DOI: 10.5061/dryad.4tmpg4fn1
title: Data for: Solar bike path feasibility study in California

description: This project explores the feasibility of integrating solar-powered
 infrastructure into bike pathways as a sustainable energy and
 transportation solution for California. Using advanced tools like ArcGIS
 (for analysis), PVWatts, SAM, and JEDI, this study evaluates the economic,
 environmental, and technical implications through a conceptual case study
 based in Riverside. Insights drawn from global case studies and
 stakeholder feedback highlight challenges such as financial constraints,
 regulatory complexities, and technical design considerations, while also
 identifying opportunities for renewable energy generation, greenhouse gas
 emission reductions, and enhanced urban mobility. The conceptual case
 study serves as a framework for assessing potential benefits and informing
 actionable strategies. Recommendations address barriers and align
 implementation with California’s climate action and sustainability goals,
 offering a roadmap for integrating renewable energy with active
 transportation systems.
description: The data collection and processing methods for this project
 utilized a combination of publicly available tools and resources to ensure
 accuracy and usability. Key geospatial, energy modeling, and economic
 analysis data were gathered using reliable tools such as ArcGIS, SAM,
 JEDI, and PVWatts, with outputs systematically processed into accessible
 formats. This approach enabled comprehensive analysis of bike path
 integration, energy performance, and economic impacts.
 <strong>Data
 Collection</strong>: 
 <strong>BikePaths_Riverside.qgz</strong>: Geospatial data
 detailing bike paths in Riverside was gathered from publicly available
 sources and initially analyzed using ArcGIS Pro. To ensure open access and
 reusability, the data has been converted to a .qgz project file compatible
 with QGIS (version 3.42), a free and open-source GIS platform.
 <strong>SAM_Input_Variable_Values.csv</strong>:
 Input parameters were collected based on standard system specifications,
 financial assumptions, and default or adjusted inputs available in the
 System Advisor Model (SAM), a widely used tool for energy performance and
 financial modeling. 
 <strong>SAM_Results_Summary.csv</strong>: The simulation
 outputs from SAM were generated after running the model with the collected
 input variables, providing details on energy production, financial
 metrics, and economic performance. 
 <strong>JEDI_Results_Summary.csv</strong>: Job and economic
 impact data were derived using the Jobs and Economic Development Impact
 (JEDI) model, which relies on predefined multipliers and region-specific
 data. 
 <strong>PVWatts_Monthly.csv</strong>: Energy production and
 irradiance data were generated using NREL’s PVWatts Calculator for a
 fixed-tilt, premium-module PV system located in Riverside, California (ZIP
 code 92507), using typical meteorological year (TMY) data and standard
 system configuration inputs. 
 <strong>Data Processing</strong>: 
 <strong>BikePaths_Riverside.qgz</strong>: The
 original geospatial data was preprocessed and analyzed using ArcGIS Pro to
 support spatial measurements and site selection. For the purpose of public
 data sharing, the file has been converted and exported to QGIS format .qgz
 to ensure it is viewable with open-source software. 
 <strong>SAM_Input_Variable_Values.csv and
 SAM_Results_Summary.csv</strong>: Data inputs and outputs were
 processed and summarized in spreadsheets for clarity and usability,
 focusing on key energy and financial metrics. 
 <strong>JEDI_Results_Summary.csv</strong>: Results from the
 JEDI model were organized and documented in a spreadsheet to provide a
 clear summary of job creation and economic impacts. 
 <strong>PVWatts_Monthly.csv</strong>: Simulation results were
 exported directly from PVWatts into a structured CSV file, replacing the
 original PDF summary and organizing monthly values for AC output, DC
 production, and plane-of-array irradiance for use in model validation and
 greenhouse gas reduction analysis.
