Planning Research On Locating And Sizing Of Distributed Generation Based On Improved Simulated Annealing Particle Swarm Optimization

In recent years, with the progress of electric power technology and the sustainable development of power industry, Distributed Generation(DG) has been widely studied and applied. When DG is accessed to grid, it can save investment, reduce energy consumption and improve the reliability of power system. However, switching the large-scale DG to the distribution network brings more uncertainties to the distribution network planning and power system load forecasting. Meanwhile, the location and capacity of DG can influence power losses, power quality and power system protection. In order to ensure safe and reliable operation of power system, it is necessary to make reasonable planning on locating and sizing of DG.On the analysis of the deficiencies of some commonly-used algorithms and planning model, this dissertation puts forward the Improved Simulated Annealing Particle Swarm Optimization(ISAPSO) algorithm to plan on locating and sizing of DG. The main contents of this paper are as follows.(1) To aim at the fact that the Particle Swarm Optimization(PSO) algorithm is easy to fall into the local minimum and has slow convergence speed in the late, the paper improves the algorithm as follows. The Simulated Annealing(SA) algorithm is combined with the PSO algorithm to form Simulated Annealing Particle Swarm Optimization(SAPSO) algorithm. The crossover operation and mutation operation of genetic algorithm are introduced to improve SAPSO algorithm and form the ISAPSO algorithm. The algorithm improves the diversity of the population so that it can jump out of local optimum effectively. Through the simulation analysis of the classical test function, the ISAPSO algorithm has a higher convergence precision than PSO algorithm and SAPSO algorithm, as well as the optimization effect is obviously enhanced.(2) ISAPSO algorithm is uses for planning research on locating and sizing of DG. Firstly, different DGs can be equivalent to different kinds of node types. The back or forward sweep method is putting forward to calculate power flow. Aiming at the PV node, the reactive power compensation device is used for power correction, and the reactive power allocation principle is adopted to determine the initial value. Then, in the case of uncertainty of the number of DG, the location and the single DG’s capacity, the mathematical model of the minimum economic cost for locating and sizing of DG is established. The objective function of this model includes the investment and operating costs of DG, the network loss cost, the annual purchase electricity costs and the environmental pollution costs. And the constraints of power flow, bus voltage, conductor current and DG capacity are considered in the model. In the end, ISAPSO algorithm is adopted to achieve the planning research on locating and sizing of DG.(3) The simulation results from IEEE33 node distribution network show that the ISAPSO algorithm can solve the planning on locating and sizing of DG effectively, and obtain a higher economic efficiency of the planning program than ISAPSO algorithm and PSO algorithm. In addition, Grid-connected DG improves the system voltage level, and makes the power system operation more economical, safer and more reliable.