Pub Date : 2023-07-05DOI: 10.1109/TEMPR.2023.3292425
Ellen Beckstedde;Leonardo Meeus;Erik Delarue
Distribution System Operators (DSOs) in Europe increasingly employ flexibility markets to manage overloaded grid lines or transformers. One of the main concerns is that grid users will use these flexibility markets to deliberately create and solve congestion, also known as inc-dec gaming. However, the relevance of this game has not yet been explored for distribution grids. We propose a bilevel model with a three-stage electricity market to examine the inc-dec game in flexibility markets at distribution level and redispatch markets at transmission level. We show that the proposed model can be formulated as a Mathematical Program with Equilibrium Constraints (MPEC) and converted into a Mixed-Integer Linear Program (MILP). We demonstrate the model using a stylized example of renewable energy curtailment due to limited capacity at the transmission and distribution network interface, which is a typical congestion situation in Europe. In our test case, the results show that strategic agents can game flexibility markets. We also find examples of the price-setter game and the inc-dec games using redispatch markets. We compare the characteristics of these games with the existing literature to help regulators and system operators to detect them in practice.
{"title":"A Bilevel Model to Study Inc-Dec Games at the TSO-DSO Interface","authors":"Ellen Beckstedde;Leonardo Meeus;Erik Delarue","doi":"10.1109/TEMPR.2023.3292425","DOIUrl":"10.1109/TEMPR.2023.3292425","url":null,"abstract":"Distribution System Operators (DSOs) in Europe increasingly employ flexibility markets to manage overloaded grid lines or transformers. One of the main concerns is that grid users will use these flexibility markets to deliberately create and solve congestion, also known as inc-dec gaming. However, the relevance of this game has not yet been explored for distribution grids. We propose a bilevel model with a three-stage electricity market to examine the inc-dec game in flexibility markets at distribution level and redispatch markets at transmission level. We show that the proposed model can be formulated as a Mathematical Program with Equilibrium Constraints (MPEC) and converted into a Mixed-Integer Linear Program (MILP). We demonstrate the model using a stylized example of renewable energy curtailment due to limited capacity at the transmission and distribution network interface, which is a typical congestion situation in Europe. In our test case, the results show that strategic agents can game flexibility markets. We also find examples of the price-setter game and the inc-dec games using redispatch markets. We compare the characteristics of these games with the existing literature to help regulators and system operators to detect them in practice.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"430-440"},"PeriodicalIF":0.0,"publicationDate":"2023-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88866418","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}
In observing the rapid growth of distributed energy resources (DERs), regional transmission organizations (RTOs) have been investigating the upcoming challenges and potential methods to support their deeper market integration. This article studies the Midcontinent Independent System Operator's (MISO) distribution factor-based commercial pricing node (Cpnode)-elemental pricing node (Epnode) network model, analyzing its suitability and potential issues in supporting the market integration of DERs across multiple locations as aggregated demand response resources (DRRs). Specifically, this article modifies the MISO's existing DRR models to aggregate component resources on different Epnodes via distribution factors as dispatchable DRRs at Cpnodes. These aggregated dispatchable DRRs will directly participate in the MISO's real-time (RT) energy market and follow the MISO's dispatch instructions at Cpnodes through the Epnode-level component resource redispatch. However, distribution factor inaccuracy could cause oscillations in locational marginal prices (LMPs) and dispatches of DRRs in the RT energy market. To this end, influential factors contributing to the occurrence of oscillations are discussed, and five distribution factor updating strategies are studied. Moreover, a correction term is proposed to resolve the timing misalignment issue in transmission constraints. Numerical simulations via the MISO's RT Security-Constrained Economic Dispatch (RT-SCED) tool and actual MISO production cases are conducted to evaluate these strategies and influential factors.
