |
+
modified_cat2 = String[]
|
| 196 |
+
modified_cat3 = String[]
|
| 197 |
+
|
| 198 |
+
function apply_uptime_downtime_multipliers!(u::String, up_mult::Int, down_mult::Int, tag::String)
|
| 199 |
+
old_up = get(generators[u], "Minimum uptime (h)", nothing)
|
| 200 |
+
old_down = get(generators[u], "Minimum downtime (h)", nothing)
|
| 201 |
+
|
| 202 |
+
if old_up !== nothing
|
| 203 |
+
generators[u]["Minimum uptime (h)"] = old_up * up_mult
|
| 204 |
+
end
|
| 205 |
+
if old_down !== nothing
|
| 206 |
+
generators[u]["Minimum downtime (h)"] = old_down * down_mult
|
| 207 |
+
end
|
| 208 |
+
|
| 209 |
+
println("[$tag] $u uptime: $old_up → $(get(generators[u], "Minimum uptime (h)", old_up)) downtime: $old_down → $(get(generators[u], "Minimum downtime (h)", old_down))")
|
| 210 |
+
end
|
| 211 |
+
|
| 212 |
+
for u in category1
|
| 213 |
+
apply_uptime_downtime_multipliers!(u, 4, 3, "Category 1")
|
| 214 |
+
push!(modified_cat1, u)
|
| 215 |
+
end
|
| 216 |
+
|
| 217 |
+
for u in category2
|
| 218 |
+
apply_uptime_downtime_multipliers!(u, 3, 2, "Category 2")
|
| 219 |
+
push!(modified_cat2, u)
|
| 220 |
+
end
|
| 221 |
+
|
| 222 |
+
for u in category3
|
| 223 |
+
apply_uptime_downtime_multipliers!(u, 2, 2, "Category 3")
|
| 224 |
+
push!(modified_cat3, u)
|
| 225 |
+
end
|
| 226 |
+
|
| 227 |
+
if haskey(json_data, "_sorted_thermal_units")
|
| 228 |
+
delete!(json_data, "_sorted_thermal_units")
|
| 229 |
+
end
|
| 230 |
+
|
| 231 |
+
write_json_pretty(output_path, json_data)
|
| 232 |
+
|
| 233 |
+
println("\nPart 2 完成 → 输出保存至: $output_path")
|
| 234 |
+
println(" Category 1 已修改 (uptime×4, downtime×3): $(length(modified_cat1)) 个")
|
| 235 |
+
println(" Category 2 已修改 (uptime×3, downtime×2): $(length(modified_cat2)) 个")
|
| 236 |
+
println(" Category 3 已修改 (uptime×2, downtime×2): $(length(modified_cat3)) 个")
|
| 237 |
+
println(" Category 4 未修改: $(length(category4)) 个")
|
| 238 |
+
|
| 239 |
+
return output_path
|
| 240 |
+
end
|
| 241 |
+
|
| 242 |
+
end
|
UnitCommitment_Trajectory_Test/src/instance/read.jl
CHANGED
|
@@ -6,7 +6,7 @@
|
|
| 6 |
using Printf # For formatted string printing
|
| 7 |
using JSON # For parsing JSON files
|
| 8 |
using DataStructures # For OrderedDict and other data structures
|
| 9 |
-
using
|
| 10 |
import Base: getindex, time # Import specific functions from Base module
|
| 11 |
|
| 12 |
# Define constant URL for downloading benchmark instances
|
|
@@ -139,7 +139,7 @@ Helper function to read a single scenario from a file path
|
|
| 139 |
function _read_scenario(path::String)::UnitCommitmentScenario
|
| 140 |
# Check if file is gzipped and read accordingly
|
| 141 |
if endswith(path, ".gz")
|
| 142 |
-
scenario = _read(
|
| 143 |
elseif endswith(path, ".json")
|
| 144 |
scenario = _read(open(path))
|
| 145 |
else
|
|
@@ -164,7 +164,7 @@ Helper function to read JSON from a file path (handles both .json and .gz files)
|
|
| 164 |
function _read_json(path::String)::OrderedDict
|
| 165 |
# Open file based on extension (gzipped or plain JSON)
|
| 166 |
if endswith(path, ".gz")
|
| 167 |
-
file =
|
| 168 |
else
|
| 169 |
file = open(path)
|
| 170 |
end
|
|
|
|
| 6 |
using Printf # For formatted string printing
|
| 7 |
using JSON # For parsing JSON files
|
| 8 |
using DataStructures # For OrderedDict and other data structures
|
| 9 |
+
using GZip # For reading gzipped files
|
| 10 |
import Base: getindex, time # Import specific functions from Base module
|
| 11 |
|
| 12 |
# Define constant URL for downloading benchmark instances
|
|
|
|
| 139 |
function _read_scenario(path::String)::UnitCommitmentScenario
|
| 140 |
# Check if file is gzipped and read accordingly
|
| 141 |
if endswith(path, ".gz")
|
| 142 |
+
scenario = _read(gzopen(path))
|
| 143 |
elseif endswith(path, ".json")
|
| 144 |
scenario = _read(open(path))
|
| 145 |
else
|
|
|
|
| 164 |
function _read_json(path::String)::OrderedDict
|
| 165 |
# Open file based on extension (gzipped or plain JSON)
|
| 166 |
if endswith(path, ".gz")
|
| 167 |
+
file = GZip.gzopen(path)
|
| 168 |
else
|
| 169 |
file = open(path)
|
| 170 |
end
|
UnitCommitment_Trajectory_Test/src/instance/subhourly.jl
ADDED
|
@@ -0,0 +1,271 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""
|
| 2 |
+
Subhourly
|
| 3 |
+
|
| 4 |
+
Module for converting UC instances from 40-minute time periods (36 periods/day)
|
| 5 |
+
to 20-minute time periods (72 periods/day).
|
| 6 |
+
"""
|
| 7 |
+
module Subhourly
|
| 8 |
+
|
| 9 |
+
using Dates
|
| 10 |
+
import ..UnitCommitment
|
| 11 |
+
|
| 12 |
+
export convert_to_subhourly, interpolate_values, repeat_values
|
| 13 |
+
|
| 14 |
+
"""
|
| 15 |
+
convert_to_subhourly(instance_path::AbstractString, next_day_path::AbstractString)
|
| 16 |
+
|
| 17 |
+
Convert a UC instance from 36 time periods (40 minutes each) to 72 time periods (20 minutes each).
|
| 18 |
+
|
| 19 |
+
# Arguments
|
| 20 |
+
- `instance_path::AbstractString`: Path to the current day's instance
|
| 21 |
+
- `next_day_path::AbstractString`: Path to the next day's instance (needed for interpolation at boundaries)
|
| 22 |
+
|
| 23 |
+
# Returns
|
| 24 |
+
- Modified `UnitCommitmentInstance` with 72 time periods
|
| 25 |
+
|
| 26 |
+
# Details
|
| 27 |
+
The function performs the following transformations:
|
| 28 |
+
1. **Interpolated quantities** (demands, profiled unit outputs): Linear interpolation using next day's first period
|
| 29 |
+
2. **Repeated quantities** (max_power, min_power, flow limits): Each value repeated twice
|
| 30 |
+
3. **Ramping capacities**: Halved (since time periods are half the duration)
|
| 31 |
+
4. **Time period counts** (min_uptime, min_downtime, startup delay): Doubled
|
| 32 |
+
5. **Power production costs (not the fixed startup costs)**: Halved
|
| 33 |
+
|
| 34 |
+
# Example
|
| 35 |
+
```julia
|
| 36 |
+
current_instance = convert_to_subhourly(
|
| 37 |
+
"matpower/case14/2017-01-01",
|
| 38 |
+
"matpower/case14/2017-01-02"
|
| 39 |
+
)
|
| 40 |
+
println("Total time periods: ", current_instance.time) # Should be 72
|
| 41 |
+
```
|
| 42 |
+
"""
|
| 43 |
+
function convert_to_subhourly(instance_path::AbstractString, next_day_path::AbstractString)
|
| 44 |
+
# Read instances
|
| 45 |
+
instance = read_instance(instance_path)
|
| 46 |
+
next_instance = read_instance(next_day_path)
|
| 47 |
+
|
| 48 |
+
return convert_to_subhourly(instance, next_instance)
|
| 49 |
+
end
|
| 50 |
+
|
| 51 |
+
"""
|
| 52 |
+
convert_to_subhourly(instance::UnitCommitment.UnitCommitmentInstance,
|
| 53 |
+
next_instance::UnitCommitment.UnitCommitmentInstance)
|
| 54 |
+
|
| 55 |
+
Convert a UC instance from 36 time periods to 72 time periods using instance objects.
