| With the development of economy,science and technology in China,the quality of life and the level of industrialization have been greatly improved.At the same time,the rapid increase of power energy demand will bring great pressure to the operation of power system.Under the pressure of global energy shortage and environmental problem,the development and use of new energy has become the current development direction.Combined with the problems and opportunities faced by the current power system,the distributed generation technology with new energy sources has become a development project supported by our country.Under the background,this paper presents a reactive power optimization model based on Multi-population Genetic Algorithm for distribution network with distributed generation by discussing the effects of distributed generation on voltage levels,harmonics and power flow.Multi-population Genetic Algorithm uses different genetic strategies and information exchange among different independent populations to improve the global searching ability and convergence speed of classical Genetic Algorithm.Finally,the effect of reactive power optimization is further verified by the simulation results of the example.The main work of this paper:Combined with the development of distributed generation technology and the status quo of reactive power optimization in China,this paper discusses the influence of distributed generation on the voltage,harmonic and loss of power system,than clarified the significance of reactive power optimization research for distribution network with distributed generation.The traditional reactive power optimization algorithm has some limitations in dealing with multi-objective problems with discrete variables,and it is difficult to solve the problems with multi-type variables,constraints and multi-objective optimization functions.In view of the characteristics of AI Algorithm in convergence mode,more and more research choose to use AI algorithm to solve the reactive power optimization problem,and obtain better optimization effect.Based on the problems of Genetic Algorithm in the iteration process,premature convergence,slow convergence speed and so on,in this paper a multi-population Genetic Algorithm is proposed,which can co-evolve among independent populations,and the convergence effect is verified by several test functions.Etablished A mathematical model for reactive power optimization of distribution network with distributed generation.Reframed the function which takes the minimum loss of power system as the objective is reconstructed,and used The multi-population Genetic Algorithm proposed in this paper to optimize the model.Finally,through the simulation of IEEE30 bus system,proved that the reactive power optimization based on multi-population Genetic Algorithm can effectively reduce the system power loss,improve the voltage level and avoid premature convergence in the Genetic Algorithm. |