{"title":"Analyzing Real-Time Market Oscillation of Demand Response Resource Aggregation—A MISO Case","authors":"Yikui Liu;Yonghong Chen;Robert Merring;Bing Huang;Lei Wu","doi":"10.1109/TEMPR.2023.3291329","DOIUrl":"10.1109/TEMPR.2023.3291329","url":null,"abstract":"In observing the rapid growth of distributed energy resources (DERs), regional transmission organizations (RTOs) have been investigating the upcoming challenges and potential methods to support their deeper market integration. This article studies the Midcontinent Independent System Operator's (MISO) distribution factor-based commercial pricing node (Cpnode)-elemental pricing node (Epnode) network model, analyzing its suitability and potential issues in supporting the market integration of DERs across multiple locations as aggregated demand response resources (DRRs). Specifically, this article modifies the MISO's existing DRR models to aggregate component resources on different Epnodes via distribution factors as dispatchable DRRs at Cpnodes. These aggregated dispatchable DRRs will directly participate in the MISO's real-time (RT) energy market and follow the MISO's dispatch instructions at Cpnodes through the Epnode-level component resource redispatch. However, distribution factor inaccuracy could cause oscillations in locational marginal prices (LMPs) and dispatches of DRRs in the RT energy market. To this end, influential factors contributing to the occurrence of oscillations are discussed, and five distribution factor updating strategies are studied. Moreover, a correction term is proposed to resolve the timing misalignment issue in transmission constraints. Numerical simulations via the MISO's RT Security-Constrained Economic Dispatch (RT-SCED) tool and actual MISO production cases are conducted to evaluate these strategies and influential factors.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"455-467"},"PeriodicalIF":0.0,"publicationDate":"2023-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85644757","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}
Pub Date : 2023-06-26DOI: 10.1109/TEMPR.2023.3289582
Stephen Hardy;Andreas Themelis;Kaoru Yamamoto;Hakan Ergun;Dirk Van Hertem
This work examines the generation and transmission expansion planning problem of offshore grids under different market clearing mechanisms: a home market design, a zonally cleared offshore bidding zone and a nodally cleared offshore bidding zone. It aims at answering two questions. Is knowing the market structure a priori necessary for effective generation and transmission expansion planning? And which market mechanism results in the highest overall social welfare? To this end, a multi-period, stochastic generation and transmission expansion planning formulation is developed for both nodal and zonal market designs. The approach considers the costs and benefits among stake-holders of hybrid offshore assets as well as gross consumer surplus. The methodology is demonstrated on a North Sea test grid based on projects from the European network of transmission system operators' ten-year network development plan. An upper bound on potential social welfare in zonal market designs is calculated and it is concluded that from a generation and transmission perspective, knowing the market structure a priori is not strictly necessary but planning under the assumption of a nodal offshore bidding zone is recommended as it results in the highest overall social welfare and best risk adjusted return.
{"title":"Optimal Grid Layouts for Hybrid Offshore Assets in the North Sea Under Different Market Designs","authors":"Stephen Hardy;Andreas Themelis;Kaoru Yamamoto;Hakan Ergun;Dirk Van Hertem","doi":"10.1109/TEMPR.2023.3289582","DOIUrl":"10.1109/TEMPR.2023.3289582","url":null,"abstract":"This work examines the generation and transmission expansion planning problem of offshore grids under different market clearing mechanisms: a home market design, a zonally cleared offshore bidding zone and a nodally cleared offshore bidding zone. It aims at answering two questions. Is knowing the market structure a priori necessary for effective generation and transmission expansion planning? And which market mechanism results in the highest overall social welfare? To this end, a multi-period, stochastic generation and transmission expansion planning formulation is developed for both nodal and zonal market designs. The approach considers the costs and benefits among stake-holders of hybrid offshore assets as well as gross consumer surplus. The methodology is demonstrated on a North Sea test grid based on projects from the European network of transmission system operators' ten-year network development plan. An upper bound on potential social welfare in zonal market designs is calculated and it is concluded that from a generation and transmission perspective, knowing the market structure a priori is not strictly necessary but planning under the assumption of a nodal offshore bidding zone is recommended as it results in the highest overall social welfare and best risk adjusted return.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"468-479"},"PeriodicalIF":0.0,"publicationDate":"2023-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80597350","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}
Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified timeframe. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of the RePtA VPP joining multiple markets over the conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor flexibility.
