Study On Multi-objective Security-constrained Unit Commitment With Wind Power And EVs

Due to the fossil-fuel crisis and environment pollution,improving energy efficiency and protecting environment have become the focus of the world.In China,in order to achieve the goal of energy-saving and emission-reduction,the power industries have taken specific initiatives to develop all kinds of renewable energy resources at the generation side making low carbon transition,and promote the use of a variety of environmentally energy load at the demand side.These measures prompt the fast development of large scale wind farms and electric vehicles.Meanwhile,smart grid construction continues to improve,and smart meters and advanced measurement system are used more and more widely.It makes power system monitor the user's electricity situation,and control electricity demand effectively.The above all provide strong hardware foundation for electric vehicles to participate in power system scheduling.Therefore,it is a good solution to establish an multi-objective security-constrained unit commitment model by combining the traditional unit commitment,distributed renewable energy and electric vehicle.It can not only optimize the energy consumption structure and energy use,promote energy conservation,but also improve energy efficiency,and economic sustainable development.This thesis analyzes the characteristics of traditional unit commitment model systematically,describes the method of dealing with the uncertainty of wind power in detail,and expatiates the modeling principle of electric vehicle charging and discharging behavior simply.And on this basis,the methods of large-scale of electric vehicles connected to the power system are studied.These researches provide a solution to cope with the challenges of wind power output randomness and the large-scale electric vehicle access.For the uncertainty of wind power and randomness of electric vehicles,an multi-objective security-constrained unit commitment strategy that based on the fuzzy chance-constrained program is proposed.The objective consists of the lowest operating cost and pollution emission.And the constraints includes power balance and spinning reserve etc.Fuzzy chance-constrained program is used to deal with the wind power forecasting errors.And electric vehicles integrate the grid with vehicle-to-grid(V2G)operation.The proposed strategy could realize connect the renewable source to smart grid optimally,and reduce operating cost as much as possible.Considering the economical operation of smart grid and the user satisfaction,an multi-objective security-constrained unit commitment strategy based on distributed control of electric vehicles is presented.The virtual price is obtained according to load characters and wind power.And then charging and discharging plan is given for electric vehicles.By combining the above charge and discharge plan,wind power and unit commitment establishes an multi-objective security-constrained unit commitment model.The objective of this model consists of the lowest operating cost,sulfur dioxide and carbon dioxide emission.And then multi-object could be described as single object problem using analytic hierarchy process.This model verifies that the optimization strategy can achieve the stabilization of wind power fluctuations,improve the efficiency of wind power utilization,reduce the frequency adjustment of the unit,and then achieve better economic and environmental benefits.