you are researcher that you want to try chapter 2,3 of thesis in {## Summary key of Chapter1:

The thesis titled *"Generation System Rehabilitation with the Aim of Flexibility Procurement"* explores the integration of renewable energy sources into power systems, driven by the urgent need to reduce carbon emissions and transition to sustainable energy systems. This transition, while environmentally beneficial, presents significant challenges in maintaining the reliability and efficiency of power systems. The variable nature of renewable energy sources, particularly wind and solar, introduces variability and uncertainty in power generation, necessitating high flexibility in power systems to manage these fluctuations. The research focuses on the role of rehabilitating old generation units to improve system flexibility, facilitating the integration of renewable resources while ensuring reliability and economic efficiency.

The study identifies a critical gap in existing research regarding the long-term planning of renewable integration, as current models focus primarily on short-term operational planning. It also highlights the lack of advanced modeling techniques that address operational constraints like ramping rates and storage requirements, which are essential for developing practical solutions. The thesis aims to create a comprehensive framework for rehabilitating aging power plants to enhance system flexibility, assessing the technical and economic feasibility of such rehabilitation versus alternatives like new generation capacity or energy storage systems. Additionally, it seeks to evaluate how rehabilitated units can support the integration of variable renewable energy sources, ensuring a smooth transition to sustainable energy systems.

The framework includes optimization techniques for decision-making in rehabilitating old plants, considering technical, economic, and regulatory constraints. The research emphasizes the importance of flexibility in modern power systems and the potential of rehabilitating existing infrastructure to meet the growing demand for renewable energy integration. Through advanced optimization and modeling, the study aims to provide a strategic approach for improving the resilience and sustainability of power grids in the face of increasing renewable energy penetration.

Overall, this thesis contributes to filling the research gap in integrating renewable energy into power systems by exploring the viability and benefits of rehabilitating old generation units, offering new insights into maintaining grid reliability and efficiency in the context of global energy transitions.

To achieve the objectives outlined in the thesis titled *"Generation System Rehabilitation with the Aim of Flexibility Procurement,"* a comprehensive and detailed research methodology is essential. This methodology will be structured to address the integration of renewable energy sources (RES) into power systems, focusing on the rehabilitation of aging generation units to enhance system flexibility. Below is a step-by-step breakdown of the proposed methodology, ensuring that all aspects are covered to meet the research objectives effectively.}this is outline of chapter 2 and 3 :## Chapter 2: Literature Review

