A fuzzy cloud theory-based stochastic model for multi-carrier energy hubs in grid-connected and islanded operations

The energy hub (EH), which is a crucial component of multi-energy systems, plays a significant role in increasing flexibility and reliability. Due to the interaction of various energies, the unpredictability of renewable energy sources, energy prices, and consumer demands, the optimal operation of EHs presents a considerable challenge for operators. In this study, networked EH takes in a variety of energy sources, including electricity, gas, and wind, and after conversion, storage, direct connection, or shifting of demands, it supplies the hub’s essential demands. In a predictable and stochastic environment, the EH is operated optimally based on an objective function that takes into account economic, greenhouse gas emission, and reliability parameters. An intelligent strategy based on fuzzy cloud theory is utilized to develop an entropy–entropy concept for its work in order to reflect the impact of uncertainties in the challenge. In both grid-connected and island-based operations, the cost of operating networked EHs is modeled as a MILP optimization problem with demand response programs and reliability restrictions. Finally, the effectiveness of various modes in enhancing the reliability and flexibility of energy systems in accordance with the optimal schedule for EHs is proven by modeling the suggested scheme on a sample test system.