基于排序交叉优化算法的冷热电联供微电网经济调度

为提高冷热电联供微电网运行的灵活性,减少运行成本,将地源热泵引入微网,建立一种包含风机、光伏、微型燃气轮机、地源热泵、燃料电池、蓄电装置和蓄冷/热装置的冷热电联供型微电网经济优化模型,并提出一种排序交叉优化算法对各机组的出力进行优化调度。同时,为了满足负荷平衡等式约束和各机组出力约束,提出一种启发式约束处理方法。为验证所提模型和算法的有效性,对微电网夏季和冬季典型运行场景进行了仿真实验,并与其他四种优化算法的结果进行比较。实验结果表明,所提出的算法具有良好的全局收敛性能,所求成本较其他四种优化算法更低,是一种求解冷热电联供微电网经济调度的有效方法。

Microgrid economic dispatch of combined cooling, heating and power based on a rank pair learning crisscross optimization algorithm

To improve the flexibility of a combined cooling, heating and power microgrid and reducing operation costs, the ground source heat pumps are integrated into the microgrid in this paper. An economic optimization model with fans, photovoltaics, micro gas turbines, ground source heat pumps, fuel cells, and electricity storage is established. To optimize the output of each unit, a rank pair learning-based Crisscross Optimization algorithm is developed. A heuristic constraint processing method is developed to satisfy the constraints of load balance and output of each unit. To verify the effectiveness of the proposed model and algorithm, an simulation experiment consisting of typical operation scenarios in summer and winter is conducted, and the results are compared with other four optimization algorithms. The results indicate that the proposed algorithm has good global convergence performance and lower cost than the other four optimization algorithms. Thus, the proposed algorithm is an effective method for solving the economic dispatch of a combined cooling, heating and power microgrid. This work is supported by the National Natural Science Foundation of China (No. 61672226), the Natural Science Foundation of Hunan Province (No. 2018JJ2137), and Excellent Youth Project of Education Department of Hunan Province (No.19B200).