description: # Data for: Solar bike path feasibility study in California
 [https://doi.org/10.5061/dryad.4tmpg4fn1](https://doi.org/10.5061/dryad.4tmpg4fn1) ## Description of the data and file structure The data was collected to evaluate the feasibility, technical requirements, and potential impacts of integrating solar-powered infrastructure into bike pathways. The study utilized geospatial data from ArcGIS for spatial analysis and site evaluation, combined with energy modeling tools such as PVWatts and SAM to estimate energy production, greenhouse gas reductions, and financial metrics. The JEDI model was employed to assess economic and job creation impacts. These efforts were guided by a conceptual case study in Riverside, California, to simulate real-world scenarios and inform actionable strategies for renewable energy integration. Feedback from stakeholders further shaped the analysis, addressing technical, economic, and regulatory challenges while aligning with California's sustainability goals. ### Files and variables #### **File: BikePaths_Riverside.qgz** **Description:** A QGIS project file (.qgz) derived from the original ArcGIS analysis. It contains geospatial data on bike paths in Riverside used for spatial evaluation and site selection in the solar bike path feasibility study. The (.qgz) format ensures accessibility through free and open-source GIS software, specifically QGIS version 3.42 or later. #### **File: JEDI_Results_Summary.csv** **Description:** This workbook is the unedited “Summary Results” export produced by NREL’s Jobs and Economic Development Impact (JEDI) photovoltaic model for a 1 MW DC solar array installed over a Riverside, CA bike path (construction year 2030). It records how the project ripples through the local economy during construction (one-time) and during each operating year (recurring). All currency values are expressed in constant-2030 U.S. dollars (noted as “$000 2030” where JEDI reports thousands); employment is shown as full-time-equivalent jobs (1 FTE = 2,080 work-hours). ##### Variables **Project Data Summary** Project Location, Year of Construction or Installation, Average System Size – DC Nameplate Capacity (KW), Number of Systems Installed, Total Project Size – DC Nameplate Capacity (KW), System Application, Solar Cell/Module Material, System Tracking, Base Installed System Cost ($/KWDC), Annual Direct Operations and Maintenance Cost ($/kW), Money Value – Current or Constant (Dollar Year), Project Construction or Installation Cost, Local Spending, Total Annual Operational Expenses, Direct Operating and Maintenance Costs, Other Annual Costs, Debt Payments, Property Taxes. Interpretation keys – System size and capacities are in kilowatts (kW DC). Cost values are given either per kilowatt or as total dollar amounts. “Local Spending” refers to the portion of costs expected to stay within California’s economy. This section defines the model assumptions that shape downstream impact calculations. **Local Economic Impacts – Construction & Installation Period** Row variable Impact Category lists channels such as Project Development and On-Site Labor, Module and Supply Chain, Induced Impacts, plus subtotal/total rows. * **Jobs (FTE):** Full-time-equivalent positions supported during the build year. * **Earnings ($000 2030):** Labor income associated with those jobs. * **Output ($000 2030):** Overall business revenues generated by that activity. * **Value Added ($000 2030):** Contribution to gross regional product (similar to GDP), combining labor income, business income, and taxes. **Local Economic Impacts – Operating Years** This section reports the annual, recurring impacts during the system’s operation. Variable definitions are the same as above and describe impacts that would continue each year the system is in use. **Detailed PV Project Costs and Financial Parameters** This section contains itemized capital cost breakdowns and financial inputs used in the model. * **Cost:** Estimated amount spent on each component or service. * **Locally (%):** Estimated percentage of each item expected to be sourced in-state. * **Locally (Y or N):** Whether the entire cost is treated as local (Y) or partially local (N). * **Wage per hour:** Base wage for each labor category involved in the project. * **Employer Payroll Overhead (%):** Additional cost of employment beyond wages (e.g., insurance, payroll taxes). * **Percentage financed, Years financed, Interest rate:** Inputs describing how the project is financed. * **Property tax and sales tax fields:** Define annual tax burdens or exemptions. **Missing Values:** Blank cells appear where the JEDI model does not generate a result for that category or combination (e.g., if a category has no output or is exempt from property taxes). Blank values do not indicate error; they signify “not applicable.” A zero (0) indicates that the model calculated the value but determined it to be zero. #### **File: SAM_Input_Variables_Values.csv** **Description:**\ This file contains the full set of input parameters actually defined by the study team for the SAM simulation of the Riverside solar bike path project. It reflects assumptions for a 1 MW DC fixed-tilt PV system modeled using the "TPO Host-Developer" financial structure with a $0.15/kWh PPA. The variables below are the only scenario-specific inputs actively set by the user; unused or default rows included by SAM’s export were omitted for clarity. ##### Variables * **analysis_period:** Number of years the system’s performance and financials are modeled. * **debt_option:** Specifies the