Optimal Operation Method Of Micro-Energy Network With Cooling,Heating,Electricity And Energy Storage

The micro-energy network can improve the comprehensive utilization rate of energy by realizing the cascade utilization of energy and the nearby consumption of energy.However,the types of energy in the network are diverse,and the coupling relationship is complex.How to optimize the output of equipment in the network,achieve the reasonable allocation of various resources,and find the optimal operation method suitable for the micro-energy network are urgent problems to be solved.Aiming at the problem of unreasonable equipment output distribution in the micro-energy network,this thesis studies the micro-energy network containing cold,hot and electricity and energy storage.The main contents are as follows:(1)The architecture design scheme of the micro-energy network connected with the power grid is established,the energy flow characteristics of the network are analyzed,and the operation characteristics of the main equipment in the network under varying working conditions are summarized.The mathematical models of the equipment including photovoltaic power generation,power grid,electric boiler,electric refrigerator,micro gas turbine and energy storage are established,and the basic scheduling strategy and operation mode of the network are determined.(2)Taking the minimum daily economic operation cost as the goal,the improved particle swarm optimization algorithm based on linear decreasing weight and variable weight compression factor is proposed to solve the daily operation cost of the microenergy network.The improved algorithm was verified to have better convergence effect,and the optimization results of thermal and cold power and the role of energy storage are analyzed.(3)A multi-objective optimization scheduling model including daily operation cost,carbon emission cost and primary energy consumption cost is established.The weight value of each sub-objective is solved by using the improved analytic hierarchy process,and the improved weighted fuzzy satisfaction method is used to blur the sub-objectives.Finally,the multi-objective optimization problem is transformed into a single objective optimization problem for solving.Finally,an example is used to demonstrate that the proposed method can take into account the three aspects of economy,energy saving and emission reduction when solving the multi-objective optimization scheduling model of micro-energy network,and can achieve a relatively ideal effect.