Stochastic optimal operation of a microgrid based on energy hub including a solar-powered compressed air energy storage system and an ice storage conditioner

Abstract

Energy Hub (EH) is known as a complex system capable of transferring, conversion, and saving various energies in a Microgrid (MG). An important issue for investors is taking advantage of EH for optimal management of all energy carriers, particularly in anticipating energy price. In this paper, a model for EH was considered for the purpose of the optimal operation of the MG with multiple energy carrier infrastructures for day-ahead. The goal of optimization was to minimize operation and environmental costs subjected to numerous technical constraints. The proposed EH manages dispatchable generation, i.e. Combined Cooling, Heat and Power (CCHP) and non-dispatchable generations, i.e., Wind Turbine (WT) and Photovoltaic (PV). It considers an Ice Storage Conditioner (ISC) as well as a Thermal Energy Storage System (TESS) as the Energy Storage System (ESS). In particular, the effects of Solar-Powered Compressed Air Energy Storage (SPCAES) as a novel ESS were studied on the performance and efficiency of the EH operation and environmental costs. The suggested model considers the stochastic behavior of WT and PV generations as well as the electrical, thermal, and cooling demands in various scenarios. The scenario generation was performed while the K-means clustering algorithm was applied for reducing the number of scenarios. The proposed model was a Mix Integer Linear Problem (MILP), which was solved using CPLEX solver in GAMS software. Implementation of the proposed framework on the typical EH showed the efficacy of the ESSs to reduce the operation costs and emissions in the day-ahead energy management.