Energy Optimization Of Distribution Network With Electric Vehicles And Distributed Energy Resources

With the rapid development of our social economy, the demand for energy continues to rise. Faced with increasingly severe fossil energy crisis and environmental pollution problems, using clean energy instead of fossil fuels will become an inevitable trend of the global energy system. Clean energy can be effectively utilized and developed by distributed energy resources, compared to Traditional fuel cars, electric vehicles have obvious advantages of energy saving and emission reduction. In this context, the energy optimization of distribution network with distributed energy resources and electric vehicles has very important value on theory and engineering.First, user behavior characteristics of electric vehicles and operating principles of different energy (such as solar power system, battery, micro-turbine, fuel cell, wind turbine) are analyzed. Then mathematical models of electric vehicles and different distributed energy systems are constructed in this paper.Second, a clean and renewable resource solar is added to combined cooling heating and power system which can achieve energy cascade utilization. In order to reduce the output randomness of solar power system, a photovoltaic -battery system is designed to smooth the output power. Combined the photovoltaic-battery system and traditional CCHP system, a comprehensive type of cogeneration system is built. Considering the impact of electric vehicles’ charging load, the environmental cost and the Life Cycle Cost are evaluated in following the electric load mode and following the thermal load mode.Last, based on the temporal and spatial characteristics of electric vehicles, the influence on distribution network active power loss and voltage deviation under uncoordinated charging mode and coordinated charging/discharging mode are studied. Considering the operating characteristics, the models of the distributed generations in power flow calculation are presented. Considering the coordinated charging/discharging strategy and 24 hours of a day, the four objective functions which include network loss, the cost of power generation, pollutant treatment cost and comprehensive performance are established. And the improved particle swarm optimization algorithm is used to solve the optimal power flow with electric vehicles and distributed generations. The validity of models and algorithm is verified through calculating the IEEE 33-node example system.