A Stochastic Bilevel Model for an Electricity Retailer in a Liberalized Distributed Renewable Energy Market

Prado, Josue Campos do; Wang, Qiao

doi:10.1109/tste.2020.2976968

Cited by 34 publications

(10 citation statements)

References 28 publications

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“…Therefore, it becomes necessary to estimate the probability density function in order to calculate the distribution similarity of load sequences accurately. Thirdly, (3) indicates that the coefficient is determined by θX and the constant 1 2 . However, in practice, θ is subject to fine-tuning.…”

Section: Transfer Condition Analysismentioning

confidence: 99%

“…C OUNTRIES worldwide are progressively deregulating their retail electricity markets, aiming for liberalization and increased competition. This shift has resulted in the emergence of numerous load service entities (LSEs) within the competitive retail market [1], [2]. More accurate shortterm load forecasting (STLF) technology is an effective way to improve the competitiveness of LSEs [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

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Model based Transfer Learning for Efficient Short-term Load Forecasting Model Training

Jiang,

Yang,

Wang

et al. 2024

Preprint

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Section: Transfer Condition Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model based Transfer Learning for Efficient Short-term Load Forecasting Model Training

Jiang,

Yang,

Wang

et al. 2024

Preprint

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“…Participants in the distribution-level market can generally be classified into the following categories: DMOs [38], DNOs, electricity retailers [39], DGs, ESSs, MGs, LCs, and LAs.…”

Section: A Market Participantsmentioning

confidence: 99%

DLMP of Competitive Markets in Active Distribution Networks: Models, Solutions, Applications, and Visions

Wang

Bai

et al. 2023

Proc. IEEE

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| Traditionally, the electric distribution system operates with uniform energy prices across all system nodes. However, as the adoption of distributed energy resources (DERs) propels a shift from passive to active distribution network (ADN) operation, a distribution-level electricity market has been proposed to manage new complexities efficiently. In addition, distribution locational marginal price (DLMP) has been established in the literature as the primary pricing mechanism. The DLMP inherits the LMP concept in the transmission-level wholesale market but incorporates characteristics of the distribution system, such as high R/X ratios and power losses, system imbalance, and voltage regulation needs. The DLMP provides a solution that can be essential for competitive market operation in future distribution systems. This article first provides an overview of the current distribution-level market architectures and their early implementations. Next, the general clearing model, model relaxations, and DLMP formulation are comprehensively reviewed.The state-of-the-art solution methods for distribution market Manuscript

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“…In the literature [55], a two-level trading model with medium-and long-term power markets and a day-ahead market was proposed to optimize the profit on the generation side, and in [56], the impact of with and without medium-and long-term trading restrictions on the decisions of electricity sales companies in the spot context was studied. The authors of [57] developed a multi-stage stochastic optimal power purchase decision model for electricity sales companies to participate in the day-ahead and real-time markets, which explored the impact of market price and demand differences on the power purchase strategies of electricity sales companies. In fact, due to the continuous change in electricity reform policies, the power purchase and sale decisions of power sales companies become extremely complex.…”

Section: Research On Multi-market Power Trading Decisions Of Electric...mentioning

confidence: 99%

Decision on Mixed Trading between Medium- and Long-Term Markets and Spot Markets for Electricity Sales Companies under New Electricity Reform Policies

Wang

Zhao

2022

Energies

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The introduction of the new round of electricity reform policies has made the electricity sales companies’ trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China’s current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market.

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A Stochastic Bilevel Model for an Electricity Retailer in a Liberalized Distributed Renewable Energy Market

Cited by 34 publications

References 28 publications

Model based Transfer Learning for Efficient Short-term Load Forecasting Model Training

Model based Transfer Learning for Efficient Short-term Load Forecasting Model Training

DLMP of Competitive Markets in Active Distribution Networks: Models, Solutions, Applications, and Visions

Decision on Mixed Trading between Medium- and Long-Term Markets and Spot Markets for Electricity Sales Companies under New Electricity Reform Policies

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