Designing Multi-Objective Electric and Thermal Energy Management System of Microgrid in the Presence of Controllable Loads and Electric Vehicles

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Abstract

The global electricity network and natural gas have been developed over a broad geographical area worldwide. So far, various investigations have been performed in relation to energy infrastructures, however the combination of these systems with each other, which has many advantages, has not examined much. For this reason, electric and thermal loads have been interconnected by CHP units, and the combined study of power and heat has helped the operator to propose a more optimal structure for energy management. Therefore, integrating different energy carriers with each other and using the benefits of each one can increase the efficiency and reliability along with optimizing system performance. Such a capability in structure and operation requires a comprehensive framework to describe the effects of combining different energy carriers on the economic and environmental indicators of energy systems. In this paper, the microgrid has been modeled as an energy hub in order to combine different energy carriers and perform conversions in them to provide the optimal electric and thermal load required by the consumer. This structure has been created by managing the incoming carriers of gas, electricity and renewable energy and managing their conversion and storage in order to minimize the cost of energy supply and environmental pollutants. In order to improve the performance of the microgrid and help the operator of the microgrid, in addition to managing generation units, a responsive load management strategy and charging and discharging of electric vehicles have also been proposed. Epsilon constraints and fuzzy decision-making methods have been used to solve this problem. The results indicate that in the optimal state with the application of responsive loads, the total cost of operation is reduced by more than 6% and the cost of environmental pollutants is reduced by about 13%.

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last seen: 2026-05-19T01:45:01.086888+00:00