IEEE Transactions on Energy Markets, Policy and Regulation最新文献_第2页

Regression Equilibrium in Electricity Markets 电力市场的回归均衡

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2025-01-17 DOI: 10.1109/TEMPR.2025.3530266

Vladimir Dvorkin

{"title":"Regression Equilibrium in Electricity Markets","authors":"Vladimir Dvorkin","doi":"10.1109/TEMPR.2025.3530266","DOIUrl":"https://doi.org/10.1109/TEMPR.2025.3530266","url":null,"abstract":"In two-stage electricity markets, renewable power producers enter the day-ahead market with a forecast of future power generation and then reconcile any forecast deviation in the real-time market at a penalty. The choice of the forecast model is thus an important strategy decision for renewable power producers as it affects financial performance. In electricity markets with large shares of renewable generation, the choice of the forecast model impacts not only individual performance but also outcomes for other producers. In this paper, we argue for the existence of a competitive regression equilibrium in two-stage electricity markets in terms of the parameters of private forecast models informing the participation strategies of renewable power producers. In our model, renewables optimize the forecast against the day-ahead and real-time prices, thereby maximizing the average profits across the day-ahead and real-time markets. By doing so, they also implicitly enhance the temporal cost coordination of day-ahead and real-time markets. We base the equilibrium analysis on the theory of variational inequalities, providing results on the existence and uniqueness of regression equilibrium in energy-only markets. We also devise two methods to compute regression equilibrium: centralized optimization and a decentralized ADMM-based algorithm.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 1","pages":"121-132"},"PeriodicalIF":0.0,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621542","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}

引用次数: 0

2024 Index IEEE Transactions on Energy Markets, Policy and Regulation Vol. 2 能源市场，政策与监管，第2卷

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-12-17 DOI: 10.1109/TEMPR.2024.3519796

引用次数: 0

Large Language Model-Based Bidding Behavior Agent and Market Sentiment Agent-Assisted Electricity Price Prediction 基于大语言模型的竞价行为Agent与市场情绪Agent辅助电价预测

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-12-16 DOI: 10.1109/TEMPR.2024.3518624

Xin Lu;Jing Qiu;Yi Yang;Chenxi Zhang;Jiafeng Lin;Sihai An

{"title":"Large Language Model-Based Bidding Behavior Agent and Market Sentiment Agent-Assisted Electricity Price Prediction","authors":"Xin Lu;Jing Qiu;Yi Yang;Chenxi Zhang;Jiafeng Lin;Sihai An","doi":"10.1109/TEMPR.2024.3518624","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3518624","url":null,"abstract":"Day-ahead electricity price prediction is crucial for market participants to make optimal trading decisions. The implementation of the five-minute settlement (5MS) process in the Australian National Electricity Market (NEM) on October 1, 2021, reduced the settlement interval from 30 minutes to 5 minutes. This change has led to more frequent adjustments in pricing, allowing for a more accurate reflection of real-time supply and demand conditions. However, this increased frequency has significantly heightened the complexity of price fluctuations in the wholesale market. Consequently, conventional machine learning and deep learning methods struggle to provide accurate predictions at this higher resolution. Since electricity prices are fundamentally determined by the supply-demand balance and the bidding behaviors of market participants, this work introduces individual participant's bidding behaviors into the prediction model. We fine-tune a pre-trained Large Language Model (LLM) to create bidding behavior agents, which forecasts day-ahead bidding behaviors. Moreover, market sentiment plays a significant role in electricity price volatility, yet it remains challenging to quantify and assess its impact. To address this, we employ a pre-trained LLM to analyze online resources, incorporating market sentiment into the price prediction model. Additionally, to enhance the accuracy of spike predictions, we improve the conditional time series generative adversarial network (CTSGAN) model by utilizing a spike confusion matrix and further strengthen the model by integrating bidding behavior and market sentiment as inputs. Case studies demonstrate that the proposed model significantly improves both electricity price and spike prediction accuracy, offering a robust tool for market participants to navigate the complexities of the modern electricity market.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 2","pages":"223-235"},"PeriodicalIF":0.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279071","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}

