Application of an intelligent method for hydrogen-based energy hub in multiple energy markets

Abstract

Use of different energy carriers together, known as an energy hub, has been a hot topic of research. The hub manager manages the energy in the hub and supplies the energy demanded by the consumers. Herein, a multi-carrier energy storage system comprising a thermal energy storage system, ice storage system, and hydrogen storage system is considered for a multi-carrier energy system to exploit their economic benefits. The proposed combined cooling, heating and electricity microgrid not only participates in the electricity, gas and heat market to meet the needs of electricity, heating and cooling, but also can use the new hydrogen power technology used in the hydrogen storage system to increase the efficiency of the whole system participate in the market. In addition, a multi-energy demand response model is used as a new concept of demand response on electrical and thermal loads, which provides more options for multi-energy end users in energy management policies. To cover the uncertainty of the existence of different energy sources in the used model and the price of electricity, a new method has been used. The LHS sampling is used to develop diverse scenarios, and the backward scenario reduction method is adopted to decrease the number of scenarios. To solve the objective function and optimization, the metaheuristic whale algorithm improved by a local search algorithm is utilized. The main goal is to reduce the operation costs of the multi-energy carrier system. The obtained results show that the hydrogen storage utilization and multi-energy demand response can reduce the system operation cost by 6% for the studied experimental system. Furthermore, as the uncertainty budget increased, the total cost of operations increased by 10%. This is because the level of planning conservatism increases with each increase in the uncertainty budget.