Research On Reactive Power Optimization Of Power System Based On Improved Particle Swarm Algorithm

In order to facilitate the implementation of the implementation of policies in the energy sector issued by the national “Thirteenth Five-Year Plan” outline,we will closely follow socio-economic production and scientific innovation,and strictly follow the concepts and guiding ideology of green,environmental protection and sustainable development in energy.Especially in terms of electricity,it is necessary to accelerate the pace of continuous improvement of power supply security and high quality of the power system.For the level of power quality,there are many indicators to measure,in which the voltage indicator is in the position of the world.At present,reactive power regulation is the main mode of voltage regulation,but insufficient or excess reactive power will affect the safety of power systems and equipment.This will not only result in economic waste,but also lead to dangerous accidents.Therefore,reasonable optimization of reactive power is a very necessary measure,and it can also effectively reduce the system active power loss.However,as the scale of power systems becomes more and more complex,traditional optimization methods have gradually exposed its drawbacks and are increasingly unable to meet the needs of modern networks.Taking into account the characteristics of reactive power compensation in situ,the paper introduces synergies.Based on the evolutionary thinking,a collaborative particle swarm optimization algorithm is proposed to solve the power system reactive power optimization problem.Collaborative Particle Swarm Optimization(PSO)algorithm is mainly based on the synergy between populations and populations,populations and environment in nature.According to the decomposition-coordination idea,the power system optimization problem is decomposed into a series of interacting subsystems.Each subsystem is integrated into this system.The idea of improving the parameters of the standard particle swarm algorithm,through the mutual cooperation,cooperation,and common evolution among subsystems,completes the evolution of the system as a whole,and finally obtains the solution to the optimization problem.This method is suitable for solving large-scale reactive power optimization problems in power systems and has a strong practical value.The main work of the thesis is as follows:(1)Constructed reactive power optimization model based on collaborative particle swarm optimization algorithm(2)The collaborative particle swarm optimization algorithm is constructed and the key links of the reactive power optimization problem are designed accordingly.(3)The simulation experiments were performed to verify the superiority of the constructed collaborative PSO algorithm in dealing with reactive power optimization problems.