Research On Household Energy Efficiency Optimization Based On Electricity Market

With the continuous access of various intermittent renewable energy sources,such as wind and solar energy,it has a profound impact on the existing grid structure and power supply mode.The household energy management extended by smart grid has gradually become a hot topic in academia.However,nowadays the main focus is on the household electricity information collection and power consumption control,while few involves in the optimal control strategy of household energy efficiency.This thesis studies the household energy efficiency optimization based on electricity market.Under the time-of-use pricing policy,this thesis formulates the intelligent electricity consumption strategies of controllable household appliances.The purposes of electricity charges minimization,energy saving and consumption reduction,as well as staggering electricity usage are achieved.A joint optimization control strategy based on genetic algorithm for electric vehicle load group is proposed,which can effectively reduce the charging fees on electric vehicle and improve the economy of household energy efficiency.The household electric appliances are divided into four categories and the load models are established,including uncontrollable appliances without storage,controllable appliances without storage,controllable appliances with direct storage consisting of household wind generation system and storage battery,as well as controllable appliances with indirect storage such as HVAC.Considering the residents' electricity consumption habits and comfort degree as well as TOU pricing,the mathematical model for the optimal control strategy of household energy efficiency are built up.Genetic Algorithm,Local Particle Swarm Optimization,Linear Decreasing inertia Weight global Particle Swarm Optimization and Simulated Annealing Particle Swarm Optimization,are applied to the model though simulated tests and data analysis.According to the simulation results,three optimal control strategies are formulated,which are ‘Electricity Charges Minimization Strategy',‘Energy Saving and Consumption Reduction Strategy' and ‘Staggering Electricity Usage Strategy'.Residents can choose different strategies based on individualized electricity demand,give priority to corresponding optimization algorithms,and adopt dayparting household intelligent electricity consumption schemes accordingly.By comparing the iteration curves of algorithms,the performance of their application in this research is analyzed.By comprehensively evaluating the optimized effect,global search ability and convergence speed,it is concluded that SAPSO and GA have the optimal comprehensive effect and strong adaptability for different household appliances and electricity demand,which can be applied to related research field.Aiming at the wind abandonment phenomenon in China,this thesis studies the household energy efficiency optimization considering Electric Vehicle under the electricity market mechanism,and proposes a joint optimization control strategy of EV load group based on GA.Through comprehensive regulation of wind power absorption as well as peak shaving and valley filling,not only coordinated dispatching optimization with wind generation and coordinated interactive development with power grid are realized,but also the charging fees on EVs are reduced,which can improve the economy of household energy efficiency.The applicability of GA and SAPSO is explored in this model and the result shows that the former one is significantly superior to the latter one in the optimization effect of the high-dimensional problem.