Study On Environmental Economic Dispatch Of EV And PV Access Power System

With large-scale electric vehicles(EV)and photovoltaic(PV)access to the power system,the energy structure of the power system,operation mode and related dispatch methods of the current power system are more complicated.To simultaneously consider environmental protection economic benefit has become a research hotspot in the field of power system optimized dispatch.At present,environmental economic dispatching often rely on multi-objective intelligent algorithm to solve the dispatch model to generate dispatch plan.The multi-objective particle swarm optimization algorithm(MOPSO)is a widely used solving algorithm.However,due to its fast convergence characteristics,it is easy to fall into the local maximum.resulting in unsatisfactory results.This paper studies the environmental economic optimization dispatch problem of electric power system considering electric vehicles and photovoltaic access.With the lowest fuel cost and minimum emission of pollutants as the dispatch target,an environment considering the synergy of electric vehicles,photovoltaics and thermal power generation is established.The economic dispatching model solves the dispatch model by improving the MOPSO algorithm,and obtains the output power of each unit of photovoltaic,electric vehicle and thermal power unit,and formulates a dispatch plan.Firstly,this paper analyzes the problem of optimal dispatch of electric vehicles and photovoltaic access to the power systems,finds out the impacts of the two participating in the dispatching on the power system and the existing shortcomings of the current research.It lays the theoretical foundation for latter power system economical dispatch research.Secondly,the characteristics of electric vehicle and photovoltaic access power system and the characteristics of electric vehicle and photovoltaic power generation are analyzed,and the influence mechanism of each power generation unit on power system dispatching is studied.The minimum fuel cost of the system and the minimum emission of pollutants are the dispatching targets.At the same time,the environmental economic dispatch model of the power system is constructed considering the constraints of vehicle travel demand and power balance.Thirdly,the traditional MOPSO algorithm is easy to fall into local optimum when finding the solution to the dispatch model,which leads to unsatisfactory solution results and affects the economic and environmental protection of dispatch.In this paper,the nonlinear adaptive inertia weight is used to improve the MOPSO algorithm to improve its search ability.At the same time,the crowding distance-based elimination strategy is used to correct the external files and improve the diversity of the solution set.Based on a number of standard test function examples,the practicability and effectiveness of the improved MOPSO and the original algorithm are compared and analyzed.Fourthly,taking the IEEE-30 node model as an example,the photovoltaic power station and load operation data of a certain area in Hebei Province are brought into the environmental economic dispatching model of the power system.The parameter setting and solving steps of the model are given in detail,and the improved MOPSO algorithm is adopted respectively.Using the MOPSO algorithm to find the solution to the model.The MOPSO algorithm improves the fuel cost by 2.50% and the pollution gas emission by 2.57% compared with the MOPSO algorithm.The superiority of the proposed method is verified by different scenarios.