- 2.1 Power System Flexibility:
    - Definitions of flexibility in power systems.
    - Importance of flexibility for integrating renewable energy sources (RES):
        - The increasing penetration of variable renewable energy sources, such as wind and solar, requires flexible resources to balance supply and demand.
        - Flexibility is essential for managing the variability and uncertainty associated with RES.
        - Flexibility allows the system to accommodate more renewable energy and reduce curtailment.
    - Flexibility metrics and assessment methods:
        - Discuss the different metrics and indices proposed in the literature for quantifying flexibility, such as Loss of Flexibility Probability (LOFP), Loss of Flexibility Duration (LOFD), and Loss of Flexibility Expectation (LOFE).
        - Explore the concept of flexibility envelopes, which visually represent the flexibility capabilities of resources over time.
        - Explain the limitations of energy-based flexibility metrics and the advantages of power-based methods.
        - Include discussion on "offline" metrics that enable quick estimations of system flexibility.
    - Flexibility challenges in long-term planning:
        - The increasing penetration of RES creates a mismatch between supply and demand characteristics, requiring long-term flexibility planning.
        - Discuss the need to shift from traditional "power balance" to "flexibility balance" in planning.
        - Highlight the difficulties in accurately predicting long-term flexibility needs due to uncertainties in load growth and renewable energy development.
        - Address the challenges of coordinating and integrating different types of flexible resources, including long-duration storage.
        - Include a discussion on the limitations of traditional planning models that do not adequately account for short-term flexibility requirements.
- 2.2 Generation Rehabilitation:
    - Motivations for rehabilitating aging power plants:
        - Aging power plants face increased operating costs, decreased practical capacities, and deteriorated availability.
        - Rehabilitating these plants can help improve efficiency, reliability, and flexibility while extending their operational life.
        - The need to meet stricter environmental regulations may also motivate rehabilitation efforts to reduce emissions.
    - Technical options for enhancing flexibility:
        - Ramping capabilities:
            - Improving the ability of plants to ramp up and down quickly to follow fluctuations in net load.
            - Exploring techniques like advanced control systems and modifications to combustion processes.
        - Operational life extension:
            - Refurbishing or replacing aging components to extend the useful life of power plants.
            - Discuss the trade-offs between life extension and new investments in more flexible technologies.
        - Advanced control systems:
            - Implementing advanced control systems to optimize plant operation and enhance responsiveness to changing grid conditions.
            - Explore the role of artificial intelligence and machine learning in improving flexibility.
    - Economic considerations and cost-benefit analysis:
        - Conducting thorough cost-benefit analyses to evaluate the economic viability of different rehabilitation options.
        - Consider factors like investment costs, operating and maintenance expenses, expected revenue from increased flexibility, and potential savings from reduced emissions.
        - Compare the costs and benefits of rehabilitation with alternative options like retiring aging plants and investing in new, more flexible technologies.
    - Environmental impacts and emission reduction potential:
        - Evaluating the environmental impacts of rehabilitation projects, focusing on air quality and greenhouse gas emissions.
        - Assessing the potential for emission reductions through improved efficiency, fuel switching, or integration of carbon capture and storage technologies.
        - Analyzing the overall impact of rehabilitation on achieving environmental targets and promoting sustainability.
- 2.3 Optimization Techniques in Power Systems:
    - Application of optimization methods for generation expansion planning:
        - Discuss various optimization techniques used in generation expansion planning, such as linear programming, mixed-integer programming, and stochastic programming.
        - Explain how these methods can be used to determine the optimal mix of generation technologies, considering factors like cost, reliability, and environmental impact.
        - Highlight the need to incorporate long-term flexibility considerations into these models.
    - Integration of flexibility considerations into optimization models:
        - Explore how flexibility metrics and constraints can be integrated into generation expansion planning models.
        - Discuss the use of flexibility domains (e.g., net load fluctuation domain, flexible supply domain) to visually represent and quantify flexibility requirements.
        - Explain how optimization models can be used to determine the optimal allocation and operation of flexible resources, including energy storage, demand response, and flexible generation.
    - Creation of flexibility pockets:
        - Explore the idea of using ramping capabilities of conventional generation units and energy storage systems to create "flexibility pockets" that can help manage changes in net load.
        - Discuss how optimization techniques can be used to determine the optimal sizing and operation of these flexibility pockets to enhance the overall system flexibility.
        - Analyze the potential benefits of flexibility pockets in terms of improved renewable energy integration, reduced curtailment, and increased system reliability.
    - Case studies and examples from literature:
        - Present case studies from the literature that demonstrate the application of optimization techniques for flexibility procurement in generation expansion planning.
        - Include examples showcasing different system configurations, optimization methods, and flexibility solutions.
        - Analyze the results of these studies, highlighting the key findings and insights related to the role of flexibility in power system planning.
- 2.4 Market Mechanisms for Flexibility:
    - Discuss the role of electricity markets in incentivizing the provision of flexibility services.
    - Explore different market mechanisms for procuring flexibility, such as:
        - Flexible ramping products:
            - These products are designed to compensate generators for their ability to ramp up or down quickly to follow changes in net load.
        - Peak shaving auxiliary services:
            - These services are procured to reduce peak demand and improve system efficiency.
        - Capacity markets:
            - These markets ensure adequate capacity resources are available to meet peak demand and provide reserve capacity for reliability.
    - Analyze the effectiveness of these mechanisms in promoting investment and operation of flexible resources.
    - Discuss the challenges and opportunities in designing market mechanisms that appropriately value and compensate for flexibility.
    - Highlight the importance of dynamic mechanisms that can adapt to changing system conditions and provide sufficient incentives for flexibility providers.
- 2.5 Emerging Technologies and Trends:
    - Explore emerging technologies and trends impacting power system flexibility, such as:
        - Advanced energy storage technologies:
            - Discuss the potential of technologies like batteries, pumped hydro storage, compressed air energy storage, and hydrogen storage in providing long-duration flexibility.
        - Demand-side flexibility:
            - Explore the role of demand response, load shifting, and energy efficiency measures in contributing to system flexibility.
        - Power-to-X technologies:
            - Discuss the potential of technologies like power-to-gas and power-to-heat in converting excess renewable energy into other forms of energy and enhancing system flexibility.
        - Artificial intelligence and machine learning:
            - Explain how AI and ML can be utilized for forecasting, optimizing operation, and controlling flexible resources.
    - Analyze the potential benefits and challenges associated with these emerging technologies.