method for sizing debt: 0 uses a fixed debt percent; 1 uses the Debt Service Coverage Ratio (DSCR) approach based on project cash flows. * **debt_percent:** Portion of total project cost financed through debt (only used if debt_option=0). * **federal_tax_rate:** Applicable federal income tax rate for project revenues. * **inv_cec_name:** Selected inverter model from SAM’s inverter library. * **inverter_costunits:** Units used to define inverter cost (e.g., $/Wac). * **inverter_count:** Number of inverter units installed in the system. * **mppt_hi_inverter:** Maximum input voltage at which the inverter’s Maximum Power Point Tracker (MPPT) operates, defining the upper bound of optimal tracking. * **mppt_low_inverter:** Minimum MPPT voltage, defining the lower bound of the inverter’s optimal power tracking range. * **om_capacity:** Annual fixed Operations & Maintenance (O&M) cost expressed per installed kilowatt (e.g., $/kW-year). * **ppa_price_input:** Initial Power Purchase Agreement (PPA) price in $/kWh for Year 1 of operation. * **real_discount_rate:** Real (inflation-adjusted) discount rate used in financial modeling and Net Present Value (NPV) calculations. * **sales_tax_rate:** Sales tax applied to capital expenditures or other taxable project costs. * **solar_resource:** Selected solar resource file representing local irradiance and climate data for the simulation site. * **state_tax_rate:** Applicable state income tax rate for project revenues. * **term_tenor:** Length of the debt term in years. * **vdcmax_inverter:** Maximum DC voltage the inverter can accept without risk of damage. **Note:** The label *SAM (TPO Host-Developer) PPA 0.15* is the custom name used to save this scenario file; it is not a system input or simulation parameter. #### **File: SAM_Results_Summary.csv** **Description:** This file is the unedited “Results Summary” export from NREL’s System Advisor Model (SAM) for the 1 MW DC solar array proposed over a Riverside, CA bike path (construction year 2030). The CSV contains three side-by-side result columns—Project Metrics, Developer Metrics, and Host Metrics—so the same rows of metrics can be compared from each stakeholder’s perspective. Energy values refer to the first operating year; all cash values are in constant-2030 U.S. dollars. Blank cells simply mean SAM did not calculate a value for that metric / stakeholder combination; a numeric 0 indicates the model produced a real zero. ##### Variables * **Annual AC energy in Year 1 (kWh):** Electricity delivered to the grid during the system’s first 12 months of operation. * **DC capacity factor in Year 1 (%):** Actual output divided by the output that would occur if the array produced at rated DC power 24/7 for a year. * **Energy yield in Year 1 (kWh/kW):** Annual AC production per unit of installed DC capacity—a convenient site-quality benchmark. * **Performance ratio in Year 1 (decimal):** Overall system efficiency after all losses; values around 0.75–0.85 are typical. * **LCOE levelized cost of energy nominal (¢/kWh):** Lifetime average cost to generate one kWh, including inflation. * **LCOE levelized cost of energy real (¢/kWh):** Same as above but expressed in constant dollars (inflation removed). * **PPA price in Year 1 (¢/kWh):** Starting energy price the host pays under the assumed power-purchase agreement. * **LPPA levelized PPA price nominal (¢/kWh):** Average PPA price over the contract term, including inflation. * **LPPA levelized PPA price real (¢/kWh):** Levelized PPA price expressed in real 2030 ¢/kWh. * **Net capital cost ($):** Total upfront (“overnight”) cost to build the system. * **Equity ($):** Portion of the capital cost financed by the project owner’s own funds. * **Size of debt ($):** Dollar amount borrowed to finance construction. * **Debt percent (%):** Share of total capital cost covered by debt. * **IRR developer internal rate of return (%):** After-tax rate of return on the developer’s equity investment. * **Year developer IRR is achieved:** Calendar year when cumulative equity cash flow becomes positive. * **NPV developer net present value ($):** Present value of developer cash flows, discounted at the assumed equity discount rate. * **Host net present value ($):** Present value of the host’s avoided-cost savings from purchasing solar power versus grid electricity. Positive values indicate savings. * **Host indifference point in Year 1 (¢/kWh):** First-year PPA price that would make the host break even (NPV = 0). * **Host indifference point levelized nominal (¢/kWh):** Levelized PPA price (with inflation) that yields zero NPV for the host. * **Host indifference point levelized real (¢/kWh):** Same as above but expressed in real (inflation-free) cents per kWh. * **Missing Values:** Blank cells indicate SAM did not compute that metric for a given stakeholder; they signify “not applicable,” not missing data. #### **File: PVWatts_Monthly.csv** **Description:** This file contains simulation results exported from NREL’s **PVWatts Calculator**, which estimates monthly solar energy production for a fixed-tilt PV system located in Riverside, California (ZIP code 92507). The file includes both input assumptions and output metrics in a structured format suitable for reuse. The top section of the file summarizes the simulation inputs. The second half is a table of monthly results. Values reflect a premium module system with no tracking, mounted on a fixed open rack. Simulation year is based on a Typical Meteorological Year (TMY) dataset and does not correspond to a specific calendar year. ##### Input Parameters * **Requested Location:** 92507, USA (Riverside, California) * **Location: L**at, Lng: 33.97, -117.34 * **Latitude, Longitude:** 33.97°, –117.34° * **Elevation:** 306.4 meters above sea level * **DC System Size:** 1,147.85 kW (total nameplate capacity of the PV array) * **Module Type:** Premium (higher-efficiency module selection in PVWatts) * **Array Type:** Fixed (open rack) – system is mounted at a fixed tilt, not tracking * **Array Tilt (deg):** 20° – the angle of the PV panels relative to horizontal * **Array Azimuth (deg):** 180° – the direction the panels face; 180° = true south * **System Losses (%):** Aggregate system losses including soiling, wiring, shading, mismatch, etc. (11.08%). * **DC to AC Size Ratio:** DC to AC inverter loading ratio (1.20) * **Inverter Efficiency (%):** Weighted average inverter efficiency (96%) * **Ground Coverage Ratio:** N/A * **Albedo:** From weather file – surface reflectance taken from local weather dataset * **Bifacial:** No (0) – bifacial gain not considered in this simulation ##### Output Variables * **Month:** Numerical month indicator from 1 (January) to 12 (December) * **Daily Average POA Irradiance (kWh/m²/day):** The average amount of solar energy received per square meter per day in the plane of the array (POA) for each month. * **DC Array Output (kWh):** The total direct current (DC) electrical energy produced by the solar array each month. * **AC System Output (kWh):** The total alternating current (AC) electricity output delivered by the system after inverter and system losses. ## Code/software 1. **ArcGIS Pro** * **Software:** ArcGIS Pro (Version 2.8 or later) * **Description:** Proprietary GIS software used for geospatial analysis and site selection in the study. The .lpkx file was originally generated in ArcGIS (not included) and later converted for open access. 2. **QGIS** * **Software:** QGIS version 3.42 * **Description:** A free and open-source geographic information system used to view the publicly shared .qgz file. QGIS enables map visualization, spatial queries, and analysis. This file was converted from ArcGIS to QGIS to meet accessibility requirements for data publication. 3. **Microsoft Excel or Compatible Software** * **Software:** Microsoft Excel (Version 2016 or later) or any open-source spreadsheet software such as LibreOffice Calc or Google Sheets. * **Description:** Used to view and manipulate the following .csv files: * JEDI_Results_Summary.csv * SAM_Results_Summary.csv * PVWatts_Monthly.csv * SAM_Input_Variables_Values.csv **Workflow:** Each file is structured with tabular data, including input parameters, simulation results, and economic metrics. Users can sort, filter, or perform basic calculations using built-in spreadsheet functionalities. Missing data is indicated by blank cells or "NA." 4\. **System Advisor Model (SAM)** * **Software:** SAM (Version 2020.11.29 or later), developed by the National Renewable Energy Laboratory (NREL). * **Description:** Required to replicate or modify simulations described in the SAM_Input_Variables_Values.csv and SAM_Results_Summary.csv files. SAM provides detailed energy modeling and financial analysis for renewable energy systems. 5\. **JEDI Model** * **Software:** Jobs and Economic Development Impact (JEDI) model, developed by NREL. * **Description:** Used to run economic and job creation simulations for renewable energy projects, corresponding to the JEDI_Results_Summary.csv file. The software supports economic multipliers and scenario analysis for regional impacts. ## Workflow Description 1. **Geospatial Analysis:** The original analysis was conducted using a BikePaths_Riverside.lpkx file in ArcGIS Pro for mapping, spatial measurement, and site selection. For public dissemination, this data was exported to a QGIS-compatible .qgz file (BikePaths_Riverside.qgz), which can be accessed using QGIS version 3.42 or later. 2. **Energy & Financial Modeling:** Input parameters were configured directly within the SAM software interface using the “TPO Host-Developer” financial model. The resulting scenario was saved and exported as SAM_Input_Variables_Values.csv. SAM then generated SAM_Results_Summary.csv, which reports first-year energy output, levelized cost of energy (LCOE), internal rate of return (IRR), net present value (NPV), and other project-level financial metrics. 3. **Economic Impact Analysis:** SAM’s system-size output (1 MW DC) fed into JEDI. JEDI generated JEDI_Results_Summary.csv, detailing construction-phase and operating-year jobs, earnings, output, and value added. 4. **Energy Estimates (QA Check):** A parallel PVWatts run produced PVWatts_Monthly.csv, listing monthly POA irradiance and AC energy. These numbers corroborate SAM’s first-year production. The geospatial dataset used in this study was originally developed and analyzed in ArcGIS Pro. To ensure accessibility through open-source software, the data has been exported to a .qgz project file for use with QGIS version 3.42. Users can open and interact with this file using the free QGIS platform, available at [https://qgis.org](https://qgis.org). The original .lpkx file format is not included in this submission to ensure full compatibility with open-source tools and to comply with data accessibility best practices. No custom scripts or code are included in the submission. All software is free or open-source except for Microsoft Excel and ArcGIS Pro, which can be substituted with compatible tools. ## Access information Other publicly accessible locations of the data: * N/A Data was derived from the following sources: * N/A