IEEE Transactions on Energy Markets, Policy and Regulation最新文献

IEEE Power & Energy Society Information IEEE电力与能源协会信息

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-09-12 DOI: 10.1109/TEMPR.2025.3599221

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IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-09-12 DOI: 10.1109/TEMPR.2025.3599225

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An Analysis of Market-to-Market Coordination 市场对市场协调的分析

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-07-29 DOI: 10.1109/TEMPR.2025.3581754

Weihang Ren;Álinson S. Xavier;Fengyu Wang;Yongpei Guan;Feng Qiu

{"title":"An Analysis of Market-to-Market Coordination","authors":"Weihang Ren;Álinson S. Xavier;Fengyu Wang;Yongpei Guan;Feng Qiu","doi":"10.1109/TEMPR.2025.3581754","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3581754","url":null,"abstract":"Interregional transmission congestion presents significant challenges for Regional Transmission Operators (RTOs), particularly when loop flow diverts electricity from scheduled paths, occupying neighboring grids and increasing congestion costs. To mitigate this cross-regional congestion, RTOs employ a market-to-market (M2M) process through an iterative method, in which they exchange real-time security-constrained economic dispatch solutions and communicate requests for congestion relief. While this method provides economic benefits, it struggles with issues like power swings and time delays. To explore the full potential of M2M enhancements, in this paper, we first analyze the current M2M iterative method practice to better understand its efficacy and identify places for improvements. Then, we explore enhancements and develop an ADMM method for M2M coordination that optimizes congestion management. Specifically, our ADMM method can achieve a minimal cost that is the same as the cost obtained through a centralized model that optimizes multiple markets altogether. Our final case studies, across a comprehensive set of multi-area benchmark instances, demonstrate the superior performance of the proposed ADMM algorithm for the M2M process. Meanwhile, we identify scenarios where the existing M2M process fails to provide solutions as a by-product. Finally, the algorithm is implemented in an open-source package UnitCommitment.jl for easy access by a broader audience.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 3","pages":"287-296"},"PeriodicalIF":0.0,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Hybrid Energy Storage Dispatch: A Bi-Level Look-Ahead Learning-Assisted Model 混合储能调度：一个双层前瞻学习辅助模型

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-07-14 DOI: 10.1109/TEMPR.2025.3589133

Hooman Khaloie;Andrej Stankovski;Blazhe Gjorgiev;Giovanni Sansavini;François Vallée

{"title":"Hybrid Energy Storage Dispatch: A Bi-Level Look-Ahead Learning-Assisted Model","authors":"Hooman Khaloie;Andrej Stankovski;Blazhe Gjorgiev;Giovanni Sansavini;François Vallée","doi":"10.1109/TEMPR.2025.3589133","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3589133","url":null,"abstract":"Compressed Air Energy Storage (CAES) and Cryogenic Energy Storage (CES) are emerging as promising technologies for sustainable grid-scale applications. To surmount the capacity and geological limitations of traditional CAES systems, this study capitalizes on the hybridization of above-ground CAES with CES, utilizing energy conversion between compressed and liquid air. Here, we develop a comprehensive mathematical model for the operation of the hybrid CAES-CES plant, incorporating discrete constraints to manage internal energy transfers and coordination. The model is leveraged to develop the: <italic>i)</i> look-ahead dispatch schedule over the following days to enhance adaptability in managing stored energy to maximize benefits, and <italic>ii)</i> strategic behavior in electricity markets through unified offers/bids submission. The dispatch problem is structured as a bi-level optimization, with the lower-level addressing market-clearing processes and the upper-level handling storage profit maximization. We reformulate the bi-level setup into a mixed-integer programming model using a mathematical program with equilibrium constraints. To mitigate the computational burden associated with the large number of integer variables in the optimization, we implement a learning-assisted framework for warm-starting these variables. Numerical results show that the hybrid plant can yield up to a 9.08% profit improvement over the standalone alternative under the look-ahead strategy. Further, results demonstrate that under the bi-level setup, the warm-start strategy effectively reduces computation time by 29.30% and 13.35% in the 24- and 118-bus networks, respectively.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 3","pages":"376-392"},"PeriodicalIF":0.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Joint Investment-Operation Planning for Assessing the Economic Impact of Hydrogen Integration in Power Systems 联合投资运营计划评估氢在电力系统中的经济影响

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-07-02 DOI: 10.1109/TEMPR.2025.3584189

