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1.浙江工业大学信息工程学院,浙江省杭州市 310023
2.浙江大学电气工程学院,浙江省杭州市 310027
冯昌森(1990—),男,博士,讲师,主要研究方向:电力系统优化控制、电力市场、机器学习、区块链技术等。E-mail:fcs@zjut.edu.cn
任冬冬(1997—),男,硕士研究生,主要研究方向:微网优化调度、区域综合能源系统优化调度。E-mail:2112003261@zjut.edu.cn
沈佳静(1992—),女,硕士研究生,主要研究方向:电力市场、微网优化调度。E-mail:joy-sjj@outlook.com
张有兵(1971—),男,通信作者,教授,博士生导师,主要研究方向:智能电网、分布式发电及新能源优化控制、电动汽车入网、电力系统通信、电能质量监控等。E-mail:youbingzhang@zjut.edu.cn
收稿日期:2021-07-15,
修回日期:2021-12-28,
网络出版日期:2022-03-18,
纸质出版日期:2022-06-10
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冯昌森,任冬冬,沈佳静等.计及多能共享的互联微能源网的分布式协同优化调度[J].电力系统自动化,2022,46(11):47-57.
FENG Changsen,REN Dongdong,SHEN Jiajing,et al.Distributed Coordinated Optimal Scheduling of Interconnected Micro-energy Grids Considering Multi-energy Sharing[J].Automation of Electric Power Systems,2022,46(11):47-57.
冯昌森,任冬冬,沈佳静等.计及多能共享的互联微能源网的分布式协同优化调度[J].电力系统自动化,2022,46(11):47-57. DOI: 10.7500/AEPS20210715001.
FENG Changsen,REN Dongdong,SHEN Jiajing,et al.Distributed Coordinated Optimal Scheduling of Interconnected Micro-energy Grids Considering Multi-energy Sharing[J].Automation of Electric Power Systems,2022,46(11):47-57. DOI: 10.7500/AEPS20210715001.
微能源网是能源互联网末端的微型综合能源系统,对提高可再生能源发电消纳率、实现碳减排的目标具有支撑作用,其运行效率常受制于可再生能源发电的不确定性和多能耦合的协调调度。在此背景下,提出一种计及多能共享的互联微能源网两阶段协同调度模型:第1阶段考虑可再生能源发电出力的不确定性,建立计及多能共享的互联微能源网的能量管理模型,实现互联综合能源系统的多能协同管理;第2阶段建立基于非合作博弈的共享能源价格出清模型,利用广义纳什均衡确定共享能源的交易结算。采用交替方向乘子法对上述两阶段优化问题进行分布式求解,可有效保护微能源网主体的信息安全和隐私。最后,采用算例对所提方法的可行性和有效性进行验证。
Micro-energy grid (MEG) is a micro integrated energy system located at the terminal of the Energy Internet
which plays a supporting role in improving the accommodation rate of the renewable energy power generation and realizing the target of the carbon emission reduction. However
its operation efficiency is usually restricted by the uncertainty of renewable energy power generation and the coordinated scheduling of the coupled multi-energy. In this context
a two-stage coordinated scheduling model for interconnected MEGs considering multi-energy sharing is proposed. In the first stage
the energy management model of interconnected MEGs is established considering the multi-energy sharing as well as the uncertainty of the renewable energy power generation to realize the multi-energy coordinated management for the interconnected integrated energy system. In the second stage
the clearing model for energy sharing price is built based on the non-cooperative game
and the generalized Nash equilibrium is used to determine the transaction settlement of sharing energy. Then
alternating direction method of multipliers is used to solve the abovementioned two-stage optimization problems in a distributed manner
which could effectively protect the information security and privacy of the MEG. Finally
the effectiveness and validation of the proposed method are demonstrated by case studies.
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