Research on robust optimization of the integrated energy system in industrial parks based on adaptive genetic algorithm

Abstract

Abstract As the core energy supply mode of the future park, the operation strategy will have an enormous impact on the operating cost and energy efficiency of the park. To further enhance the economic and robustness of the park’s integrated energy system (IES), an optimization model for the operation is established based on robust algorithms and adaptive genetic algorithms (GA). The results show that the optimized carbon neutral park’s comprehensive energy system achieves full consumption of renewable energy, and the utilization rate of new energy reaches 100%. Cool storage is used when the energy price is low, on the contrary, cooling is supplied. After considering the consumption indicators of new energy, the improvement of the new energy utilization rate can raise the system’s efficiency.