Optimal Scheduling of CCHP With Distributed Energy Resources Based on Water Cycle Algorithm

In this paper, we deal with the optimal scheduling of a combined cooling, heating, and power (CCHP) system driven by distributed energy resources. First, a multi-objective optimization model is established based on three performance indexes, i.e., energy efficiency, economy, and environment. Then, we propose an optimal scheduling method based on the water cycle algorithm (WCA) and fuzzy mathematics optimization theory, which addresses the limitations in many traditional optimization algorithms such as local optimization, multiple iterations, and slow convergence speed. Moreover, aimed at showing the effectiveness of the proposed method, a case study has been carried out and the results show that the proposed method has better convergence performance, faster calculation, and higher precision compared with other algorithms such as genetic algorithm (GA), and particle swarm optimization (PSO), and the multi-objective model can reflect the operating state of the distributed energy resources CCHP system accurately.