Multi-Objective Energy Scheduling with Fuzzy Logic-Based Weight Tuning for Disaster Relief

Power supply after disasters is crucial for supporting relief efforts, healthcare, transportation, communications, and other essential services. Due to its high scalability and flexibility, microgrid has gradually become a popular solution for post-disaster power supply. However, the complex and dynamic environment and user demands in disaster areas present significant challenges for microgrid energy management. This paper presents a multi-objective energy scheduling model with fuzzy logic-based weight tuning for disaster relief microgrid. Firstly, a constrained multi-objective optimization problem for disaster area microgrid is formulated as a single-objective problem through weighted aggregation. Then, a fuzzy logic-based weight tuning method is designed to adaptively adjust the weight coefficients of different objectives to change their priorities based on environment and user demand inputs. Moreover, several performance metrics are implemented to evaluate the scheduling results from various perspectives. In order to verify the proposed strategy's performance, a disaster area microgrid scenario is established for case studies. The results indicate that the proposed method offers high flexibility to make it suitable for complex post-disaster power supply applications of microgrid.