Amin Maghami;Evrim Ursavas;Ashish Cherukuri

{"title":"Joint Investment-Operation Planning for Assessing the Economic Impact of Hydrogen Integration in Power Systems","authors":"Amin Maghami;Evrim Ursavas;Ashish Cherukuri","doi":"10.1109/TEMPR.2025.3584189","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3584189","url":null,"abstract":"The transition to renewable energy is pivotal for achieving decarbonization goals in the electricity sector. The focus on low-carbon emissions extends beyond the power sector, emphasizing the need for efficient planning for other energy carriers like green hydrogen. However, the intermittency of renewable sources necessitates solutions for operational planning and supply security, making energy storage systems vital for grid services. Battery energy storage systems (BESS) play a key role in future power networks dominated by renewables, as a short-term buffer. This study explores the conditions under which integrating large-scale BESS with hydrogen facilities in the power network enhances overall system profitability. We analyze this by formulating a joint investment-operation decision-making process, modeled as a mixed-integer chance-constrained optimization problem. To address computational challenges, we implement a scalable decomposition-based solution method that enables tractable optimization. Through the optimal solutions, we analyze different incentive strategies and technology cost scenarios to accelerate the kick-off of hydrogen production. By addressing the challenges of intermittency, pricing mechanisms, and optimizing the synergy between BESS and hydrogen systems, this research provides insights for resilient and profitable renewable energy networks, highlighting that hydrogen selling price significantly influences investment decisions and that incentives can accelerate market entry and transition.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 3","pages":"236-250"},"PeriodicalIF":0.0,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Strategic and Fair Aggregator Interactions in Energy Markets: Multi-Agent Dynamics and Quasiconcave Games 能源市场中的战略与公平聚合互动：多智能体动力学与准iconcave博弈

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-06-23 DOI: 10.1109/TEMPR.2025.3581089

Jiayi Li;Matt Motoki;Baosen Zhang

{"title":"Strategic and Fair Aggregator Interactions in Energy Markets: Multi-Agent Dynamics and Quasiconcave Games","authors":"Jiayi Li;Matt Motoki;Baosen Zhang","doi":"10.1109/TEMPR.2025.3581089","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3581089","url":null,"abstract":"The introduction of aggregator structures has proven effective in bringing fairness to energy resource allocation by negotiating for more resources and economic surplus on behalf of users. This paper extends the fair energy resource allocation problem to a multi-agent setting, focusing on interactions among multiple aggregators in an electricity market. We consider a setting where aggregators submit quantity-only bids as in a noncooperative Cournot game. Unlike classical Cournot models, where firms optimize only for profit, our framework incorporates a bi-level decision process, in which each aggregator determines its total purchase while simultaneously optimizing the internal allocation among its users based on fairness-efficiency trade-off objectives and constraints. We prove that the strategic optimization problems faced by the aggregators form a quasi-concave game, ensuring the existence of a Nash equilibrium. This resolves complexities related to market price dependencies on total purchases and balancing fairness and efficiency in energy allocation. In addition, we design simulations to characterize the equilibrium points of the induced game, demonstrating how aggregators stabilize market outcomes, ensure fair resource distribution, and optimize user surplus. Our findings offer a robust framework for understanding strategic interactions among aggregators, contributing to more efficient and equitable energy markets.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 3","pages":"340-351"},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Minimizing Bid Adjustments and Maximizing Flexibility: A Comprehensive Framework for Grid Prequalification of DERs 最小化投标调整和最大化灵活性：电网预审DERs的综合框架

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-06-16 DOI: 10.1109/TEMPR.2025.3580217

Rohit Vijay;Parul Mathuria

{"title":"Minimizing Bid Adjustments and Maximizing Flexibility: A Comprehensive Framework for Grid Prequalification of DERs","authors":"Rohit Vijay;Parul Mathuria","doi":"10.1109/TEMPR.2025.3580217","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3580217","url":null,"abstract":"Distributed Energy Resources (DERs) offer great potential to provide flexibility-based services but come with operational challenges when integrated in the centralized ancillary service (AS) market operated by transmission system operator (TSO). The current market arrangement lacks sufficient resolution of distribution constraints during market clearing. To address this issue, a detailed grid prequalification process is required before DER participation in the centralized market. In this context, this paper introduces a detailed framework for distribution system operators (DSOs) to qualify DERs and adjust their operational limits, maximizing flexibility with minimal bid deviation. The framework employs network capability regions to consider distribution constraints, uses the Euclidean distance to reduce complex power deviations, and considers grid integration costs as a preference criterion for bid modifications. Results confirm that using a single network capability region allows for dynamic prequalification, which enhances transparency and reduces the need for bid adjustments. Additionally, considering grid integration costs can lead to savings on future reinforcement expenses for DSOs. The approach has been tested using IEEE standard bus systems, demonstrating enhanced flexibility in DERs, which is transferred to the TSO. This approach is suitable for larger systems having multiple DERs connected under a single DSO.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 3","pages":"352-362"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-06-13 DOI: 10.1109/TEMPR.2025.3573826

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IEEE Power & Energy Society Information IEEE电力与能源协会信息

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-06-13 DOI: 10.1109/TEMPR.2025.3573822

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IEEE Transactions on Energy Markets, Policy, and Regulation Information for Authors IEEE能源市场、政策和法规信息汇刊

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-06-13 DOI: 10.1109/TEMPR.2025.3573824

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