引用次数: 0

Electricity Market-Clearing With Extreme Events 极端事件下电力市场出清

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-12-13 DOI: 10.1109/TEMPR.2024.3517474

Tomás Tapia;Zhirui Liang;Charalambos Konstantinou;Yury Dvorkin

{"title":"Electricity Market-Clearing With Extreme Events","authors":"Tomás Tapia;Zhirui Liang;Charalambos Konstantinou;Yury Dvorkin","doi":"10.1109/TEMPR.2024.3517474","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3517474","url":null,"abstract":"Extreme events jeopardize power network operations, causing beyond-design failures and massive supply interruptions. Existing market designs fail to internalize and systematically assess the risk of extreme and rare events. Efficiently maintaining the reliability of renewable-dominant power systems during extreme weather events requires co-optimizing system resources, while differentiating between large/rare and small/frequent deviations from forecast conditions. To address this gap in both research and practice, we propose managing the uncertainties associated with extreme weather events through an additional reserve service, termed extreme reserve. The procurement of extreme reserve is co-optimized with energy and regular reserve using a large deviation theory chance-constrained (LDT-CC) model, where LDT offers a mathematical framework to quantify the increased uncertainty during extreme events. To mitigate the high additional costs associated with reserve scheduling under the LDT-CC model, we also propose an LDT model based on weighted chance constraints (LDT-WCC). This model prepares the power system for extreme events at a lower cost, making it a less conservative alternative to the LDT-CC model. The proposed market design leads to a competitive equilibrium while ensuring cost recovery. Numerical experiments on an illustrative system and a modified 8-zone ISO New England system highlight the advantages of the proposed market design.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 2","pages":"194-208"},"PeriodicalIF":0.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279074","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}

引用次数: 0

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 : 2024-12-12 DOI: 10.1109/TEMPR.2024.3505656

引用次数: 0

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 : 2024-12-12 DOI: 10.1109/TEMPR.2024.3505658

引用次数: 0

Blank Page 空白页

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-12-12 DOI: 10.1109/TEMPR.2024.3505660

引用次数: 0

A Catastrophe Bond Design for the Financial Resilience of Electric Utilities Against Wildfires 电力公司应对野火财务弹性的巨灾债券设计

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-11-18 DOI: 10.1109/TEMPR.2024.3501012

Saeed Nematshahi;Behrouz Sohrabi;Ali Arabnya;Amin Khodaei;Erin Belval

{"title":"A Catastrophe Bond Design for the Financial Resilience of Electric Utilities Against Wildfires","authors":"Saeed Nematshahi;Behrouz Sohrabi;Ali Arabnya;Amin Khodaei;Erin Belval","doi":"10.1109/TEMPR.2024.3501012","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3501012","url":null,"abstract":"The scale of wildfires, in terms of acreage burned and mortality rates, is risingdue to climate change. There are various causes for wildfire ignition; however, power lines are one of the most significant factors, leading to some of the most devastating wildfire events over the past decade and even bankrupting electric utilities. Traditional insurance strategies are often not applicable for providing financial resilience to electric utilities against such catastrophic events. This paper quantifies the associated risk and proposes a catastrophe bond (CAT bond) as a form of parametric insurance to cover a portion of the risk. Vegetative fuel, weather, power grid, and historical wildfire ignition data are integrated into a proposed simulation-based methodology to accurately price the risk of the third-party wildfire liability, transmission line reconstruction, and the cost of load-shedding. The proposed methodology offers a useful tool for transmission system owners to transfer a portion of the risk of wildfire ignition to CAT bond investors. In addition, the premium calculation is analyzed through a sensitivity analysis to calibrate the indemnity-based CAT bond parameters.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 1","pages":"133-143"},"PeriodicalIF":0.0,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621897","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}

