Optimal Configuration and Economic Analysis of Wind-Solar-Storage Resources in Multi-Park Hybrid Microgrids Based on Hybrid Intelligent Algorithms
Abstract
To solve the problems of low renewable energy utilization and high grid dependence in multi-park hybrid microgrids (MPHMs), this paper aims to develop a centralized optimization framework for the wind-solar-storage resource configuration to realize the coordinated operation of new energy suppliers, integrated energy service providers and end-users. An multi-objective economic dispatch model considering source-storage-load-grid coordination, time-of-use pricing and demand response incentive, as well as technical constraints of energy storage is established. An improved hybrid intelligent algorithm combining NSGA-III with enhanced solution selection based on clustering is designed to efficiently solve the optimization problem and obtain practical configurations. The proposed method is applied to a system including industrial, commercial and residential parks with different loads and renewable generation capacity. Simulation results indicate that the optimal energy storage configuration can eliminate the renewable curtailment in all parks and reduce both daily electricity purchasing cost from main grid and total daily power supply cost. These results demonstrate that coordinated planning can improve both sustainability and economy of MPHMs. Sensitivity analyses validate that the solution is robust to the variations of storage cost, incentive policy and renewable generation capacity. The proposed method performs better than non-storage scenario even in unfavorable cost conditions. The proposed scalable and practical method provides a valuable reference for optimizing multi-area microgrids and integrated energy systems.