摘要
随着售电侧电力市场改革的不断深入,研究配电网与微电网群之间的电能交易问题对推动区域电网经济效益具有重要意义。针对此问题,本文研究提出了一种基于纳什议价的配电网与微电网群日前电能交易方法。该方法在充分考虑可再生能源发电和电力负荷波动对微电网电能交易调度影响的基础上,以配电运营商与微电网运营商在电网电价下的最优交易成本作为纳什议价的谈判破裂点,构建了配电运营商与多个微电网运营商分别独立议价的合作博弈模型。其合作博弈均衡的求解问题可转化为社会效益最大化和支付效益最大化两个连续子问题,并采用交替方向乘子法进行分步求解。最后,通过算例分析验证了所提方法对提升区域电网中电能交易主体经济效益的有效性。
With the deepening of the power market reform on the selling side,it is of great significance to study the power transaction between distribution network and microgrid cluster to promote the economic benefits of regional power grid.To solve this problem,a day-ahead power transaction method was proposed based on Nash bargaining for distribution network and microgrid cluster.On the basis of fully considering the influence of renewable energy generation and power load fluctuation on the power transaction scheduling of microgrid,the optimal transaction cost between distribution operators and microgrid operators under the grid price was taken as the breakdown point of Nash negotiation,a cooperative game model of independent negotiation between distribution operators and several microgrid operators was constructed.The cooperative game equilibrium can be transformed into two continuous subproblems of social benefit maximization and payment benefit maximization,which are solved step by step by alternating direction multiplier method.Finally,an example is given to verify the effectiveness of the proposed method in improving the economic benefits of power transaction subjects in regional power grid.
作者
朱涵宇
曹文平
胡存刚
芮涛
郭之栋
罗魁
ZHU Han-yu;CAO Wen-ping;HU Cun-gang;RUI Tao;GUO Zhi-dong;LUO Kui(School of Electrical Engineering and Automation,Anhui University,Hefei 230601,China;Engineering Research Center of Power Quality,Ministry of Education(Anhui University),Hefei 230601,China;China Electric Power Research Institute,Beijing 100192,China)
出处
《科学技术与工程》
北大核心
2023年第10期4225-4233,共9页
Science Technology and Engineering
基金
新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司)开放基金(NYB51202001734)
安徽省高校自然科学基金(KJ2020A0038)。
关键词
微电网群
能量交易
纳什议价
随机优化
交替方向乘子法
microgrid cluster
energy trading
Nash bargaining
stochastic optimization
alternating direction method of multipliers