## Chapter 2: Literature Review

- 2.1 Power System Flexibility:
    - Definitions of flexibility in power systems.
    - Importance of flexibility for integrating renewable energy sources (RES):
        - The increasing penetration of variable renewable energy sources, such as wind and solar, requires flexible resources to balance supply and demand.
        - Flexibility is essential for managing the variability and uncertainty associated with RES.
        - Flexibility allows the system to accommodate more renewable energy and reduce curtailment.
    - Flexibility metrics and assessment methods:
        - Discuss the different metrics and indices proposed in the literature for quantifying flexibility, such as Loss of Flexibility Probability (LOFP), Loss of Flexibility Duration (LOFD), and Loss of Flexibility Expectation (LOFE).
        - Explore the concept of flexibility envelopes, which visually represent the flexibility capabilities of resources over time.
        - Explain the limitations of energy-based flexibility metrics and the advantages of power-based methods.
        - Include discussion on "offline" metrics that enable quick estimations of system flexibility.
    - Flexibility challenges in long-term planning:
        - The increasing penetration of RES creates a mismatch between supply and demand characteristics, requiring long-term flexibility planning.
        - Discuss the need to shift from traditional "power balance" to "flexibility balance" in planning.
        - Highlight the difficulties in accurately predicting long-term flexibility needs due to uncertainties in load growth and renewable energy development.
        - Address the challenges of coordinating and integrating different types of flexible resources, including long-duration storage.
        - Include a discussion on the limitations of traditional planning models that do not adequately account for short-term flexibility requirements.
- 2.2 Generation Rehabilitation:
    - Motivations for rehabilitating aging power plants:
        - Aging power plants face increased operating costs, decreased practical capacities, and deteriorated availability.
        - Rehabilitating these plants can help improve efficiency, reliability, and flexibility while extending their operational life.
        - The need to meet stricter environmental regulations may also motivate rehabilitation efforts to reduce emissions.
    - Technical options for enhancing flexibility:
        - Ramping capabilities:
            - Improving the ability of plants to ramp up and down quickly to follow fluctuations in net load.
            - Exploring techniques like advanced control systems and modifications to combustion processes.
        - Operational life extension:
            - Refurbishing or replacing aging components to extend the useful life of power plants.
            - Discuss the trade-offs between life extension and new investments in more flexible technologies.
        - Advanced control systems:
            - Implementing advanced control systems to optimize plant operation and enhance responsiveness to changing grid conditions.
            - Explore the role of artificial intelligence and machine learning in improving flexibility.
    - Economic considerations and cost-benefit analysis:
        - Conducting thorough cost-benefit analyses to evaluate the economic viability of different rehabilitation options.
        - Consider factors like investment costs, operating and maintenance expenses, expected revenue from increased flexibility, and potential savings from reduced emissions.
        - Compare the costs and benefits of rehabilitation with alternative options like retiring aging plants and investing in new, more flexible technologies.
    - Environmental impacts and emission reduction potential:
        - Evaluating the environmental impacts of rehabilitation projects, focusing on air quality and greenhouse gas emissions.
        - Assessing the potential for emission reductions through improved efficiency, fuel switching, or integration of carbon capture and storage technologies.
        - Analyzing the overall impact of rehabilitation on achieving environmental targets and promoting sustainability.
- 2.3 Optimization Techniques in Power Systems:
    - Application of optimization methods for generation expansion planning:
        - Discuss various optimization techniques used in generation expansion planning, such as linear programming, mixed-integer programming, and stochastic programming.
        - Explain how these methods can be used to determine the optimal mix of generation technologies, considering factors like cost, reliability, and environmental impact.
        - Highlight the need to incorporate long-term flexibility considerations into these models.
    - Integration of flexibility considerations into optimization models:
        - Explore how flexibility metrics and constraints can be integrated into generation expansion planning models.
        - Discuss the use of flexibility domains (e.g., net load fluctuation domain, flexible supply domain) to visually represent and quantify flexibility requirements.
        - Explain how optimization models can be used to determine the optimal allocation and operation of flexible resources, including energy storage, demand response, and flexible generation.
    - Case studies and examples from literature:
        - Present case studies from the literature that demonstrate the application of optimization techniques for flexibility procurement in generation expansion planning.
        - Include examples showcasing different system configurations, optimization methods, and flexibility solutions.
        - Analyze the results of these studies, highlighting the key findings and insights related to the role of flexibility in power system planning.
- 2.4 Market Mechanisms for Flexibility:
    - Discuss the role of electricity markets in incentivizing the provision of flexibility services.
    - Explore different market mechanisms for procuring flexibility, such as:
        - Flexible ramping products:
            - These products are designed to compensate generators for their ability to ramp up or down quickly to follow changes in net load.
        - Peak shaving auxiliary services:
            - These services are procured to reduce peak demand and improve system efficiency.
        - Capacity markets:
            - These markets ensure adequate capacity resources are available to meet peak demand and provide reserve capacity for reliability.
    - Analyze the effectiveness of these mechanisms in promoting investment and operation of flexible resources.
    - Discuss the challenges and opportunities in designing market mechanisms that appropriately value and compensate for flexibility.
    - Highlight the importance of dynamic mechanisms that can adapt to changing system conditions and provide sufficient incentives for flexibility providers.
- 2.5 Emerging Technologies and Trends:
    - Explore emerging technologies and trends impacting power system flexibility, such as:
        - Advanced energy storage technologies:
            - Discuss the potential of technologies like batteries, pumped hydro storage, compressed air energy storage, and hydrogen storage in providing long-duration flexibility.
        - Demand-side flexibility:
            - Explore the role of demand response, load shifting, and energy efficiency measures in contributing to system flexibility.
        - Power-to-X technologies:
            - Discuss the potential of technologies like power-to-gas and power-to-heat in converting excess renewable energy into other forms of energy and enhancing system flexibility.
        - Artificial intelligence and machine learning:
            - Explain how AI and ML can be utilized for forecasting, optimizing operation, and controlling flexible resources.
    - Analyze the potential benefits and challenges associated with these emerging technologies.

