Research On Multi-Energy Optimized Capacity Ratio Of Rural Microgrid Based On KFCM-WOA Algorithm

With the vigorous development of smart agriculture and facilities,power consumption in rural areas will continue to increase.However,existing infrastructure such as rural power grids are difficult to meet large-scale power demand,affecting social and economic development in rural areas.At the same time,some remote mountainous areas and agricultural and pastoral areas have problems such as harsh natural environments and long transmission distances.The construction of transmission lines is difficult,resulting in high power costs and large transmission losses in large areas for remote areas.Aiming at the practical problem that traditional energy sources cannot meet the economic development power supply in rural areas,the use of wind-solar-gas-storage complementary power generation to compensate for the shortcomings of randomness and strong fluctuations in wind and sunlight can provide relatively stable and reliable power for the load.The status quo of domestic and foreign research on the problem is analyzed,and the existing problems are analyzed,and on this basis,research on the allocation of multi-energy complementary capacity is conducted.The main research contents of the thesis include the following three points:The basic principles of wind power generation,photovoltaic power generation,biogas power generation,and energy storage system power generation were analyzed,and corresponding mathematical models were constructed.The operating principles and operating characteristics of each part of the wind,photovoltaic,and gas storage were analyzed,which laid the foundation for capacity allocation research.basis.The optimized allocation method of wind,solar and gas storage complementary power generation capacity is analyzed.Aiming at the two objective functions of the smallest energy storage capacity and the lowest total equipment investment cost in the wind,solar and gas energy storage complementary power generation system,a distributed energy share of the system capacity share and SOC status are constructed.The numerical and stable security indicators are used as constraints to optimize the configuration model.The shortcomings of the standard whale algorithm are analyzed.The kernel fuzzy C-means clustering and Levy flight strategy are used to improve the algorithm development and exploration capabilities.An improved whale algorithm(KFCM-WOA).Finally,a village in a county in Baiyin city was selected to analyze the capacity optimization configuration of the wind-gas-gas storage complementary power generation system.The feasibility of the optimized configuration method was verified.The capacity configuration scheme can meet the load energy requirements and reduce the rate of wind and light abandonment.And operation and maintenance costs.The performance of particle swarm optimization,genetic algorithm,standard whale optimization algorithm and improved whale optimization algorithm are compared and analyzed respectively.Simulation results show that the improved whale optimization algorithm is effective for solving the capacity allocation optimization problem,and has greatly improved the convergence speed and optimization accuracy.