A Research Of Energy Optimal Scheduling Algorithm For Microgrids Based On Game Theory

Environment pollution and energy shortage pose a threat to sound environment of human society.Nowadays,energy saving and low carbon economy have become trends of global economic development.In the current period of the new information technology that is in full swing,microgrid,as the crossing field of new information technology and electric power grid,is widely regarded as the new industry of board market prospects and advanced technology industries.The development of microgrid theory and technology is helpful to promote the rapid growth of information technology and electric field in the aspect of theory,technology,industry,etc.This thesis mainly studies problems of energy consumption scheduling,demand response management and energy trading in the microgrid.In view of the existing disadvantages of energy optimal scheduling methods in the microgrid,considering multiple energy resources of electricity,gas,heat energy and cold energy and so on into the microgrid model,we formulate a new energy optimization scheduling model based on a variety of game theoretic approaches including non-cooperative game,Stackelberg game,two-layer game,etc.The main contribution of the thesis are as follows:Firstly,a household electricity consumption scheduling model in the residential microgrid is formulated based on non-cooperative game.Household users within a residential microgrid schedule adjustable electricity loads to reduce their electricity consumption costs.We present the proof of Nash equilibrium in the proposed game model and an electricity consumption scheduling algorithm for reaching the equilibrium.Simulation results show that the proposed game approach can household users' about 41% electricity consumption costs.Secondly,on the basis of the electricity consumption scheduling model,taking account of the energy resource of gas into the microgrid model,a dual energy consumption scheduling model in the energy interconnected microgrid including two energy resources of electricity and gas is formulated based on non-cooperative game.Users within the energy interconnected microgrid schedule electricity and gas usages to minimize their total energy costs.We prove the uniqueness of Nash equilibrium in the proposed game model,and present a dual energy consumption scheduling algorithm for reaching the equilibrium.Simulation results show that the proposed game approach can reduce about 43% electricity and 40% gas consumption costs of users.Thirdly,based on the electricity consumption scheduling and the dual energy consumption scheduling model,think of the energy resource of cold energy and heat energy into the microgrid model,a multi-energy demand response management model in the residential smart microgrid including four energy resources of electricity,gas,cold energy and heat energy is formulated using Stackelberg game.An energy provider,as a leader,adjusts energy prices,and residential smart energy hubs,as followers,schedule energy consumptions according to the prices.We prove the uniqueness of Stackelberg equilibrium in the proposed game model,and present a demand response management algorithm for reaching the equilibrium are presented.Simulation results show that the proposed game approach can effectively improve the utilization efficiency of multiple energy resources as well as energy revenues of the energy provider,and reduce the energy consumption costs of users.Fourthly,on the basis of the electricity consumption scheduling,the dual energy consumption scheduling and multi-energy demand response management model within the microgrid,considering the energy trading among microgrids in the microgrid model,a multi-energy trading model in the industrial microgrid is formulated based on two-layer game.Game in the first layer is proposed to be a non-cooperative game within an industrial microgrid.Industrial users schedule their energy consumption for reducing their energy consumption costs.In the second layer,Stackelberg game is used for multi-energy trading among industrial microgrids.Industrial microgrids energy buyers or sellers adjust the energy trading strategies to improve their utilities.We present the proof of Nash equilibrium in the game model within a microgrid as well as Stackelberg equilibrium in the game model among microgrids,and an energy consumption scheduling algorithm for reaching Nash equilibrium as well as a multi-energy trading algorithm for reaching Stackelberg equilibrium.Simulation results show that the proposed game approach can effectively reduce energy consumption costs of users,and improve utilities of industrial microgrids participating in multi-energy trading as well as the utilization rates of renewable energy resources.Finally,the studies on energy optimization scheduling in the microgrid are summarized,and future work on related studies is also given.