|
| 56 |
+
"""
|
| 57 |
+
function convert_to_subhourly(instance, next_instance)
|
| 58 |
+
sc_current = instance.scenarios[1]
|
| 59 |
+
sc_next = next_instance.scenarios[1]
|
| 60 |
+
|
| 61 |
+
# Process buses - interpolate loads
|
| 62 |
+
for i in 1:length(sc_current.buses)
|
| 63 |
+
load_current = sc_current.buses[i].load
|
| 64 |
+
load_next_first = sc_next.buses[i].load[1]
|
| 65 |
+
sc_current.buses[i].load = interpolate_values(load_current, load_next_first)
|
| 66 |
+
end
|
| 67 |
+
|
| 68 |
+
# Process thermal units
|
| 69 |
+
for i in 1:length(sc_current.thermal_units)
|
| 70 |
+
unit = sc_current.thermal_units[i]
|
| 71 |
+
unit_next = sc_next.thermal_units[i]
|
| 72 |
+
|
| 73 |
+
# Repeat time-dependent vector quantities
|
| 74 |
+
unit.max_power = repeat_values(unit.max_power)
|
| 75 |
+
unit.min_power = repeat_values(unit.min_power)
|
| 76 |
+
unit.must_run = repeat_values(unit.must_run)
|
| 77 |
+
unit.min_power_cost = repeat_values(unit.min_power_cost)
|
| 78 |
+
|
| 79 |
+
# Process cost segments
|
| 80 |
+
for j in 1:length(unit.cost_segments)
|
| 81 |
+
# cost should be repeated and then halved
|
| 82 |
+
unit.cost_segments[j].cost = interpolate_values(unit.cost_segments[j].cost, unit.cost_segments[j].cost[1]) ./ 2.0
|
| 83 |
+
unit.cost_segments[j].mw = interpolate_values(unit.cost_segments[j].mw, unit.cost_segments[j].mw[1])
|
| 84 |
+
end
|
| 85 |
+
|
| 86 |
+
# Repeat commitment status
|
| 87 |
+
unit.commitment_status = repeat_values(unit.commitment_status)
|
| 88 |
+
|
| 89 |
+
# Halve ramping capacities per time period (since time periods are half the duration)
|
| 90 |
+
unit.ramp_up_limit = unit.ramp_up_limit / 2.0
|
| 91 |
+
unit.ramp_down_limit = unit.ramp_down_limit / 2.0
|
| 92 |
+
# Note: startup_limit and shutdown_limit are NOT modified (they are power limits, not per-period rates)
|
| 93 |
+
|
| 94 |
+
# Double time period counts
|
| 95 |
+
unit.min_uptime = unit.min_uptime * 2
|
| 96 |
+
unit.min_downtime = unit.min_downtime * 2
|
| 97 |
+
|
| 98 |
+
# Double startup delays in startup categories
|
| 99 |
+
for startup_cat in unit.startup_categories
|
| 100 |
+
startup_cat.delay = startup_cat.delay * 2
|
| 101 |
+
end
|
| 102 |
+
end
|
| 103 |
+
|
| 104 |
+
# Process transmission lines
|
| 105 |
+
for i in 1:length(sc_current.lines)
|
| 106 |
+
line = sc_current.lines[i]
|
| 107 |
+
|
| 108 |
+
# Repeat flow limits
|
| 109 |
+
line.normal_flow_limit = repeat_values(line.normal_flow_limit)
|
| 110 |
+
line.emergency_flow_limit = repeat_values(line.emergency_flow_limit)
|
| 111 |
+
line.flow_limit_penalty = repeat_values(line.flow_limit_penalty)
|
| 112 |
+
end
|
| 113 |
+
|
| 114 |
+
# Process reserves - interpolate
|
| 115 |
+
for i in 1:length(sc_current.reserves)
|
| 116 |
+
reserve = sc_current.reserves[i]
|
| 117 |
+
reserve_next = sc_next.reserves[i]
|
| 118 |
+
|
| 119 |
+
# Interpolate reserve requirements
|
| 120 |
+
reserve.amount = interpolate_values(reserve.amount, reserve_next.amount[1])
|
| 121 |
+
end
|
| 122 |
+
|
| 123 |
+
# Process price-sensitive loads - interpolate
|
| 124 |
+
for i in 1:length(sc_current.price_sensitive_loads)
|
| 125 |
+
psl = sc_current.price_sensitive_loads[i]
|
| 126 |
+
psl_next = sc_next.price_sensitive_loads[i]
|
| 127 |
+
|
| 128 |
+
# Interpolate demand and revenue
|
| 129 |
+
psl.demand = interpolate_values(psl.demand, psl_next.demand[1])
|
| 130 |
+
psl.revenue = interpolate_values(psl.revenue, psl_next.revenue[1])
|
| 131 |
+
end
|
| 132 |
+
|
| 133 |
+
# Process profiled units (renewables)
|
| 134 |
+
for i in 1:length(sc_current.profiled_units)
|
| 135 |
+
pu = sc_current.profiled_units[i]
|
| 136 |
+
pu_next = sc_next.profiled_units[i]
|
| 137 |
+
|
| 138 |
+
# Interpolate renewable profiles
|
| 139 |
+
pu.min_power = interpolate_values(pu.min_power, pu_next.min_power[1])
|
| 140 |
+
pu.max_power = interpolate_values(pu.max_power, pu_next.max_power[1])
|
| 141 |
+
pu.cost = interpolate_values(pu.cost, pu_next.cost[1])
|
| 142 |
+
end
|
| 143 |
+
|
| 144 |
+
# Process storage units
|
| 145 |
+
for i in 1:length(sc_current.storage_units)
|
| 146 |
+
su = sc_current.storage_units[i]
|
| 147 |
+
su_next = sc_next.storage_units[i]
|
| 148 |
+
|
| 149 |
+
# Interpolate storage levels
|
| 150 |
+
su.min_level = interpolate_values(su.min_level, su_next.min_level[1])
|
| 151 |
+
su.max_level = interpolate_values(su.max_level, su_next.max_level[1])
|
| 152 |
+
|
| 153 |
+
# Repeat other storage parameters
|
| 154 |
+
su.simultaneous_charge_and_discharge = repeat_values(su.simultaneous_charge_and_discharge)
|
| 155 |
+
su.charge_cost = interpolate_values(su.charge_cost, su_next.charge_cost[1])
|
| 156 |
+
su.discharge_cost = interpolate_values(su.discharge_cost, su_next.discharge_cost[1])
|
| 157 |
+
su.charge_efficiency = repeat_values(su.charge_efficiency)
|
| 158 |
+
su.discharge_efficiency = repeat_values(su.discharge_efficiency)
|
| 159 |
+
su.loss_factor = repeat_values(su.loss_factor)
|
| 160 |
+
|
| 161 |
+
# Repeat rate limits
|
| 162 |
+
su.min_charge_rate = repeat_values(su.min_charge_rate)
|
| 163 |
+
su.max_charge_rate = repeat_values(su.max_charge_rate)
|
| 164 |
+
su.min_discharge_rate = repeat_values(su.min_discharge_rate)
|
| 165 |
+
su.max_discharge_rate = repeat_values(su.max_discharge_rate)
|
| 166 |
+
end
|
| 167 |
+
|
| 168 |
+
# Process scenario-level fields
|
| 169 |
+
sc_current.power_balance_penalty = repeat_values(sc_current.power_balance_penalty)
|
| 170 |
+
|
| 171 |
+
# Update time count
|
| 172 |
+
sc_current.time = 72
|
| 173 |
+
instance.time = 72
|
| 174 |
+
|
| 175 |
+
return instance
|
| 176 |
+
end
|
| 177 |
+
|
| 178 |
+
"""
|
| 179 |
+
interpolate_values(values::Vector{T}, next_first::T) where T
|
| 180 |
+
|
| 181 |
+
Interpolate a vector of 36 values to 72 values using linear interpolation.