### Chapter 3: Research Methodology

### 3.1 Introduction

- Overview of the research approach
- Justification for using a mixed-methods approach
- Outline of the chapter structure

### 3.2 Research Design

- Description of the mixed-methods design
- Explanation of the integration of quantitative and qualitative components
- Justification for selecting mathematical modeling, optimization, and qualitative methods

### 3.3 Quantitative Methodology

- **3.3.1 Mathematical Modeling and Optimization**
    - Overview of mathematical models for system behavior
    - Description of optimization algorithms used
    - Application of these models in evaluating generation unit rehabilitation versus new infrastructure or storage solutions
- **3.3.2 Simulation Techniques**
    - Explanation of the simulation tools (e.g., MATLAB) to model dynamic system behavior
    - Description of scenarios, including varying renewable penetration levels
    - Discussion on modeling assumptions and simplifications
- **3.3.3 Sensitivity Analysis**
    - Approach for assessing impacts of uncertainties in input data
    - Method for scenario analysis and stress testing flexibility options
- **3.3.4 Statistical Analysis of Historical Data**
    - Overview of data sources (e.g., CAISO, ERCOT, and NREL datasets)
    - Data preprocessing and filtering for curtailment and generation trends
    - Statistical methods used for identifying patterns in load and generation

### 3.4 Qualitative Methodology

- **3.4.1 Case Studies**
    - Selection criteria and overview of case studies on generation unit rehabilitation
    - Methods for analyzing and extracting key insights from case studies
- **3.4.2 Expert Interviews and Focus Groups**
    - Approach for selecting industry experts, utility companies, and policymakers
    - Protocols for conducting interviews and focus groups
    - Analysis techniques for qualitative data
- **3.4.3 Meta-Inferences and Joint Displays**
    - Integration of qualitative and quantitative findings
    - Use of joint displays to interpret and present combined data insights

### 3.5 Data Collection and Processing

- **3.5.1 Description of Datasets**
    - Overview of datasets (e.g., NREL report, CAISO, ERCOT, Hawaii curtailment data)
    - Sample data structures and relevant variables (e.g., delivered MWh, curtailed MWh)
- **3.5.2 Data Preprocessing**
    - Data cleaning and handling of confidential and missing data
    - Aggregation methods for quarterly and annual analysis
- **3.5.3 Data Validation**
    - Triangulation and peer review for reliability
    - Techniques to ensure accuracy in quantitative models and qualitative findings

### 3.6 Model Validation and Reliability

- **3.6.1 Model Testing and Calibration**
    - Approach for validating simulation and optimization models
    - Techniques for calibration against historical data
- **3.6.2 Validation Through Sensitivity and Scenario Testing**
    - Sensitivity analysis for model reliability
    - Scenario testing to confirm robustness under various conditions

### 3.7 Stakeholder Engagement and Dissemination of Findings

- Approach for stakeholder involvement in research findings
- Alignment of research with industry practices and policy-making processes

### 3.8 Summary of Chapter

- Recap of research methodology steps
- Transition to Chapter 4 (Results and Analysis).your action is a critical thinking in research database and find best paper match for objective of thesis and related to outline section and write this section in academic persian and must be use real and existe paper and use it and must be do with apa citation method and highlight with apa format in text and end of text as a reference list.write comprehensive all section