Open AccessRobust stochastic optimal operation of an industrial building including plug in electric vehicle, solar‐powered compressed air energy storage and ice storage conditioner: A case study in the city of Kaveh, Iran
Author(s) -
Doosti Reza,
Sedighizadeh Mostafa,
Sedighizadeh Davoud,
Sheikhi Fini Alireza
Publication year - 2022
Publication title -
iet smart cities
Language(s) - English
Resource type - Journals
ISSN - 2631-7680
DOI - 10.1049/smc2.12025
Subject(s) - thermal energy storage , energy storage , photovoltaic system , solver , automotive engineering , air conditioning , process engineering , computer science , environmental science , engineering , power (physics) , electrical engineering , mechanical engineering , ecology , physics , quantum mechanics , biology , programming language
Abstract An optimal day‐ahead operation of a microgrid (MG) based on an energy hub (EH) that is an industrial building, is presented in this paper. The proposed EH includes wind turbine (WT), photovoltaic (PV), triple generation that is combined cooling, heat and power, and salt water desalination. The purpose of solving problem is to lessen the operational and pollution costs limited to several technical restrictions. The EH takes into account plug in electric vehicle (PEV) and an ice storage conditioner (ISC) and together with a thermal energy storage system that is a supplementary energy storage system (ESS). Particularly, the performance and efficacy of the EH operational and pollution costs are studied by considering a solar‐‐powered compressed air energy storage (SPCAES) that is a novel rechargeable and developing ESS. The proposed model takes into account the uncertain behaviour of PV and WT generations together with the thermal, electrical, and cooling demands, which deal with a robust optimisation approach. The suggested robust mix integer linear problem model is figured out using the CPLEX solver in general algebraic modelling system software. The proposed framework is implemented on the industrial building located in the industrial city of Kaveh, Iran. The simulation results show that using ESSs including SPCAES, ISC, and PEVs reduce the total costs (operation and emission costs) by 2.42% in the day‐ahead energy management.