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杭州电子科技大学自动化学院,浙江省杭州市 310018
罗平(1978—),女,通信作者,博士,副教授,硕士生导师,主要研究方向:综合能源系统的优化调度。E-mail:luoping@hdu.edu.cn
周濠炳(1997—),男,硕士研究生,主要研究方向:综合能源系统。E-mail:zhbandsxy@163.com
徐林(1994—),男,硕士研究生,主要研究方向:智能微网的优化调度。E-mail:1240988469@qq.com
收稿:2021-01-21,
修回:2021-12-06,
网络出版:2022-03-04,
纸质出版:2022-05-10
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罗平,周濠炳,徐林等.基于区间优化的冷热电联供型多微网日前优化调度[J].电力系统自动化,2022,46(9):137-146.
LUO Ping,ZHOU Haobing,XU Lin,et al.Day-ahead Optimal Scheduling of Multi-microgrids with Combined Cooling, Heating and Power Based on Interval Optimization[J].Automation of Electric Power Systems,2022,46(9):137-146.
罗平,周濠炳,徐林等.基于区间优化的冷热电联供型多微网日前优化调度[J].电力系统自动化,2022,46(9):137-146. DOI: 10.7500/AEPS20210121001.
LUO Ping,ZHOU Haobing,XU Lin,et al.Day-ahead Optimal Scheduling of Multi-microgrids with Combined Cooling, Heating and Power Based on Interval Optimization[J].Automation of Electric Power Systems,2022,46(9):137-146. DOI: 10.7500/AEPS20210121001.
冷热电联供型多微网系统日前优化调度需综合考虑源荷的不确定性、微网间热电功率交互及不同利益主体间的博弈。将各微网作为不同的利益主体,利用区间数描述风光分布式能源和冷热电负荷功率的波动性。以各微网中可控微源出力、可调度电负荷以及微网间的热电交互功率和交互电价为优化变量,建立目标为各微网运行成本最小的纳什议价合作博弈模型。将该非凸优化问题等价变换为两个凸优化子问题,并采用区间序关系和可能度将对应子问题的区间优化模型转化为确定性的凸优化模型。为保证用户的隐私,利用加速的交替方向乘子法对两个子问题进行了分布式求解。最后,通过仿真验证了所提方法的有效性和合理性。
The day-ahead optimal dispatch of the multi-microgrid with combined cooling
heating and power system requires comprehensive consideration of the uncertainty of source and load
the interaction of thermal and electrical power and the game between different stakeholders. Taking each microgrid as different stakeholders
the interval number is used to describe the fluctuation of distributed wind power and photovoltaic power generation and cooling
heating and power load. The controllable micro-source output and schedulable electrical load in each microgrid
the thermal and electrical interactive power and interactive electricity price between microgrids are selected as optimization variables
and a Nash bargaining cooperative game model with the goal of minimizing the operating cost of each microgrid is established. The non-convex optimization problem is equivalently transformed into two convex optimization subproblems
and the interval optimization model of the corresponding subproblem is converted into a deterministic convex optimization model by using interval order relation and possibility degree. To ensure the privacy of users
the accelerated alternating direction multiplier method is used to solve the two subproblems in a distributed way. Finally
the effectiveness and rationality of the proposed method are verified by simulation.
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