Two-layer optimization of dynamic energy flow in integrated energy system considering average overlimit ratio of state variable
The optimal dynamic energy flow of integrated energy system(IES)can minimize system opera-ting costs.Aiming at the phenomenon of state variables exceeding limit in the optimization process of IES energy flow,the average overlimit ratio of state variable is introduced to describe the overlimit degree of state variables uniformly,and the multi-objective dynamic time-series energy flow model of electricity-gas-thermal IES,which takes the average overlimit ratio of state variables into account,is established to solve the problem that the optimization results deviate from the feasible optimal solutions due to improper selec-tion of the penalty cost coefficient of state variable overlimit.In order to prevent the optimization of ener-gy flow by honey badger algorithm(HBA)from falling into local minimum,a two-layer optimization model of dynamic energy flow based on multi-objective differential evolution(MODE)algorithm is established.The upper steady-state energy flow model takes the IES operating cost and the average overlimit ratio of state variables of as optimization objectives and adopts the MODE algorithm to solve the Pareto non-dominated solution set in the global space.The lower dynamic energy flow model takes the weighted sum of the IES operating cost and the average overlimit penalty cost of state variables as the optimization objective,gene-rates the initial population decision quantity of HBA based on Pareto solution set,and speeds up the solu-tion of IES global optimal dynamic energy flow by HBA.The effectiveness of the proposed model and opti-mization method is verified by numerical simulation.
integrated energy systemaverage overlimit ratio of state variabledynamic energy flowtwo-layer optimization modelhoney badger algorithmmulti-objective differential evolution algorithm
万方数据
维普
