Optimal and stochastic performance of an energy hub-based microgrid consisting of a solar-powered compressed-air energy storage system and cooling storage system by modified grasshopper optimization algorithm

摘要

Simultaneous operation of different energy generation and transmission infrastructures is a subject that has been considered under the concept of energy hub. This subject is highly regarded in the field of microgrids. One of the basic issues for investors is to properly utilize the energy hub for optimally managing energy carriers, especially in the energy price prediction. In the present paper, a new strategy is introduced for the energy hub in order to achieve the optimal performance of a microgrid (MG) that includes different energy carriers for each day. The objective of this strategy is to minimize the operation cost and consider the environmental issues. The proposed energy hub consists of a combined cooling-heating-power (CCHP) system along with a wind turbine and photovoltaic cells. The studied energy hub system is composed of an ice storage conditioner (ISC) system and an energy storage system (ESS) as the energy storage resource (ESR). One of the goals of the present work is to investigate the effect of solar-powered compressed-air energy storage (SPCAES) on the per-formance of the energy hub. The proposed strategy takes into account the uncertainty of the energy resources such as the wind and sun for meeting the electric, thermal, and cooling needs in different scenarios. In the present paper, to produce various scenarios, the Latin hypercube sampling (LHS) method is used. Also, the k-means method is used to reduce the number of scenarios. The objective function is solved using the modified grasshopper optimization algorithm (MGOA). According to the modeling results, the ESS can exhibit successful performance in the energy management strategy. (c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.