The Distribution Network Planning With Distributed Generation Based On Quantum Particle Swarm Optimization Algorithm

In recent years, the world happened a few times big blackouts, including the power system accidents of2008snowstorms, which fully exposes the mode of single centralized power supply is vulnerability. The development of distributed power generation technology provides an important supplement for the centralized power supply way, the combination of them is to save investment, reduce energy consumption and main way of improving power system stability and flexibility, also is an important developing direction of future energy field. However distributed power supply for power grid to provide energy supplement and the voltage support at the same time,it also will impact the tide distribution, power quality, relay protection and so on, so reasonable planning of distributed power distribution network is very important.According to principles and content of the distribution network planning, This article mainly studied how to optimize the location and capacity of the distribution power when them access to distribution network. The first, describes the various types of distributed power supply technology, and mainly introduced the blower, photovoltaic cells and small hydropower of the three output model of distributed power; The second, introduced the influence of distribution network system which access to distributed power, including the power flow calculation, power quality, the relay protection system, the system reliability and power distribution planning, etc. The third, introduced the quantum particle swarm optimization algorithm, Using three non-linear test function with constraints to prove the feasibility and effectiveness of the QPSO algorithm; Finally, aimed at containing distributed power distribution network planning, to establish the minimum objective function of active network loss and DG operation cost, with voltage, current and DG capacity limits as constraint conditions, using the penalty function method to convert the constraint and to join the objective function to form the comprehensive objective function, using IEEE14node as the region’s simulation test system, using the quantum particle swarm optimization algorithm to optimize the configuration of the distributed power, and comparing with the basic particle swarm optimization algorithm, the simulation results verify the proposed algorithm has better global optimal ability and faster convergence speed; According to the distribution network planning of a given area actual situation, using the quantum particle swarm optimization algorithm to solve the optimal location and capacity of distribution network which with three kinds of distributed power, before and after using the DG access to distribution network system, with the node voltage and the network loss change to show that it is important to select reasonable DG location and capacity, provide reference value for the region’s power distribution system planning.