Day-ahead Optimization Of Electric-gas-hot-water Integrated Energy System With Flexible Resources And Demand Response

The joint optimization of regional integrated energy system is not only limited to electricity,heat,cold,gas,etc.,but also needs to connect hydropower cogeneration units with power systems to better promote energy conservation and emission reduction.Demand response technology can realize bidirectional interaction between power generation side and load side,and further improve energy efficiency.At the same time,as a new controllable load,electric vehicles interact with the power system through charging and discharging.Users can also adjust the demand for different energy sources to achieve the same effect of peak shaving and valley filling and cost saving.Therefore,this paper studies the day-ahead scheduling scheme with the participation of flexible resources such as orderly charging and discharging of electric vehicles,energy storage devices and the comprehensive demand response of electric hot water.The main work is as follows :Firstly,the operation characteristics of each energy consumption unit in the regional electrical and thermal integrated energy system,including water load,are analyzed,and the optimization model of regional electrical and thermal integrated energy system is established.The optimization model of regional electric hot water integrated energy system is solved by particle swarm optimization.The optimization results of regional electricity-gas-heat-water integrated energy system are compared with those of regional electricity-gas-heat integrated energy system,which verifies the optimization rationality of water load operation in integrated energy system.Secondly,according to the schedulable value of electric,gas,heat and water loads,combined with the influence of demand response,the optimal scheduling model of electric hot water integrated energy system considering demand response is established with the optimal operation cost of the system as the goal.The optimization model is solved by particle swarm optimization.Simulation results show that the model can improve the integrated energy system...