|
| 182 |
+
|
| 183 |
+
# Arguments
|
| 184 |
+
- `values::Vector{T}`: Original 36-element vector
|
| 185 |
+
- `next_first::T`: First value from the next day (for boundary interpolation)
|
| 186 |
+
|
| 187 |
+
# Returns
|
| 188 |
+
- 72-element vector with interpolated values
|
| 189 |
+
|
| 190 |
+
# Details
|
| 191 |
+
For each pair of consecutive values, inserts an interpolated midpoint.
|
| 192 |
+
Uses `next_first` to interpolate the value after the last period.
|
| 193 |
+
|
| 194 |
+
# Example
|
| 195 |
+
```julia
|
| 196 |
+
interpolate_values([10.0, 20.0, 30.0], 40.0)
|
| 197 |
+
# Returns: [10.0, 15.0, 20.0, 25.0, 30.0, 35.0]
|
| 198 |
+
```
|
| 199 |
+
"""
|
| 200 |
+
function interpolate_values(values::Vector{T}, next_first::T) where T
|
| 201 |
+
n = length(values)
|
| 202 |
+
result = Vector{T}(undef, 2 * n)
|
| 203 |
+
|
| 204 |
+
for i in 1:n-1
|
| 205 |
+
result[2*i-1] = values[i]
|
| 206 |
+
result[2*i] = (values[i] + values[i+1]) / 2
|
| 207 |
+
end
|
| 208 |
+
|
| 209 |
+
# Handle the last period using next day's first value
|
| 210 |
+
result[2*n-1] = values[n]
|
| 211 |
+
result[2*n] = (values[n] + next_first) / 2
|
| 212 |
+
|
| 213 |
+
return result
|
| 214 |
+
end
|
| 215 |
+
|
| 216 |
+
"""
|
| 217 |
+
repeat_values(values::Vector{T}) where T
|
| 218 |
+
|
| 219 |
+
Repeat each element of a 36-element vector to create a 72-element vector.
|
| 220 |
+
|
| 221 |
+
# Arguments
|
| 222 |
+
- `values::Vector{T}`: Original 36-element vector
|
| 223 |
+
|
| 224 |
+
# Returns
|
| 225 |
+
- 72-element vector with each value repeated twice
|
| 226 |
+
|
| 227 |
+
# Example
|
| 228 |
+
```julia
|
| 229 |
+
repeat_values([1, 2, 3])
|
| 230 |
+
# Returns: [1, 1, 2, 2, 3, 3]
|
| 231 |
+
```
|
| 232 |
+
"""
|
| 233 |
+
function repeat_values(values::Vector{T}) where T
|
| 234 |
+
n = length(values)
|
| 235 |
+
result = Vector{T}(undef, 2 * n)
|
| 236 |
+
|
| 237 |
+
for i in 1:n
|
| 238 |
+
result[2*i-1] = values[i]
|
| 239 |
+
result[2*i] = values[i]
|
| 240 |
+
end
|
| 241 |
+
|
| 242 |
+
return result
|
| 243 |
+
end
|
| 244 |
+
|
| 245 |
+
"""
|
| 246 |
+
read_instance(path::AbstractString)
|
| 247 |
+
|
| 248 |
+
Read a UC instance from a local file or benchmark.
|
| 249 |
+
|
| 250 |
+
# Arguments
|
| 251 |
+
- `path::AbstractString`: Path to instance file or benchmark name
|
| 252 |
+
|
| 253 |
+
# Returns
|
| 254 |
+
- `UnitCommitmentInstance` object
|
| 255 |
+
"""
|
| 256 |
+
function read_instance(path::AbstractString)
|
| 257 |
+
# Check if path exists locally with common extensions
|
| 258 |
+
if isfile(path)
|
| 259 |
+
return UnitCommitment.read(path)
|
| 260 |
+
elseif isfile(path * ".json.gz")
|
| 261 |
+
return UnitCommitment.read(path * ".json.gz")
|
| 262 |
+
elseif isfile(path * ".json")
|
| 263 |
+
return UnitCommitment.read(path * ".json")
|
| 264 |
+
else
|
| 265 |
+
# Try reading as benchmark
|
| 266 |
+
return UnitCommitment.read_benchmark(path)
|
| 267 |
+
end
|
| 268 |
+
end
|
| 269 |
+
|
| 270 |
+
end # module
|
| 271 |
+
|
UnitCommitment_Trajectory_Test/src/model/formulations/{xxx2005 → ArrCon2004}/powertrajectories.jl
RENAMED
|
@@ -2,7 +2,7 @@ function _add_power_trajectory_eqs!(
|
|
| 2 |
model::JuMP.Model,
|
| 3 |
g::ThermalUnit,
|
| 4 |
formulation_prod_vars::Gar1962.ProdVars,
|
| 5 |
-
formulation_power_trajectories::
|
| 6 |
formulation_status_vars::Gar1962.StatusVars,
|
| 7 |
sc::UnitCommitmentScenario,
|
| 8 |
)::Nothing
|
|
@@ -165,4 +165,4 @@ function _add_power_trajectory_eqs!(
|
|
| 165 |
)
|
| 166 |
end
|
| 167 |
return
|
| 168 |
-
end
|
|
|
|
| 2 |
model::JuMP.Model,
|
| 3 |
g::ThermalUnit,
|
| 4 |
formulation_prod_vars::Gar1962.ProdVars,
|
| 5 |
+
formulation_power_trajectories::ArrCon2004.PowerTrajectories,
|
| 6 |
formulation_status_vars::Gar1962.StatusVars,
|
| 7 |
sc::UnitCommitmentScenario,
|
| 8 |
)::Nothing
|
|
|
|
| 165 |
)
|
| 166 |
end
|
| 167 |
return
|
| 168 |
+
end
|
UnitCommitment_Trajectory_Test/src/model/formulations/{xxx2005 → ArrCon2004}/structs.jl
RENAMED
|
@@ -1,7 +1,7 @@
|
|
| 1 |
-
module
|
| 2 |
|
| 3 |
import ..PowerTrajectoriesFormulation
|
| 4 |
|
| 5 |
struct PowerTrajectories <: PowerTrajectoriesFormulation end
|
| 6 |
|
| 7 |
-
end
|
|
|
|
| 1 |
+
module ArrCon2004
|
| 2 |
|
| 3 |
import ..PowerTrajectoriesFormulation
|
| 4 |
|
| 5 |
struct PowerTrajectories <: PowerTrajectoriesFormulation end
|
| 6 |
|
| 7 |
+
end
|
UnitCommitment_Trajectory_Test/src/model/formulations/Gar1962/prod.jl
CHANGED
|
@@ -59,7 +59,7 @@ function _add_production_limit_eqs!(
|
|
| 59 |
model::JuMP.Model,
|
| 60 |
g::ThermalUnit,
|
| 61 |
formulation_prod_vars::Gar1962.ProdVars,
|
| 62 |
-
formulation_power_trajectories::
|
| 63 |
sc::UnitCommitmentScenario
|
| 64 |
)::Nothing
|
| 65 |
if isempty(g.startup_curve) || isempty(g.shutdown_curve)
|
|
|
|
| 59 |
model::JuMP.Model,
|
| 60 |
g::ThermalUnit,
|
| 61 |
formulation_prod_vars::Gar1962.ProdVars,
|
| 62 |
+
formulation_power_trajectories::ArrCon2004.PowerTrajectories,
|
| 63 |
sc::UnitCommitmentScenario
|
| 64 |
)::Nothing
|
| 65 |
if isempty(g.startup_curve) || isempty(g.shutdown_curve)
|
UnitCommitment_Trajectory_Test/test/test_instance_modification.jl
ADDED
|
@@ -0,0 +1,305 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
using UnitCommitment
|
| 2 |
+
using HiGHS
|
| 3 |
+
import JuMP
|
| 4 |
+
|
| 5 |
+
CASES =[
|
| 6 |
+
("testdata/case2383wp/2017-07-27.json.gz", "case2383wp"),
|
| 7 |
+
# ("testdata/case2736sp/2017-07-21.json.gz", "case2736sp")
|
| 8 |
+
]
|
| 9 |
+
|
| 10 |
+
function build_and_solve(instance, use_traj)
|
| 11 |
+
formulation = use_traj ?