{"title":"Multi-Timescale Trading Strategy for Renewable Power to Ammonia Virtual Power Plant in the Electricity, Hydrogen, and Ammonia Markets","authors":"Sirui Wu;Jin Lin;Jiarong Li;Feng Liu;Yonghua Song;Yanhui Xu;Xiang Cheng;Zhipeng Yu","doi":"10.1109/TEMPR.2023.3287857","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3287857","url":null,"abstract":"Renewablepower to ammonia (RePtA) is a prominent zero-carbon pathway for decarbonization. Due to the imbalance between renewables and production energy demand, the RePtA system relies on electricity exchange with the power grid. Participating in the electricity market as a virtual power plant (VPP) may help to reduce energy costs. However, the power profile of local photovoltaics and wind turbines is similar to those in the market, resulting in rising energy costs under the conventional strategy. Hence, we develop a multi-timescale trading strategy for the RePtA VPP in the electricity, hydrogen, and ammonia markets. By utilizing the hydrogen and ammonia buffer systems, the RePtA VPP can optimally coordinate production planning. Moreover, we find it possible to describe the trading of electricity, ammonia, and hydrogen in a unified timeframe. The two-stage robust optimization model of the electricity market is extended to multiple markets and solved by the column and constraint generation (CC&G) algorithm. The case is derived from an actual project in the Inner Mongolia Autonomous Region. Sensitivity analysis demonstrates the economic advantages of the RePtA VPP joining multiple markets over the conventional strategy and reveals the necessity of the hydrogen and ammonia buffer and reactor flexibility.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"322-335"},"PeriodicalIF":0.0,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138633842","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}
Pub Date : 2023-06-16DOI: 10.1109/TEMPR.2023.3287027
Can Huang;Qinran Hu;Linwei Sang;Donald D. Lucas;Robin Wong;Bin Wang;Wanshi Hong;Mengqi Yao;Vaibhav Donde
Public Safety Power Shutoffs (PSPS), also known as proactive de-energizations, proactively de-energize a portion of power systems to mitigate the risk of catastrophic wildfires caused by electric infrastructure. Since the first practice in Southern California in 2012, PSPS have been widely discussed in government and industry, but seldom in the academic literature. This article surveys the PSPS program in California, including its history, policies, and practices. In practice, PSPS present strong interactions between electric utilities and customers, yielding PSPS a trade-off problem to balance the risk of power-line-ignited wild-fires (i.e., wildfire risk) against the harms of power shutoff (i.e., PSPS risk). In this regard, this article summarizes the industry-standard and research methods for PSPS studies, including models, data sources, and test systems. It is suggested to integrate engineering solutions with social-economic science, such as energy innovation, energy equity, and PSPS uncertainties, in future PSPS studies.
{"title":"A Review of Public Safety Power Shutoffs (PSPS) for Wildfire Mitigation: Policies, Practices, Models and Data Sources","authors":"Can Huang;Qinran Hu;Linwei Sang;Donald D. Lucas;Robin Wong;Bin Wang;Wanshi Hong;Mengqi Yao;Vaibhav Donde","doi":"10.1109/TEMPR.2023.3287027","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3287027","url":null,"abstract":"Public Safety Power Shutoffs (PSPS), also known as proactive de-energizations, proactively de-energize a portion of power systems to mitigate the risk of catastrophic wildfires caused by electric infrastructure. Since the first practice in Southern California in 2012, PSPS have been widely discussed in government and industry, but seldom in the academic literature. This article surveys the PSPS program in California, including its history, policies, and practices. In practice, PSPS present strong interactions between electric utilities and customers, yielding PSPS a trade-off problem to balance the risk of power-line-ignited wild-fires (i.e., wildfire risk) against the harms of power shutoff (i.e., PSPS risk). In this regard, this article summarizes the industry-standard and research methods for PSPS studies, including models, data sources, and test systems. It is suggested to integrate engineering solutions with social-economic science, such as energy innovation, energy equity, and PSPS uncertainties, in future PSPS studies.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 3","pages":"187-197"},"PeriodicalIF":0.0,"publicationDate":"2023-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9794458/10250976/10154121.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50328316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1109/TEMPR.2023.3280692
{"title":"IEEE Transactions on Energy Markets, Policy, and Regulation Information for Authors","authors":"","doi":"10.1109/TEMPR.2023.3280692","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3280692","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 2","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9794458/10153503/10153533.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67817736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1109/TEMPR.2023.3280686
{"title":"IEEE Power & Energy Society Information","authors":"","doi":"10.1109/TEMPR.2023.3280686","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3280686","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 2","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9794458/10153503/10153515.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67817737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1109/TEMPR.2023.3280690
{"title":"Blank Page","authors":"","doi":"10.1109/TEMPR.2023.3280690","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3280690","url":null,"abstract":"","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 2","pages":"C4-C4"},"PeriodicalIF":0.0,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9794458/10153503/10153529.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67817734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-05DOI: 10.1109/TEMPR.2023.3281392
Paulo Victor de Souza Borges;Armando Martins Leite da Silva;Delberis A. Lima;Luiz C. Nascimento
This paper presents a new methodology for valuation and remuneration of distributed generation (DG) sources in distribution power systems. The main concept is the shaping of a tariff signal capable of capturing the effects of DG, accurately measuring the costs and benefits and allocating them according to the responsibility of each generating agent, in view of their site in the grid. This signaling is composed by the changes provoked by DG in four tariff properties: network usage, electrical losses, peak load, and reliability indices. The allocation of responsibilities among generators is performed using the Shapley value from the cooperative game theory. To illustrate the proposed methodology, the IEEE RBTS DG version and a Brazilian distribution network are used and the results obtained are widely discussed.
