The Optimal Strategies For Electric Vehicle Charging With Aiming At Peak Load Shifting

Energy and environment has currently become the most concerned global issues.Energy is the foundation of the economy,and environment is an important factor which constrains economic and social development.Under the circumstances, energy-saving and eco-friendly EV(Electric Vehicles) is in the ascendant. However, The power needed to charge the batteries of EV has the feature of dispersion and randomness. It’s largely accessed to distribution networks will affect the whole system’s safety and stability, such as additional peak load, power loss, voltage stability, power quality, relay protection, power supply reliability and so on.Based on research status at home and abroad, this paper focuses on the optimal strategies for charging EV. Firstly, analyze the model of electric vehicles’power demand.The factors related to the demand on charging power of electric vehicles are analyzed. According to statistical data of internal combustion cars and taking the probability distribution of some enchancement factors, a statistical model of electric vehicles’power demand is built.The mathematical expectation of single electric vehicle’s power demand and its standard deviation are solved by Monte Carlo simulation, after that a method to compute total power demand of many electric vehicles is given.Taking a case study for example, the impacts of power demand of electric vehicles in different scales on original load curves are calculated. Then, analyze the demand side management technology which taking peak load shafting as the core. The action and importance of peak load shafting in reducing network loss is analyzed and it is proved that the more flat the load curve is, the more the network loss reduces based on Cauchy-Schwarz inequality. Finally, develop the optimality strategies and the control system for charging EV. The Composition and theory of control system are analyzed. The optimal strategies are devided into local charging strategy and global charging strategy by the degree of Optimization, and take a case study to verify and compare the effect of the two charging strategies on minimizing peak load and reducing network losses.