引用次数: 0

Exploring and Quantifying the Impact of Ex-Ante Market Power Mitigation in the Integrated European Day-Ahead Electricity Market 探索和量化欧洲一体化日前电力市场事前电力缓解的影响

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-11-15 DOI: 10.1109/TEMPR.2024.3500068

Christos K. Simoglou;Pandelis N. Biskas;Georgios I. Tsoumalis;Alex D. Papalexopoulos

{"title":"Exploring and Quantifying the Impact of Ex-Ante Market Power Mitigation in the Integrated European Day-Ahead Electricity Market","authors":"Christos K. Simoglou;Pandelis N. Biskas;Georgios I. Tsoumalis;Alex D. Papalexopoulos","doi":"10.1109/TEMPR.2024.3500068","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3500068","url":null,"abstract":"Default Energy Bids (DEBs) lie among the most prominent ex-ante market power mitigation approaches implemented in modern electricity markets. This paper presents a conduct-and-impact methodology for the exploration and quantification of the impact that the enforcement of DEBs would have on the operation of the integrated European day-ahead electricity market as a whole. A quantitative large-scale simulation of the day-ahead market of eighteen European countries has been performed in order to evaluate the effect that the implementation of various DEB levels in the sell orders of thermal generating units would have on the market clearing prices and the associated revenues of market participants. Extensive scenario-based chronological simulations using a specialized and commercially available day-ahead market simulation software for a historical two-month period in 2021-2022 indicated that if thermal generating units were allowed to bid above their average variable cost only by up to 10–30%, day-ahead market clearing prices in most European countries would decrease, also leading to lower market revenues from −5.2% up to −9.9% for all market participants. The proposed methodology is directly applicable to unit-based day-ahead electricity markets in Europe. An extension to European portfolio-based day-ahead markets is also proposed.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 1","pages":"83-97"},"PeriodicalIF":0.0,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621543","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}

引用次数: 0

Fair Least Core: Efficient, Stable and Unique Game-Theoretic Reward Allocation in Energy Communities by Row-Generation 公平最小核心：基于行代的能源社区高效、稳定、独特的博弈论奖励分配

IEEE Transactions on Energy Markets, Policy and Regulation Pub Date : 2024-11-08 DOI: 10.1109/TEMPR.2024.3495237

Davide Fioriti;Giancarlo Bigi;Antonio Frangioni;Mauro Passacantando;Davide Poli

{"title":"Fair Least Core: Efficient, Stable and Unique Game-Theoretic Reward Allocation in Energy Communities by Row-Generation","authors":"Davide Fioriti;Giancarlo Bigi;Antonio Frangioni;Mauro Passacantando;Davide Poli","doi":"10.1109/TEMPR.2024.3495237","DOIUrl":"https://doi.org/10.1109/TEMPR.2024.3495237","url":null,"abstract":"Energy Communities are increasingly proposed as a tool to boost renewable penetration and maximize citizen participation in energy matters. These policies enable the formation of legal entities that bring together power system members, enabling collective investment and operation of energy assets. However, designing appropriate reward schemes is crucial to fairly foster individuals to join, as well to ensure collaborative and stable aggregation, maximizing community benefits. Cooperative Game Theory, emphasizing coordination among members, has been extensively proposed for ECs and microgrids; however, it is still perceived as obscure and difficult to compute due to its exponential computational requirements. This study proposes a novel framework for stable fair benefit allocation, named Fair Least Core, that provides uniqueness, reproducibility, stability and fairness. A novel row-generation algorithm is also proposed that allows to efficiently compute the imputations for coalitions of practical size. A case study of ECs with up to 100 members shows the stability, reproducibility, fairness and efficiency properties of proposed model. The results also highlight how the market power of individual users changes as the community grows larger, which can steer the development of practical reliable, robust and fair reward allocations for energy system applications.","PeriodicalId":100639,"journal":{"name":"IEEE Transactions on Energy Markets, Policy and Regulation","volume":"3 2","pages":"170-181"},"PeriodicalIF":0.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10748402","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144281208","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}

引用次数: 0