Optimizing Multi-Microgrid Operations: A Compromise Approach Incorporating Loss Considerations and Renewable Energy Uncertainty

Document Type : Research Article

Authors

1 Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran

2 Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran Department of Smart Control Systems, Niroo Research Institute (NRI), Tehran, Iran

Abstract

The significant integration of variable renewable energy sources, along with the uncertainties in their generation, presents a substantial challenge for the distribution system operator. Microgrids, recognized as intelligent grid systems, offer a promising solution for the efficient integration of local renewable energy resources. However, the intermittent nature of renewable energy introduces operational complexities and additional costs associated with maintaining stable performance within the microgrid's energy management system. The presence of multiple microgrids facilitates the creation of a flexible and diversified energy market structure. This paper investigates the impact of losses on microgrid expenses through the analysis of various scenarios. A compromise model objective is proposed, focusing on the minimization of microgrid costs. To address the uncertainties associated with variable renewable energy sources and their impact on system costs, distributed energy resource schedules, and the overall energy market, we propose a new data-driven probabilistic efficient point method. This method calculates the optimal generation from sustainable energy at various risk levels, which can then be integrated into a suggested transactive day-ahead market model. Simulation results confirm that the proposed compromise strategy is feasible, with system cost nearly matching the minimum achievable. Specifically, during peak demand periods, the compromise scenario yields a 3% reduction compared to the actual system cost. Likewise, system losses, which reach their maximum during high-demand intervals, are reduced by 2.5% under the compromise-based solution relative to the actual system. These outcomes confirm the effectiveness of the proposed approach in simultaneously achieving economic efficiency and technical reliability.

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References

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AUT Journal of Modeling and Simulation
Volume 57, Issue 1
June 2025
Pages 73-88

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