Multi-objective Optimization of Integrated Energy System Based on Weighted Fuzzy Algorithm

Integrated energy system (IES) has shown great potential in reducing carbon emission and improving energy efficiency. This paper presents a multi-objective optimization method for park-level integrated energy system (PIES). Firstly, the energy flow balance equation of the system is constructed based on energy hub. Further, taking carbon emission and energy cost as optimization objectives, the multi-objective weighted fuzzy programming method is used to optimize the system, and the Pareto frontier is obtained. Finally, numerical simulation is carried in three different scenarios and the optimal scheduling results are analyzed to further reveal the coupling operation mechanism. Results indicate that the proposed multi-objective optimal scheduling model can provide different dispatch strategies for decision-makers to satisfy different needs and coordinate the contraction between economy and environment.