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1.智能电网教育部重点实验室(天津大学),天津市 300072
2.国网经济技术研究院有限公司,北京市 102209
Received:01 April 2025,
Revised:2025-07-30,
Online First:12 September 2025,
Published:25 December 2025
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孔祥玉,张龙宇,郭玥等.基于条件风险价值的配电网能量-备用运营策略与均衡分析[J].电力系统自动化,2025,49(24):87-101.
KONG Xiangyu,ZHANG Longyu,GUO Yue,et al.Operation Strategy and Equilibrium Analysis of Energy-Reserve of Distribution Networks Based on Conditional Value at Risk[J].Automation of Electric Power Systems,2025,49(24):87-101.
孔祥玉,张龙宇,郭玥等.基于条件风险价值的配电网能量-备用运营策略与均衡分析[J].电力系统自动化,2025,49(24):87-101. DOI: 10.7500/AEPS20250401005.
KONG Xiangyu,ZHANG Longyu,GUO Yue,et al.Operation Strategy and Equilibrium Analysis of Energy-Reserve of Distribution Networks Based on Conditional Value at Risk[J].Automation of Electric Power Systems,2025,49(24):87-101. DOI: 10.7500/AEPS20250401005.
随着增量配电网运营权的全面放开以及电力市场化改革,增量配电网参与市场面临多主体竞价行为与新能源不确定性等挑战。为此,提出一种基于条件风险价值的配电网能量-备用运营策略与均衡分析方法,模拟多个增量配电网的市场博弈行为与风险管理策略。首先,提出增量配电网参与能量和备用市场的总体框架。其次,构建考虑多个增量配电网参与能量和备用市场的双层优化决策模型。上层以增量配电网参与能量和备用市场的运营成本最小为目标,通过条件风险价值理论衡量不确定性与多主体博弈风险;下层模拟能量和备用市场的联合出清。最后,通过KKT(Karush-Kuhn-Tucker)条件、强对偶理论将非线性双层模型转化为带均衡约束的均衡模型,以表示多个增量配电网之间的博弈关系。算例分析表明,所提方法可有效提高增量配电网在不确定性与多主体博弈环境下的市场竞争力,形成更加契合市场实际的最优运行策略。
With the full liberalization of operation rights of incremental distribution networks and the electricity market reform
incremental distribution networks face challenges such as multi-entity bidding behaviors and uncertainties in renewable energy sources when participating in markets. To address these challenges
the operation strategy of energy-reserve and equilibrium analysis method for distribution networks based on conditional value at risk (CVaR) are proposed to simulate the market game behaviors and risk management strategies of multiple incremental distribution networks. Firstly
an overall framework for incremental distribution networks to participate in the energy and reserve markets is proposed. Secondly
a bi-level optimization decision-making model considering the participation of multiple incremental distribution networks in the energy and reserve markets is constructed. The upper level aims to minimize the operation costs of incremental distribution networks participating in the energy and reserve markets
and uses CVaR theory to measure the risks of uncertainties and multi-agent games; the lower level simulates the joint clearing of the energy and reserve markets. Finally
the nonlinear bi-level model is transformed into an equilibrium model with equilibrium constraints (EPEC) through the Karush-Kuhn-Tucker (KKT) conditions and strong duality theory
so as to describe the game relationship among multiple incremental distribution networks. Case studies show that the proposed method can effectively improve the market competitiveness of incremental distribution networks in the environment of uncertainties and multi-entity games
and form an optimal operation strategy that is more in line with market realities.
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