|
| 12 |
+
UnitCommitment.Formulation(
|
| 13 |
+
power_trajectories = UnitCommitment.ArrCon2004.PowerTrajectories()
|
| 14 |
+
) :
|
| 15 |
+
UnitCommitment.Formulation()
|
| 16 |
+
model = UnitCommitment.build_model(
|
| 17 |
+
instance = instance,
|
| 18 |
+
optimizer = HiGHS.Optimizer,
|
| 19 |
+
formulation = formulation,
|
| 20 |
+
)
|
| 21 |
+
JuMP.set_silent(model)
|
| 22 |
+
JuMP.optimize!(model)
|
| 23 |
+
return model
|
| 24 |
+
end
|
| 25 |
+
|
| 26 |
+
function get_actual_power(model, g, t, T, prev_p)
|
| 27 |
+
uname = g.name
|
| 28 |
+
UD = length(g.startup_curve)
|
| 29 |
+
DD = length(g.shutdown_curve)
|
| 30 |
+
startup_curve = g.startup_curve
|
| 31 |
+
shutdown_curve = g.shutdown_curve
|
| 32 |
+
Pmin = g.min_power[t]
|
| 33 |
+
Pmax = g.max_power[t]
|
| 34 |
+
RU = g.ramp_up_limit
|
| 35 |
+
|
| 36 |
+
v = round(JuMP.value(model[:is_on][uname, t]))
|
| 37 |
+
y = round(JuMP.value(model[:switch_on][uname, t]))
|
| 38 |
+
pa = JuMP.value(model[:prod_above]["s1", uname, t])
|
| 39 |
+
|
| 40 |
+
in_su = UD > 0 && any(
|
| 41 |
+
round(JuMP.value(model[:switch_on][uname, t-i+1])) == 1.0
|
| 42 |
+
for i in 1:UD if t-i+1 >= 1)
|
| 43 |
+
in_sd = DD > 0 && any(
|
| 44 |
+
round(JuMP.value(model[:switch_off][uname, t+i])) == 1.0
|
| 45 |
+
for i in 1:DD if t+i <= T)
|
| 46 |
+
|
| 47 |
+
p = 0.0
|
| 48 |
+
if in_su
|
| 49 |
+
for i in 1:UD
|
| 50 |
+
if t-i+1 >= 1 && round(JuMP.value(model[:switch_on][uname, t-i+1])) == 1.0
|
| 51 |
+
p = startup_curve[i]; break
|
| 52 |
+
end
|
| 53 |
+
end
|
| 54 |
+
elseif in_sd
|
| 55 |
+
for i in 1:DD
|
| 56 |
+
if t+i <= T && round(JuMP.value(model[:switch_off][uname, t+i])) == 1.0
|
| 57 |
+
p = shutdown_curve[DD-i+1]; break
|
| 58 |
+
end
|
| 59 |
+
end
|
| 60 |
+
elseif v > 0.5
|
| 61 |
+
p = pa + Pmin
|
| 62 |
+
end
|
| 63 |
+
|
| 64 |
+
status = if v == 0.0; "Offline"
|
| 65 |
+
elseif y == 1.0; "Startup_t1"
|
| 66 |
+
elseif in_su; "Startup_traj"
|
| 67 |
+
elseif in_sd; "Shutdown_traj"
|
| 68 |
+
else "Normal"
|
| 69 |
+
end
|
| 70 |
+
|
| 71 |
+
# 计算上下界 (ub, lb)
|
| 72 |
+
sum_y = sum(round(JuMP.value(model[:switch_on][uname, t-i+1])) for i in 1:UD if t-i+1 >= 1; init=0.0)
|
| 73 |
+
sum_z = DD > 0 ? sum(round(JuMP.value(model[:switch_off][uname, t+i])) for i in 1:DD if t+i <= T; init=0.0) : 0.0
|
| 74 |
+
|
| 75 |
+
ramp_ub = if t == 1
|
| 76 |
+
g.initial_power + RU
|
| 77 |
+
elseif sum_y > 0
|
| 78 |
+
Pmax
|
| 79 |
+
else
|
| 80 |
+
prev_p + RU
|
| 81 |
+
end
|
| 82 |
+
|
| 83 |
+
if v == 0.0 || (UD == 0 && DD == 0)
|
| 84 |
+
ub_val = ""
|
| 85 |
+
lb_val = ""
|
| 86 |
+
else
|
| 87 |
+
su_sum = sum(startup_curve[i] * round(JuMP.value(model[:switch_on][uname, t-i+1]))
|
| 88 |
+
for i in 1:UD if t-i+1 >= 1; init=0.0)
|
| 89 |
+
sd_sum = DD > 0 ? sum(shutdown_curve[i] * round(JuMP.value(model[:switch_off][uname, t+DD-i+1]))
|
| 90 |
+
for i in 1:DD if t+DD-i+1 >= 1 && t+DD-i+1 <= T; init=0.0) : 0.0
|
| 91 |
+
ub_val = min(su_sum + Pmax*(v-sum_y), sd_sum + Pmax*(v-sum_z), ramp_ub)
|
| 92 |
+
lb_val = max(Pmin*(v-sum_z-sum_y)+su_sum, Pmin*(v-sum_z-sum_y)+sd_sum)
|
| 93 |
+
end
|
| 94 |
+
|
| 95 |
+
return p, status, ub_val, lb_val
|
| 96 |
+
end
|
| 97 |
+
|
| 98 |
+
function export_combined_csv(
|
| 99 |
+
model_base, model_v1, model_v2,
|
| 100 |
+
instance_orig, instance_v1, instance_v2,
|
| 101 |
+
run_name, out_dir
|
| 102 |
+
)
|
| 103 |
+
sc_orig = instance_orig.scenarios[1]
|
| 104 |
+
sc_v1 = instance_v1.scenarios[1]
|
| 105 |
+
sc_v2 = instance_v2.scenarios[1]
|
| 106 |
+
T = instance_orig.time
|
| 107 |
+
|
| 108 |
+
unit_map_v1 = Dict(g.name => g for g in sc_v1.thermal_units)
|
| 109 |
+
unit_map_v2 = Dict(g.name => g for g in sc_v2.thermal_units)
|
| 110 |
+
|
| 111 |
+
rows = String[]
|
| 112 |
+
push!(rows,
|
| 113 |
+
"run_name,case,unit,t," *
|
| 114 |
+
"p_base,p_v1,p_v2," *
|
| 115 |
+
"ub_v1,lb_v1,ub_v2,lb_v2," *
|
| 116 |
+
"status_v1,status_v2," *
|
| 117 |
+
"pmin,pmax,startup_limit,shutdown_limit,UD,DD," *
|
| 118 |
+
"has_startup_v1,has_shutdown_v1,has_startup_v2,has_shutdown_v2," *
|
| 119 |
+
"min_uptime_orig,min_uptime_v2,has_curve"
|
| 120 |
+
)
|
| 121 |
+
|
| 122 |
+
case_name = split(run_name, "-")[1]
|
| 123 |
+
|
| 124 |
+
for g_orig in sc_orig.thermal_units
|
| 125 |
+
uname = g_orig.name
|
| 126 |
+
g_v1 = unit_map_v1[uname]
|
| 127 |
+
g_v2 = unit_map_v2[uname]
|
| 128 |
+
|
| 129 |
+
has_curve = !isempty(g_v1.startup_curve)
|
| 130 |
+
UD = length(g_v1.startup_curve)
|
| 131 |
+
DD = length(g_v1.shutdown_curve)
|
| 132 |
+
startup_limit = g_v1.startup_limit
|
| 133 |
+
shutdown_limit = g_v1.shutdown_limit
|
| 134 |
+
min_uptime_orig = g_orig.min_uptime
|
| 135 |
+
min_uptime_v2 = g_v2.min_uptime
|
| 136 |
+
|
| 137 |
+
# 判断整个周期内是否有真实启动/停机行为
|
| 138 |
+
su_v1 = has_curve && any(round(JuMP.value(model_v1[:switch_on][uname, t])) == 1.0 for t in 1:T)
|
| 139 |
+
sd_v1 = has_curve && any(round(JuMP.value(model_v1[:switch_off][uname, t])) == 1.0 for t in 1:T)
|
| 140 |
+
su_v2 = has_curve && any(round(JuMP.value(model_v2[:switch_on][uname, t])) == 1.0 for t in 1:T)
|
| 141 |
+
