中国电力 ›› 2025, Vol. 58 ›› Issue (6): 56-66, 155.DOI: 10.11930/j.issn.1004-9649.202411001

• 基于数据驱动的电力系统安全稳定分析与控制 • 上一篇    下一篇

计及风险管理的分布式资源聚合商电力市场交易模型

翟哲(), 陈梓煜(), 刘起兴(), 梁彦杰(), 李智勇()   

  1. 中国南方电网有限公司电力调度控制中心,广东 广州 510000
  • 收稿日期:2024-11-01 发布日期:2025-06-30 出版日期:2025-06-28
  • 作者简介:
    翟哲(1990),男,通信作者,硕士,工程师,从事电力市场设计与运营研究,E-mail:zhaizhe_nfdw@yeah.net
    陈梓煜(1988),男,学士,工程师,从事电力市场设计与运营研究,E-mail:chenziyu@csg.cn
  • 基金资助:
    中国南方电网有限责任公司科技项目(000005GS62220009)。

An Electricity Market Trading Model for Distributed Resource Aggregators Considering Risk Management

ZHAI Zhe(), CHEN Ziyu(), LIU Qixing(), LIANG Yanjie(), LI Zhiyong()   

  1. Dispatching and Control Center, China Southern Power Grid, Guangzhou 510000, China
  • Received:2024-11-01 Online:2025-06-30 Published:2025-06-28
  • Supported by:
    This work is supported by Science and Technology Project of CSG (No.000005GS62220009).

摘要:

新型电力系统背景下,分布式资源大量接入,分布式资源聚合商(distributed energy resource aggregator,DERA)成为电力市场的新兴主体。然而市场交易存在出清电价、风光电源出力等多种不确定性因素,有必要提出计及风险管理的DERA电力市场交易模型,为DERA提供兼顾风险与收益的交易策略。首先,分析了市场组织架构。其次,利用条件风险价值量化不确定性因素带来的风险损失,提出考虑出清电价不确定性的竞价模型与考虑风光电源出力不确定性的调度决策模型,形成DERA参与能量-备用辅助服务市场的交易策略。然后,构建了能量-备用辅助服务市场联合出清模型。最后,以某地区实际能量与备用辅助服务市场的运营数据为例,将所提出的DERA电力市场交易模型应用于该市场的投标与出清。结果表明:所提方法能够指导DERA进行合理的报量报价,提高参与市场的收益。

关键词: 风险管理, 不确定性, 分布式资源聚合商, 能量市场, 备用辅助服务市场

Abstract:

In the context of new power system, the large-scale integration of distributed energy resources has led to the emergence of distributed energy resource aggregators as new entities in the electricity market. However, market transactions are subject to various uncertainties, such as clearing prices and the output of wind and solar power sources. Therefore, it is necessary to propose an electricity market trading model for distributed resource aggregators that considers risk management, providing trading strategies that balance risk and return for aggregators. Firstly, the market organizational structure was analyzed. Secondly, the risk losses caused by uncertainties were quantified using Conditional Value at Risk (CVaR). A bidding model that considers the uncertainty of clearing prices and a scheduling decision-making model that accounts for the uncertainty of wind and solar power output were proposed, forming a trading strategy for distributed energy resource aggregators to participate in the energy-reserve auxiliary services market. Thirdly, a joint clearing model for the energy-reserve auxiliary services market was constructed. Finally, using actual operational data from the energy and reserve auxiliary services market in a certain region as an example, the proposed electricity market trading model for distributed energy resource aggregators was applied to the bidding and clearing processes of that market. The results show that the proposed method can guide distributed energy resource aggregators in making rational quantity bids and offers, thereby increasing their market participation profits.

Key words: risk management, uncertainty, distributed energy resource aggregator, energy market, reserve auxiliary services market


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