Site Selection And Capacity Determination Of Distributed Power Generation Based On Whale Particle Swarm Hybrid Algorithm

With the widespread use of renewable energy,a wide range of Distributed Generation(DG)sources are being incorporated into the distributed electricity network.This has an impact on currents,network losses,node voltages and reliability in the distribution network.How to apply distributed generation and how to choose the right location and capacity to optimize the operation of the distribution network is an important issue to be studied and solved.Therefore,this paper researches and analyses the rationalization of the application of distributed power supply access location and capacity for distribution networks,establishes a multi-objective optimization model that integrates reliability and economy,and proposes a method for DG siting and capacity setting using a whale particle swarm hybrid algorithm.The thesis accomplishes the following research:(1)The DGs are equated into four node types,analyze how to deal with the node problem in DG-containing distribution network tide calculation and detail the calculation process using the forward back generation method.The IEEE 33-node distribution system is used as an example to verify the effectiveness and feasibility of the forward generation method in the calculation of DG-containing distribution network currents.The impact of different node types,different access locations and different access capacities on the voltage level and network loss of the distribution network is analyzed and the law is summarized.The simulation results show that reasonable planning of DG access location and capacity in the distribution network can effectively reduce network losses and voltage drop.(2)This paper considers the constraints of tidal current,node voltage and total DG access capacity,and sets up a restriction area for the total DG access capacity and node voltage of the distribution network when the DG access location and capacity are unknown,and constructs a DG siting and capacity setting objective function with the minimum network loss,voltage deviation and comprehensive cost of DG investment.Using the hierarchical analysis method,the respective weights of the three objectives are calculated according to their relative importance,and a total objective function with the optimal coordination of the three objectives is established.(3)To address the limitations of the traditional particle swarm algorithm and the whale algorithm,this paper improves the hybrid optimization of the particle swarm algorithm and the whale algorithm in three directions,namely,enhancing the search capability,avoiding falling into local optimum and fixing infeasible solutions,respectively,and names the improved whale particle swarm hybrid algorithm as(WOAPSO).Simulation analysis of the whale particle swarm hybrid algorithm is carried out using three types of typical test functions to verify that the proposed algorithm has high convergence speed and convergence accuracy.The study applies the whale particle swarm hybrid algorithm to the siting and capacity determination of distributed power sources,and takes the IEEE 33-node distribution system as an example,and solves the access schemes of two DGs,PV and wind power,using the particle swarm algorithm,the whale algorithm and the whale particle swarm hybrid algorithm respectively,and compares the planning results,showing that the planning results using the whale particle swarm hybrid algorithm are more reasonable and can bring considerable economic benefits and improve the operational reliability of the distribution network.