sd_v2 = has_curve && any(round(JuMP.value(model_v2[:switch_off][uname, t])) == 1.0 for t in 1:T)
|
| 142 |
+
|
| 143 |
+
prev_p_v1 = 0.0
|
| 144 |
+
prev_p_v2 = 0.0
|
| 145 |
+
|
| 146 |
+
for t in 1:T
|
| 147 |
+
Pmin = g_orig.min_power[t]
|
| 148 |
+
Pmax = g_orig.max_power[t]
|
| 149 |
+
|
| 150 |
+
# base model
|
| 151 |
+
pa0 = JuMP.value(model_base[:prod_above]["s1", uname, t])
|
| 152 |
+
v0 = round(JuMP.value(model_base[:is_on][uname, t]))
|
| 153 |
+
p_base = pa0 + Pmin * v0
|
| 154 |
+
|
| 155 |
+
# v1 model
|
| 156 |
+
p_v1, status_v1, ub_v1, lb_v1 = get_actual_power(model_v1, g_v1, t, T, prev_p_v1)
|
| 157 |
+
prev_p_v1 = p_v1
|
| 158 |
+
|
| 159 |
+
# v2 model
|
| 160 |
+
p_v2, status_v2, ub_v2, lb_v2 = get_actual_power(model_v2, g_v2, t, T, prev_p_v2)
|
| 161 |
+
prev_p_v2 = p_v2
|
| 162 |
+
|
| 163 |
+
push!(rows,
|
| 164 |
+
"$run_name,$case_name,$uname,$t," *
|
| 165 |
+
"$(round(p_base,digits=4)),$(round(p_v1,digits=4)),$(round(p_v2,digits=4))," *
|
| 166 |
+
"$ub_v1,$lb_v1,$ub_v2,$lb_v2," *
|
| 167 |
+
"$status_v1,$status_v2," *
|
| 168 |
+
"$(round(Pmin,digits=4)),$(round(Pmax,digits=4))," *
|
| 169 |
+
"$(round(startup_limit,digits=4)),$(round(shutdown_limit,digits=4))," *
|
| 170 |
+
"$UD,$DD,$su_v1,$sd_v1,$su_v2,$sd_v2," *
|
| 171 |
+
"$min_uptime_orig,$min_uptime_v2,$has_curve"
|
| 172 |
+
)
|
| 173 |
+
end
|
| 174 |
+
end
|
| 175 |
+
|
| 176 |
+
fname = joinpath(out_dir, "$(run_name)_combined.csv")
|
| 177 |
+
open(fname, "w") do f
|
| 178 |
+
for row in rows
|
| 179 |
+
println(f, row)
|
| 180 |
+
end
|
| 181 |
+
end
|
| 182 |
+
println(" Saved: $fname")
|
| 183 |
+
|
| 184 |
+
# ---------- 物理合理性验证统计输出 ----------
|
| 185 |
+
total_curves = 0
|
| 186 |
+
v1_su_count, v1_sd_count = 0, 0
|
| 187 |
+
v2_su_count, v2_sd_count = 0, 0
|
| 188 |
+
|
| 189 |
+
for g_v1 in sc_v1.thermal_units
|
| 190 |
+
uname = g_v1.name
|
| 191 |
+
if !isempty(g_v1.startup_curve)
|
| 192 |
+
total_curves += 1
|
| 193 |
+
if any(round(JuMP.value(model_v1[:switch_on][uname, t])) == 1.0 for t in 1:T) v1_su_count += 1 end
|
| 194 |
+
if any(round(JuMP.value(model_v1[:switch_off][uname, t])) == 1.0 for t in 1:T) v1_sd_count += 1 end
|
| 195 |
+
if any(round(JuMP.value(model_v2[:switch_on][uname, t])) == 1.0 for t in 1:T) v2_su_count += 1 end
|
| 196 |
+
if any(round(JuMP.value(model_v2[:switch_off][uname, t])) == 1.0 for t in 1:T) v2_sd_count += 1 end
|
| 197 |
+
end
|
| 198 |
+
end
|
| 199 |
+
|
| 200 |
+
println("\n [物理合理性验证] 启停轨迹激活统计:")
|
| 201 |
+
println(" 配置了曲线的机组总数: $total_curves")
|
| 202 |
+
println(" v1 发生实际启动: $(v1_su_count)/$total_curves | 发生实际停机: $(v1_sd_count)/$total_curves")
|
| 203 |
+
println(" v2 发生实际启动: $(v2_su_count)/$total_curves | 发生实际停机: $(v2_sd_count)/$total_curves")
|
| 204 |
+
if total_curves > 0 && v1_su_count == 0 && v2_su_count == 0
|
| 205 |
+
println(" 警告: 即使添加了曲线，也没有任何相关机组发生真实启动/停机。")
|
| 206 |
+
end
|
| 207 |
+
end
|
| 208 |
+
|
| 209 |
+
function export_summary_csv(results, run_name, case_name, out_dir)
|
| 210 |
+
fname = joinpath(out_dir, "$(run_name)_summary.csv")
|
| 211 |
+
open(fname, "w") do f
|
| 212 |
+
println(f, "case,model,objective,lower_bound,mip_gap_actual,solve_time,diff_pct")
|
| 213 |
+
for (tag, obj, lb, gap, stime, diff) in results
|
| 214 |
+
println(f, "$case_name,$tag,$(round(obj,digits=4)),$(round(lb,digits=4)),$(round(gap,digits=6)),$(round(stime,digits=4)),$(round(diff,digits=6))")
|
| 215 |
+
end
|
| 216 |
+
end
|
| 217 |
+
println(" Saved: $fname")
|
| 218 |
+
end
|
| 219 |
+
|
| 220 |
+
println("="^60)
|
| 221 |
+
|
| 222 |
+
# 定义主输出文件夹
|
| 223 |
+
master_dir = "test"
|
| 224 |
+
mkpath(master_dir)
|
| 225 |
+
println(">> 开始测试")
|
| 226 |
+
|
| 227 |
+
for (json_path, case_name) in CASES
|
| 228 |
+
# 提取日期，例如：2017-01-01（现在是从 .json 文件中提取）
|
| 229 |
+
date_str = split(basename(json_path), ".")[1]
|
| 230 |
+
|
| 231 |
+
# 拼接统一前缀名称：case2383wp-2017-01-01
|
| 232 |
+
run_name = "$(case_name)-$(date_str)"
|
| 233 |
+
|
| 234 |
+
# 输出存放在 master_dir 下
|
| 235 |
+
out_dir = joinpath(master_dir, run_name)
|
| 236 |
+
mkpath(out_dir)
|
| 237 |
+
|
| 238 |
+
println("\n[Run: $run_name]")
|
| 239 |
+
|
| 240 |
+
# 读取原始instance → 求解base model
|
| 241 |
+
instance_orig = UnitCommitment.read(json_path)
|
| 242 |
+
println(" [1/4] 求解 base model...")
|
| 243 |
+
model_base = build_and_solve(instance_orig, false)
|
| 244 |
+
|
| 245 |
+
obj_base = JuMP.objective_value(model_base)
|
| 246 |
+
lb_base = JuMP.objective_bound(model_base)
|
| 247 |
+
time_base = JuMP.solve_time(model_base)
|
| 248 |
+
gap_base = abs(obj_base - lb_base) / max(1e-10, abs(obj_base))
|
| 249 |
+
println(" base obj: $(round(obj_base, digits=2)) | gap: $(round(gap_base*100, digits=4))% | solver_time: $(round(time_base, digits=2))s")
|
| 250 |
+
|
| 251 |
+
println("\n[2/4] Part 1 - 添加 startup/shutdown curve...")
|
| 252 |
+
json_v1_path = UnitCommitment.add_trajectory_curves_to_source_data(
|
| 253 |
+
json_path;
|
| 254 |
+
top_pct = 0.10,
|
| 255 |
+
output_path = joinpath(out_dir, "$(run_name)-part1.json"),
|
| 256 |
+
)
|
| 257 |
+
instance_v1 = UnitCommitment.read(json_v1_path)
|
| 258 |
+
println(" 求解 traj_v1 model...")
