Multi-objective planning of energy hub on economic aspects and resources with heat and power sources, energizable, electric vehicle and hydrogen storage system due to uncertainties and demand response

Nowadays, microgrids and their optimal exploitation based on energy hubs are particularly important. A microgrid is an energy system that supplies electricity to customers with renewable and fossil generation sources. Therefore, the main goal of this work in optimal planning of energy hubs includes how to distribute products such as combined energy and heat sources, hydrogen storage systems, electric vehicles, and controllable loads to examine the role of demand side management and renewables. This research study also aimed at minimizing the cost of power generation in the following hours or days, as well as the spread of environmental pollution. Since various sources of uncertainty such as load, energy price in the wind turbine, and solar cell output power market affect the microgrid's economic optimization, this research study is covered by probabilistic modeling. The hydrogen storage system includes an electrolyzer, hydrogen tanks, and a fuel cell. We apply the load-side response program to flatten the load diagram and optimize the microgrid use. As this model has different objective functions, a multi-objective random algorithm was proposed to solve it. Finally, the proposed model and method for a sample system in different scenarios are discussed. Based on obtained results from all scenarios, the first case reduced the operating cost by 20.75 % and 15.17 % compared to the second and third cases. Similarly, the rate of environmental pollution has decreased by 7.94 % and 2.23 %.

Automated summary

Currently, microgrids and their optimal use based on energy hubs play a vital role. A microgrid is an energy system that utilizes renewable and fossil generation sources to provide electricity to consumers. The primary objective of this research is to optimize the planning of energy hubs by efficiently distributing products like combined energy and heat sources, hydrogen storage systems, electric vehicles, and controllable loads, considering the importance of demand-side management and renewable energy utilization. The study also focuses on minimizing power generation costs and reducing environmental pollution. Probabilistic modeling is employed due to various sources of uncertainty in the microgrid's economic optimization, such as load, energy price, and solar cell output power. The proposed model includes a hydrogen storage system consisting of an electrolyzer, hydrogen tanks, and a fuel cell. The load-side response program is utilized to flatten the load curve and optimize microgrid usage. A multi-objective random algorithm is proposed to solve this model with different objective functions. The study concludes with the application of the proposed model and method to a sample system under different scenarios, showing significant reductions in operating costs and environmental pollution rates compared to other cases.