An Optimized Load Shedding Strategy Using Fuzzy MOORA Ranking
Thai An Nguyen, Tung Giang Tran, Huy Anh Quyen, Van Hien Truong, Thu Hien Huynh Thi · Engineering Technology & Applied Science Research · 2025
Ensuring the stability and reliability of power systems under fault conditions and power imbalances remains a critical challenge in modern electrical networks. Among various mitigation techniques, selective Load Shedding (LS) is recognized as an effective method for restoring the system balance. However, identifying which loads to shed involves complex trade-offs among technical constraints, system priorities, and economic impacts. This paper proposes a novel Multi-Criteria Decision-Making (MCDM) approach based on Fuzzy Multi-Objective Optimization by Ratio Analysis under a Fuzzy Environment (MOORA) to improve the LS strategies. The integration of fuzzy logic enables the method to handle uncertainty and vagueness in real-time operational data, thereby enhancing decision robustness and adaptability. The proposed approach maintains the computational simplicity while ensuring an accurate load ranking based on multiple conflicting criteria. To validate the method, it is applied to a 16-bus microgrid model under various fault scenarios. Simulation results demonstrate that the method enhances system stability, reduces unnecessary economic losses, and improves the precision of load prioritization. These findings indicate that the approach is not only practical and scalable, but also highly suitable for intelligent load management in smart grid applications.