|
| 259 |
+
model_v1 = build_and_solve(instance_v1, true)
|
| 260 |
+
|
| 261 |
+
obj_v1 = JuMP.objective_value(model_v1)
|
| 262 |
+
lb_v1 = JuMP.objective_bound(model_v1)
|
| 263 |
+
time_v1 = JuMP.solve_time(model_v1)
|
| 264 |
+
gap_v1 = abs(obj_v1 - lb_v1) / max(1e-10, abs(obj_v1))
|
| 265 |
+
diff_v1 = (obj_v1 - obj_base) / obj_base * 100
|
| 266 |
+
println(" v1 obj: $(round(obj_v1, digits=2)) diff=$(round(diff_v1, digits=4))% | gap: $(round(gap_v1*100, digits=4))% | solver_time: $(round(time_v1, digits=2))s")
|
| 267 |
+
|
| 268 |
+
println("\n [3/4] Part 2 - 修改 Minimum uptime...")
|
| 269 |
+
json_v2_path = UnitCommitment.modify_min_uptime_in_source_data(
|
| 270 |
+
json_v1_path;
|
| 271 |
+
output_path = joinpath(out_dir, "$(run_name)-part2.json"),
|
| 272 |
+
)
|
| 273 |
+
instance_v2 = UnitCommitment.read(json_v2_path)
|
| 274 |
+
println(" 求解 traj_v2 model...")
|
| 275 |
+
model_v2 = build_and_solve(instance_v2, true)
|
| 276 |
+
|
| 277 |
+
obj_v2 = JuMP.objective_value(model_v2)
|
| 278 |
+
lb_v2 = JuMP.objective_bound(model_v2)
|
| 279 |
+
time_v2 = JuMP.solve_time(model_v2)
|
| 280 |
+
gap_v2 = abs(obj_v2 - lb_v2) / max(1e-10, abs(obj_v2))
|
| 281 |
+
diff_v2 = (obj_v2 - obj_base) / obj_base * 100
|
| 282 |
+
println(" v2 obj: $(round(obj_v2, digits=2)) diff=$(round(diff_v2, digits=4))% | gap: $(round(gap_v2*100, digits=4))% | solver_time: $(round(time_v2, digits=2))s")
|
| 283 |
+
|
| 284 |
+
println("\n ── 目标值汇总 " * "─"^30)
|
| 285 |
+
println(" base : obj=$(round(obj_base, digits=2)), gap=$(round(gap_base*100, digits=4))%, solver_time=$(round(time_base, digits=2))s")
|
| 286 |
+
println(" v1 : obj=$(round(obj_v1, digits=2)), diff=$(round(diff_v1, digits=4))%, gap=$(round(gap_v1*100, digits=4))%, solver_time=$(round(time_v1, digits=2))s")
|
| 287 |
+
println(" v2 : obj=$(round(obj_v2, digits=2)), diff=$(round(diff_v2, digits=4))%, gap=$(round(gap_v2*100, digits=4))%, solver_time=$(round(time_v2, digits=2))s")
|
| 288 |
+
|
| 289 |
+
println("\n[4/4] 导出 CSV...")
|
| 290 |
+
export_combined_csv(
|
| 291 |
+
model_base, model_v1, model_v2,
|
| 292 |
+
instance_orig, instance_v1, instance_v2,
|
| 293 |
+
run_name, out_dir
|
| 294 |
+
)
|
| 295 |
+
|
| 296 |
+
results_to_export =[
|
| 297 |
+
("base", obj_base, lb_base, gap_base, time_base, 0.0),
|
| 298 |
+
("v1", obj_v1, lb_v1, gap_v1, time_v1, diff_v1),
|
| 299 |
+
("v2", obj_v2, lb_v2, gap_v2, time_v2, diff_v2)
|
| 300 |
+
]
|
| 301 |
+
export_summary_csv(results_to_export, run_name, case_name, out_dir)
|
| 302 |
+
end
|
| 303 |
+
|
| 304 |
+
println("\n" * "="^60)
|
| 305 |
+
println("测试完成")
|
UnitCommitment_Trajectory_Test/test_main.jl
CHANGED
|
@@ -1,307 +1 @@
|
|
| 1 |
-
|
| 2 |
-
using HiGHS
|
| 3 |
-
import JuMP
|
| 4 |
-
include("pmax-preprocessing.jl")
|
| 5 |
-
|
| 6 |
-
CASES =[
|
| 7 |
-
("testdata/case2383wp/2017-01-01.json.gz", "case2383wp"),
|
| 8 |
-
# ("testdata/case2736sp/2017-07-21.json.gz", "case2736sp")
|
| 9 |
-
]
|
| 10 |
-
|
| 11 |
-
function build_and_solve(instance, use_traj)
|
| 12 |
-
formulation = use_traj ?
|
| 13 |
-
UnitCommitment.Formulation(
|
| 14 |
-
power_trajectories = UnitCommitment.xxx2005.PowerTrajectories()
|
| 15 |
-
) :
|
| 16 |
-
UnitCommitment.Formulation()
|
| 17 |
-
model = UnitCommitment.build_model(
|
| 18 |
-
instance = instance,
|
| 19 |
-
optimizer = HiGHS.Optimizer,
|
| 20 |
-
formulation = formulation,
|
| 21 |
-
)
|
| 22 |
-
JuMP.set_silent(model)
|
| 23 |
-
JuMP.optimize!(model)
|
| 24 |
-
return model
|
| 25 |
-
end
|
| 26 |
-
|
| 27 |
-
function get_actual_power(model, g, t, T, prev_p)
|
| 28 |
-
uname = g.name
|
| 29 |
-
UD = length(g.startup_curve)
|
| 30 |
-
DD = length(g.shutdown_curve)
|
| 31 |
-
startup_curve = g.startup_curve
|
| 32 |
-
shutdown_curve = g.shutdown_curve
|
| 33 |
-
Pmin = g.min_power[t]
|
| 34 |
-
Pmax = g.max_power[t]
|
| 35 |
-
RU = g.ramp_up_limit
|
| 36 |
-
|
| 37 |
-
v = round(JuMP.value(model[:is_on][uname, t]))
|
| 38 |
-
y = round(JuMP.value(model[:switch_on][uname, t]))
|
| 39 |
-
pa = JuMP.value(model[:prod_above]["s1", uname, t])
|
| 40 |
-
|
| 41 |
-
in_su = UD > 0 && any(
|
| 42 |
-
round(JuMP.value(model[:switch_on][uname, t-i+1])) == 1.0
|
| 43 |
-
for i in 1:UD if t-i+1 >= 1)
|
| 44 |
-
in_sd = DD > 0 && any(
|
| 45 |
-
round(JuMP.value(model[:switch_off][uname, t+i])) == 1.0
|
| 46 |
-
for i in 1:DD if t+i <= T)
|
| 47 |
-
|
| 48 |
-
p = 0.0
|
| 49 |
-
if in_su
|
| 50 |
-
for i in 1:UD
|
| 51 |
-
if t-i+1 >= 1 && round(JuMP.value(model[:switch_on][uname, t-i+1])) == 1.0
|
| 52 |
-
p = startup_curve[i]; break
|
| 53 |
-
end
|
| 54 |
-
end
|
| 55 |
-
elseif in_sd
|
| 56 |
-
for i in 1:DD
|
| 57 |
-
if t+i <= T && round(JuMP.value(model[:switch_off][uname, t+i])) == 1.0
|
| 58 |
-
p = shutdown_curve[DD-i+1]; break
|
| 59 |
-
end
|
| 60 |
-
end
|
| 61 |
-
elseif v > 0.5
|
| 62 |
-
p = pa + Pmin
|
| 63 |
-
end
|
| 64 |
-
|
| 65 |
-
status = if v == 0.0; "Offline"
|
| 66 |
-
elseif y == 1.0; "Startup_t1"
|
| 67 |
-
elseif in_su; "Startup_traj"
|
| 68 |
-
elseif in_sd; "Shutdown_traj"
|
| 69 |
-
else "Normal"
|
| 70 |
-
end
|
| 71 |
-
|
| 72 |
-
# 计算上下界 (ub, lb)
|
| 73 |
-
sum_y = sum(round(JuMP.value(model[:switch_on][uname, t-i+1])) for i in 1:UD if t-i+1 >= 1; init=0.0)
|
| 74 |
-
sum_z = DD > 0 ? sum(round(JuMP.value(model[:switch_off][uname, t+i])) for i in 1:DD if t+i <= T; init=0.0) : 0.0
