Optimal Allocation Of Hybrid Energy Storage Capacity Based On Improved Multi-objective Particle Swarm Algorithm

Due to the increasingly serious energy consumption and environmental problems,new energy technologies have been developed rapidly.In particular,new energy technologies,mainly photovoltaic,are favored by more experts and scholars.Distributed Generation(DG)has attracted much attention from the international community.However,due to the intermittent,random and fluctuating characteristics of DG,it brings many problems to the safe and stable operation of the distribution network,such as feeder power fluctuation,inter-line power imbalance and voltage crossing limits.There are many types of energy storage technologies with different characteristics,which complement each other in terms of capacity scale,response time,cost minimization and technical maturity.The use of two or more types of energy storage technologies can effectively improve the grid integration capability of the landscape and the continuous and stable operation of the distribution network.Therefore,how to optimize the capacity configuration of hybrid energy storage systems has become an important direction of research for scholars at home and abroad.The following studies are conducted in this paper:First,this paper explores the output characteristics of wind energy development and photovoltaic development,and establishes a stochastic output model.By applying the theory of sequence operation,the probability density distribution of wind and photovoltaic power generation is discretized so as to obtain the expected sequence of wind and photovoltaic power generation at each moment,which lays the foundation for us to deal with the uncertainty of wind and photovoltaic power generation.And the corresponding mathematical models are established to study the working principle of the battery and supercapacitor as well as the advantages and disadvantages of each.According to their different characteristics,the respective mathematical models are established.Based on the characteristics of energy-based energy storage devices and powerbased energy storage devices,the two are mixed,and the connection between them is determined and the characteristics of the hybrid energy storage system are further analyzed,which provides a strong basis for establishing the objective function in the subsequent chapters.Secondly,the hybrid energy storage capacity optimization configuration problem is a multi-objective,multi-constrained,multivariable nonlinear optimization problem,and the particle swarm algorithm has received wide attention for its superiority.In order to further improve the convergence and diversity of the multi-objective particle swarm optimization algorithm,a multi-objective particle swarm optimization algorithm with multi-strategy improvement is proposed.A heterogeneous update model with elite particle leaders is established and individual learning enhancement factor terms are set to motivate the population to quickly find the true Pareto optimal solution.An external file redundancy mechanism is introduced to enhance the solution diversity by using its variation and interference strategy on the population to avoid the occurrence of premature algorithm.Through test cases,the results show that the proposed algorithm exhibits better convergence and diversity compared with several other optimization algorithms.Finally,for the multi-objective hybrid energy storage capacity optimization allocation problem in distribution networks,from the perspective of improving the stability and economy of active distribution networks,the mathematical model is established with the minimum annual average life-cycle cost of energy storage and the minimum network loss cost,and the multi-objective hybrid energy storage capacity optimization allocation model is combined with voltage stability indexes,and the improved multi-objective particle swarm algorithm(Multi-Objective The model is solved using the improved Multi-Objective Particle Swarm Optimization(MOPSO)algorithm to optimize the hybrid energy storage capacity allocation scheme.The simulation results show that the configuration model and method can improve the voltage stability and reduce the network loss cost of the distribution network,and the improved algorithm has good practicality and convergence.