1. 华北电力大学电气与电子工程学院, 河北省保定市 071003; 2. 浙江大学电气工程学院, 浙江省杭州市 310027
1. School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China; 2. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
With the high proportion of renewable energy sources, the planning and design of the stand-alone microgrid put higher requirements on the level of flexibility because of no support from the grid. In order to enhance the ability of stand-alone microgrid to accommodate renewable energy, power to hydrogen(P2H)is employed as a flexible resource. Additionally, the capacities of wind turbine and photovoltaic cells, together with the capacities of flexibility resources in microgrid, are taken as decision variables to establish a multi-objective optimization model, which takes the lowest annual investment operation cost and the highest static flexibility level as optimization objectives. Aiming at uncertainties of wind power, photovoltaic intensity and loads during long-time period, the X-means clustering method is introduced to obtain typical scenarios of wind speed, photovoltaic intensity and loads. With regard to the established mixed integer multi-objective programming model, the Tchebycheff approach is adopted to convert the original multi-objective model into multiple single-objective models. For the Pareto non-inferior solution sets obtained by solving a series of single-objective problems, the ranking index is constructed with the utilization of the fuzzy entropy weight method and fuzzy membership degree, and the optimal solution is defined as the non-inferior solution with the highest ranking function value. Finally, the correctness and rationality of the proposed optimal configuration method are verified based on the MATLAB simulation.
LI Peng, HAN Jianpei, YIN Yunxing,et al.Multi-objective Optimal Capacity Configuration of Microgrid with Power to Hydrogen as Flexible Resource[J].Automation of Electric Power Systems,2019,43(17):28-35. DOI:10.7500/AEPS20181023006.