{"title":"DG Locational Value in Distribution Systems Considering Reliability via Cooperative Game Theory","authors":"Paulo Victor de Souza Borges;Armando Martins Leite da Silva;Delberis A. Lima;Luiz C. Nascimento","doi":"10.1109/TEMPR.2023.3281392","DOIUrl":"10.1109/TEMPR.2023.3281392","url":null,"abstract":"This paper presents a new methodology for valuation and remuneration of distributed generation (DG) sources in distribution power systems. The main concept is the shaping of a tariff signal capable of capturing the effects of DG, accurately measuring the costs and benefits and allocating them according to the responsibility of each generating agent, in view of their site in the grid. This signaling is composed by the changes provoked by DG in four tariff properties: network usage, electrical losses, peak load, and reliability indices. The allocation of responsibilities among generators is performed using the Shapley value from the cooperative game theory. To illustrate the proposed methodology, the IEEE RBTS DG version and a Brazilian distribution network are used and the results obtained are widely discussed.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 4","pages":"336-347"},"PeriodicalIF":0.0,"publicationDate":"2023-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82075423","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}
In a growing retail electricity market, demand response (DR) is becoming an integral part of the system to enhance economic and operational performances. This is rendered as incentive-based DR (IBDR) in the proposed study. It presents a bi-level decision framework under the ambit of multiple demand response providers (DRPs) in the retail competition. It is formulated as a multi-leader-multi-follower game, where multiple DRPs, as the DR stakeholders, are strategically interacting to optimize load serving entity cost at the upper level, and individual DRP as the aggregated customers is optimizing its cost at the lower level. The strategic behavior of DRPs is modeled in a game-theoretic framework using a generalized Stackelberg game. Further, the existence and uniqueness of the game are validated using variational inequalities. It is presented as a nonlinear problem to consider AC network constraints. An equilibrium problem with equilibrium constraints is used as a mathematical program to model the multi-leader-multi-follower, bi-level problem, which is simultaneously solved for all DRPs. The diagonalization method is employed to solve the problem. The detailed numerical analyses are conducted on IEEE 33-bus test and Indian-108 bus distribution systems to demonstrate the applicability and scalability of the proposed model and the suggested method.
{"title":"A Bi-Level Decision Framework for Incentive-Based Demand Response in Distribution Systems","authors":"Vipin Chandra Pandey;Nikhil Gupta;Khaleequr Rehman Niazi;Anil Swarnkar;Tanuj Rawat;Charalambos Konstantinou","doi":"10.1109/TEMPR.2023.3282443","DOIUrl":"https://doi.org/10.1109/TEMPR.2023.3282443","url":null,"abstract":"In a growing retail electricity market, demand response (DR) is becoming an integral part of the system to enhance economic and operational performances. This is rendered as incentive-based DR (IBDR) in the proposed study. It presents a bi-level decision framework under the ambit of multiple demand response providers (DRPs) in the retail competition. It is formulated as a multi-leader-multi-follower game, where multiple DRPs, as the DR stakeholders, are strategically interacting to optimize load serving entity cost at the upper level, and individual DRP as the aggregated customers is optimizing its cost at the lower level. The strategic behavior of DRPs is modeled in a game-theoretic framework using a generalized Stackelberg game. Further, the existence and uniqueness of the game are validated using variational inequalities. It is presented as a nonlinear problem to consider AC network constraints. An equilibrium problem with equilibrium constraints is used as a mathematical program to model the multi-leader-multi-follower, bi-level problem, which is simultaneously solved for all DRPs. The diagonalization method is employed to solve the problem. The detailed numerical analyses are conducted on IEEE 33-bus test and Indian-108 bus distribution systems to demonstrate the applicability and scalability of the proposed model and the suggested method.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"1 3","pages":"211-225"},"PeriodicalIF":0.0,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50329185","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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