|
| 75 |
-
|
| 76 |
-
ramp_ub = if t == 1
|
| 77 |
-
g.initial_power + RU
|
| 78 |
-
elseif sum_y > 0
|
| 79 |
-
Pmax
|
| 80 |
-
else
|
| 81 |
-
prev_p + RU
|
| 82 |
-
end
|
| 83 |
-
|
| 84 |
-
if v == 0.0 || (UD == 0 && DD == 0)
|
| 85 |
-
ub_val = ""
|
| 86 |
-
lb_val = ""
|
| 87 |
-
else
|
| 88 |
-
su_sum = sum(startup_curve[i] * round(JuMP.value(model[:switch_on][uname, t-i+1]))
|
| 89 |
-
for i in 1:UD if t-i+1 >= 1; init=0.0)
|
| 90 |
-
sd_sum = DD > 0 ? sum(shutdown_curve[i] * round(JuMP.value(model[:switch_off][uname, t+DD-i+1]))
|
| 91 |
-
for i in 1:DD if t+DD-i+1 >= 1 && t+DD-i+1 <= T; init=0.0) : 0.0
|
| 92 |
-
ub_val = min(su_sum + Pmax*(v-sum_y), sd_sum + Pmax*(v-sum_z), ramp_ub)
|
| 93 |
-
lb_val = max(Pmin*(v-sum_z-sum_y)+su_sum, Pmin*(v-sum_z-sum_y)+sd_sum)
|
| 94 |
-
end
|
| 95 |
-
|
| 96 |
-
return p, status, ub_val, lb_val
|
| 97 |
-
end
|
| 98 |
-
|
| 99 |
-
function export_combined_csv(
|
| 100 |
-
model_base, model_v1, model_v2,
|
| 101 |
-
instance_orig, instance_v1, instance_v2,
|
| 102 |
-
run_name, out_dir
|
| 103 |
-
)
|
| 104 |
-
sc_orig = instance_orig.scenarios[1]
|
| 105 |
-
sc_v1 = instance_v1.scenarios[1]
|
| 106 |
-
sc_v2 = instance_v2.scenarios[1]
|
| 107 |
-
T = instance_orig.time
|
| 108 |
-
|
| 109 |
-
unit_map_v1 = Dict(g.name => g for g in sc_v1.thermal_units)
|
| 110 |
-
unit_map_v2 = Dict(g.name => g for g in sc_v2.thermal_units)
|
| 111 |
-
|
| 112 |
-
rows = String[]
|
| 113 |
-
push!(rows,
|
| 114 |
-
"run_name,case,unit,t," *
|
| 115 |
-
"p_base,p_v1,p_v2," *
|
| 116 |
-
"ub_v1,lb_v1,ub_v2,lb_v2," *
|
| 117 |
-
"status_v1,status_v2," *
|
| 118 |
-
"pmin,pmax,startup_limit,shutdown_limit,UD,DD," *
|
| 119 |
-
"has_startup_v1,has_shutdown_v1,has_startup_v2,has_shutdown_v2," *
|
| 120 |
-
"min_uptime_orig,min_uptime_v2,has_curve"
|
| 121 |
-
)
|
| 122 |
-
|
| 123 |
-
case_name = split(run_name, "-")[1]
|
| 124 |
-
|
| 125 |
-
for g_orig in sc_orig.thermal_units
|
| 126 |
-
uname = g_orig.name
|
| 127 |
-
g_v1 = unit_map_v1[uname]
|
| 128 |
-
g_v2 = unit_map_v2[uname]
|
| 129 |
-
|
| 130 |
-
has_curve = !isempty(g_v1.startup_curve)
|
| 131 |
-
UD = length(g_v1.startup_curve)
|
| 132 |
-
DD = length(g_v1.shutdown_curve)
|
| 133 |
-
startup_limit = g_v1.startup_limit
|
| 134 |
-
shutdown_limit = g_v1.shutdown_limit
|
| 135 |
-
min_uptime_orig = g_orig.min_uptime
|
| 136 |
-
min_uptime_v2 = g_v2.min_uptime
|
| 137 |
-
|
| 138 |
-
# 判断整个周期内是否有真实启动/停机行为
|
| 139 |
-
su_v1 = has_curve && any(round(JuMP.value(model_v1[:switch_on][uname, t])) == 1.0 for t in 1:T)
|
| 140 |
-
sd_v1 = has_curve && any(round(JuMP.value(model_v1[:switch_off][uname, t])) == 1.0 for t in 1:T)
|
| 141 |
-
su_v2 = has_curve && any(round(JuMP.value(model_v2[:switch_on][uname, t])) == 1.0 for t in 1:T)
|
| 142 |
-
sd_v2 = has_curve && any(round(JuMP.value(model_v2[:switch_off][uname, t])) == 1.0 for t in 1:T)
|
| 143 |
-
|
| 144 |
-
prev_p_v1 = 0.0
|
| 145 |
-
prev_p_v2 = 0.0
|
| 146 |
-
|
| 147 |
-
for t in 1:T
|
| 148 |
-
Pmin = g_orig.min_power[t]
|
| 149 |
-
Pmax = g_orig.max_power[t]
|
| 150 |
-
|
| 151 |
-
# base model
|
| 152 |
-
pa0 = JuMP.value(model_base[:prod_above]["s1", uname, t])
|
| 153 |
-
v0 = round(JuMP.value(model_base[:is_on][uname, t]))
|
| 154 |
-
p_base = pa0 + Pmin * v0
|
| 155 |
-
|
| 156 |
-
# v1 model
|
| 157 |
-
p_v1, status_v1, ub_v1, lb_v1 = get_actual_power(model_v1, g_v1, t, T, prev_p_v1)
|
| 158 |
-
prev_p_v1 = p_v1
|
| 159 |
-
|
| 160 |
-
# v2 model
|
| 161 |
-
p_v2, status_v2, ub_v2, lb_v2 = get_actual_power(model_v2, g_v2, t, T, prev_p_v2)
|
| 162 |
-
prev_p_v2 = p_v2
|
| 163 |
-
|
| 164 |
-
push!(rows,
|
| 165 |
-
"$run_name,$case_name,$uname,$t," *
|
| 166 |
-
"$(round(p_base,digits=4)),$(round(p_v1,digits=4)),$(round(p_v2,digits=4))," *
|
| 167 |
-
"$ub_v1,$lb_v1,$ub_v2,$lb_v2," *
|
| 168 |
-
"$status_v1,$status_v2," *
|
| 169 |
-
"$(round(Pmin,digits=4)),$(round(Pmax,digits=4))," *
|
| 170 |
-
"$(round(startup_limit,digits=4)),$(round(shutdown_limit,digits=4))," *
|
| 171 |
-
"$UD,$DD,$su_v1,$sd_v1,$su_v2,$sd_v2," *
|
| 172 |
-
"$min_uptime_orig,$min_uptime_v2,$has_curve"
|
| 173 |
-
)
|
| 174 |
-
end
|
| 175 |
-
end
|
| 176 |
-
|
| 177 |
-
fname = joinpath(out_dir, "$(run_name)_combined.csv")
|
| 178 |
-
open(fname, "w") do f
|
| 179 |
-
for row in rows
|
| 180 |
-
println(f, row)
|
| 181 |
-
end
|
| 182 |
-
end
|
| 183 |
-
println(" Saved: $fname")
|
| 184 |
-
|
| 185 |
-
# ---------- 物理合理性验证统计输出 ----------
|
| 186 |
-
total_curves = 0
|
| 187 |
-
v1_su_count, v1_sd_count = 0, 0
|
| 188 |
-
v2_su_count, v2_sd_count = 0, 0
|
| 189 |
-
|
| 190 |
-
for g_v1 in sc_v1.thermal_units
|
| 191 |
-
uname = g_v1.name
|
| 192 |
-
if !isempty(g_v1.startup_curve)
|
| 193 |
-
total_curves += 1
|
| 194 |
-
if any(round(JuMP.value(model_v1[:switch_on][uname, t])) == 1.0 for t in 1:T) v1_su_count += 1 end
|
| 195 |
-
if any(round(JuMP.value(model_v1[:switch_off][uname, t])) == 1.0 for t in 1:T) v1_sd_count += 1 end
|
| 196 |
-
if any(round(JuMP.value(model_v2[:switch_on][uname, t])) == 1.0 for t in 1:T) v2_su_count += 1 end
|
| 197 |
-
if any(round(JuMP.value(model_v2[:switch_off][uname, t])) == 1.0 for t in 1:T) v2_sd_count += 1 end
|
| 198 |
-
end
|
| 199 |
-
end
|
| 200 |
-
|
| 201 |
-
println("\n [物理合理性验证] 启停轨迹激活统计:")
|
| 202 |
-
println(" 配置了曲线的机组总数: $total_curves")
