Risk-driven optimal scheduling of renewable-oriented energy hub under demand response program and energy storages: A novel Entropic value-at-risk modeling

Abstract

Energy hubs have revolutionized the field of energy management, emerging as state-of-the-art solutions for achieving efficient and sustainable energy systems. These hubs act as integrated platforms that seamlessly combine a variety of energy technologies, facilitating the synergistic interaction of multi-carrier energy systems with diverse energy sources. This paper outlines a framework for an energy hub that integrates a wide range of energy technologies, encompassing electrical, thermal, and cooling systems, alongside renewable resources and storage units. The proposed model incorporates demand response programs (DRPs) to effectively manage energy demand, optimize load distribution, enhance grid stability, and achieve substantial cost reductions. The effectiveness of the proposed framework is demonstrated through careful analysis of four distinct case studies, giving its potential in diverse energy management scenarios. To tackle uncertainties associated with power, heating, and cooling demands, as well as power and gas market prices, wind speed, and solar irradiation, this study utilizes EVaR as a stochastic modeling approach. The EVaR is a novel coherent risk measure incorporated to enhance risk management practices and surpass the limitations of traditional value-at-risk measures. According to the obtained results, due to the conservativeness of the operator, the income has decreased by 23 % while the system operation cost has increased by 36 % in the presence of the EVaR optimization approach.