A Risk-Averse Hybrid Approach for Optimal Participation of Power-to-Hydrogen Technology-Based Multi-Energy Microgrid in Multi-Energy Markets

Abstract

Global consensus on energy economic and environmental issues, as well as increasing penetration of renewable resources, has created new challenges for researchers to explore more financial-effective, environment-friendly, reliable, and secure energy systems. To this end, this paper focuses on combined cooling, heating, and power microgrid to alleviate these issues. In this regard, a multi-carrier energy storage system composed of thermal storage system, ice storage system, and hydrogen storage system are integrated into the proposed system to benefit from their techno-economic advantages. The proposed combined cooling, heating, and power microgrid not only participates in power, gas, and thermal market to supply power, thermal, and cooling demands but also can participate in the hydrogen market using a novel power-to-hydrogen technology utilized in the hydrogen storage system to increase the entire system efficiency. Moreover, a multi-energy demand response model is applied as a new concept of demand response on both electrical and thermal loads, which provides more options for multi-energy end-users in energy management policies. Additionally, a novel hybrid robust-stochastic approach is proposed to deal with the uncertainty of wind speed and electricity price fluctuations, which enables the operator to use the advantages of both scenario-based stochastic and robust optimization methods simultaneously to handle such uncertainties. The scenario-based stochastic technique is used to handle the uncertainty of wind speed while the robust optimization method is also considered to manage the uncertainty associated with electricity price in a conservative environment. The main objective of the proposed model is to minimize the operation cost of multi-energy microgrid, which is formulated as a mixed-integer linear programming problem. Finally, to verify the effectiveness of the proposed methodology, a case study and numerical results are provided. Obtained results shows that utilizing hydrogen storage and multi-energy demand response can reduce the system operation cost up to 5% for the studied test system.