|
| 203 |
-
println(" v1 发生实际启动: $(v1_su_count)/$total_curves | 发生实际停机: $(v1_sd_count)/$total_curves")
|
| 204 |
-
println(" v2 发生实际启动: $(v2_su_count)/$total_curves | 发生实际停机: $(v2_sd_count)/$total_curves")
|
| 205 |
-
if total_curves > 0 && v1_su_count == 0 && v2_su_count == 0
|
| 206 |
-
println(" 警告: 即使添加了曲线，也没有任何相关机组发生真实启动/停机。")
|
| 207 |
-
end
|
| 208 |
-
end
|
| 209 |
-
|
| 210 |
-
function export_summary_csv(results, run_name, case_name, out_dir)
|
| 211 |
-
fname = joinpath(out_dir, "$(run_name)_summary.csv")
|
| 212 |
-
open(fname, "w") do f
|
| 213 |
-
println(f, "case,model,objective,lower_bound,mip_gap_actual,solve_time,diff_pct")
|
| 214 |
-
for (tag, obj, lb, gap, stime, diff) in results
|
| 215 |
-
println(f, "$case_name,$tag,$(round(obj,digits=4)),$(round(lb,digits=4)),$(round(gap,digits=6)),$(round(stime,digits=4)),$(round(diff,digits=6))")
|
| 216 |
-
end
|
| 217 |
-
end
|
| 218 |
-
println(" Saved: $fname")
|
| 219 |
-
end
|
| 220 |
-
|
| 221 |
-
println("="^60)
|
| 222 |
-
|
| 223 |
-
# 定义主输出文件夹
|
| 224 |
-
master_dir = "test"
|
| 225 |
-
mkpath(master_dir)
|
| 226 |
-
println(">> 开始测试")
|
| 227 |
-
|
| 228 |
-
for (json_path, case_name) in CASES
|
| 229 |
-
# 提取日期，例如：2017-01-01（现在是从 .json 文件中提取）
|
| 230 |
-
date_str = split(basename(json_path), ".")[1]
|
| 231 |
-
|
| 232 |
-
# 拼接统一前缀名称：case2383wp-2017-01-01
|
| 233 |
-
run_name = "$(case_name)-$(date_str)"
|
| 234 |
-
|
| 235 |
-
# 输出存放在 master_dir 下
|
| 236 |
-
out_dir = joinpath(master_dir, run_name)
|
| 237 |
-
mkpath(out_dir)
|
| 238 |
-
|
| 239 |
-
println("\n[Run: $run_name]")
|
| 240 |
-
|
| 241 |
-
# 读取原始instance → 求解base model
|
| 242 |
-
instance_orig = UnitCommitment.read(json_path)
|
| 243 |
-
println(" [1/4] 求解 base model...")
|
| 244 |
-
model_base = build_and_solve(instance_orig, false)
|
| 245 |
-
|
| 246 |
-
obj_base = JuMP.objective_value(model_base)
|
| 247 |
-
lb_base = JuMP.objective_bound(model_base)
|
| 248 |
-
time_base = JuMP.solve_time(model_base)
|
| 249 |
-
gap_base = abs(obj_base - lb_base) / max(1e-10, abs(obj_base))
|
| 250 |
-
println(" base obj: $(round(obj_base, digits=2)) | gap: $(round(gap_base*100, digits=4))% | solver_time: $(round(time_base, digits=2))s")
|
| 251 |
-
|
| 252 |
-
println("\n[2/4] Part 1 - 添加 startup/shutdown curve...")
|
| 253 |
-
json_v1_path = add_trajectory_curves(
|
| 254 |
-
json_path;
|
| 255 |
-
top_pct = 0.10,
|
| 256 |
-
output_path = joinpath(out_dir, "$(run_name)-part1.json"),
|
| 257 |
-
)
|
| 258 |
-
instance_v1 = UnitCommitment.read(json_v1_path)
|
| 259 |
-
println(" 求解 traj_v1 model...")
|
| 260 |
-
model_v1 = build_and_solve(instance_v1, true)
|
| 261 |
-
|
| 262 |
-
obj_v1 = JuMP.objective_value(model_v1)
|
| 263 |
-
lb_v1 = JuMP.objective_bound(model_v1)
|
| 264 |
-
time_v1 = JuMP.solve_time(model_v1)
|
| 265 |
-
gap_v1 = abs(obj_v1 - lb_v1) / max(1e-10, abs(obj_v1))
|
| 266 |
-
diff_v1 = (obj_v1 - obj_base) / obj_base * 100
|
| 267 |
-
println(" v1 obj: $(round(obj_v1, digits=2)) diff=$(round(diff_v1, digits=4))% | gap: $(round(gap_v1*100, digits=4))% | solver_time: $(round(time_v1, digits=2))s")
|
| 268 |
-
|
| 269 |
-
println("\n [3/4] Part 2 - 修改 Minimum uptime...")
|
| 270 |
-
json_v2_path = modify_min_uptime(
|
| 271 |
-
json_v1_path;
|
| 272 |
-
top_pct = 0.10,
|
| 273 |
-
output_path = joinpath(out_dir, "$(run_name)-part2.json"),
|
| 274 |
-
)
|
| 275 |
-
instance_v2 = UnitCommitment.read(json_v2_path)
|
| 276 |
-
println(" 求解 traj_v2 model...")
|
| 277 |
-
model_v2 = build_and_solve(instance_v2, true)
|
| 278 |
-
|
| 279 |
-
obj_v2 = JuMP.objective_value(model_v2)
|
| 280 |
-
lb_v2 = JuMP.objective_bound(model_v2)
|
| 281 |
-
time_v2 = JuMP.solve_time(model_v2)
|
| 282 |
-
gap_v2 = abs(obj_v2 - lb_v2) / max(1e-10, abs(obj_v2))
|
| 283 |
-
diff_v2 = (obj_v2 - obj_base) / obj_base * 100
|
| 284 |
-
println(" v2 obj: $(round(obj_v2, digits=2)) diff=$(round(diff_v2, digits=4))% | gap: $(round(gap_v2*100, digits=4))% | solver_time: $(round(time_v2, digits=2))s")
|
| 285 |
-
|
| 286 |
-
println("\n ── 目标值汇总 " * "─"^30)
|
| 287 |
-
println(" base : obj=$(round(obj_base, digits=2)), gap=$(round(gap_base*100, digits=4))%, solver_time=$(round(time_base, digits=2))s")
|
| 288 |
-
println(" v1 : obj=$(round(obj_v1, digits=2)), diff=$(round(diff_v1, digits=4))%, gap=$(round(gap_v1*100, digits=4))%, solver_time=$(round(time_v1, digits=2))s")
|
| 289 |
-
println(" v2 : obj=$(round(obj_v2, digits=2)), diff=$(round(diff_v2, digits=4))%, gap=$(round(gap_v2*100, digits=4))%, solver_time=$(round(time_v2, digits=2))s")
|
| 290 |
-
|
| 291 |
-
println("\n[4/4] 导出 CSV...")
|
| 292 |
-
export_combined_csv(
|
| 293 |
-
model_base, model_v1, model_v2,
|
| 294 |
-
instance_orig, instance_v1, instance_v2,
|
| 295 |
-
run_name, out_dir
|
| 296 |
-
)
|
| 297 |
-
|
| 298 |
-
results_to_export =[
|
| 299 |
-
("base", obj_base, lb_base, gap_base, time_base, 0.0),
|
| 300 |
-
("v1", obj_v1, lb_v1, gap_v1, time_v1, diff_v1),
|
| 301 |
-
("v2", obj_v2, lb_v2, gap_v2, time_v2, diff_v2)
|
| 302 |
-
]
|
| 303 |
-
export_summary_csv(results_to_export, run_name, case_name, out_dir)
|
| 304 |
-
end
|
| 305 |
-
|
| 306 |
-
println("\n" * "="^60)
|
| 307 |
-
println("测试完成")
|
|
|
|
| 1 |
+
include(joinpath(@__DIR__, "test", "test_instance_modification.jl"))
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