Natural disasters, such as earthquakes, typhoons and floodings, can have a catastrophic impact on the human society. Under such situations, effective and timely power supply is critical for supporting emergency response, medical services, communications, transportation, and other essential services. Microgrid technology can quickly incorporate distributed energy resources to provide local power supply in an islanding mode without reliance on the main grid, making it a promising solution for rapid power restoration after disasters. However, disaster environments are often highly dynamic and complex. The golden 72 hours rescue period and rapidly changing environmental conditions make microgrid energy management a highly time-sensitive task. One of the key challenges is how to properly adapt the objective functions under different operating conditions in this time-sensitive microgrid energy management to achieve timely responses.
To address this challenge, we have been developing an adaptive objective function system for disaster relief microgrids. An objective function library is first established, consisting of various built-in objective functions designed for different disaster relief scenarios. Based on the changing information collected and analyzed from the external environment in the situation awareness, a fuzzy logic system, incorporating human expert knowledge as fuzzy rules, can automatically assign different objective functions with adaptive weight values to represent their relative priorities. Multiple objective functions with the highest priorities are dynamically selected from this library to reflect the most updated disaster site conditions. These selected objective functions are then aggregated linearly into a single-objective optimization form using the determined weights.
We have integrated the objective function library, adaptive weight tuning system, and other energy management functional modules into an EMS research and development fast prototyping platform for disaster relief. This platform enables flexible and convenient configuration of microgrid prototypes for case analysis and proof-of-concept validation in a modular manner. Case studies have demonstrated the effectiveness of the proposed methodology in enhancing the adaptability of the microgrid energy management, making it well-suited for time-sensitive applications such as disaster relief.
Publications:
[1] Z. Long and M.-Y. Chow, “Multi-objective energy scheduling with fuzzy logic-based weight tuning for disaster relief,” in 2025 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES). IEEE, 2025, (accepted).
[2] Z. Long and M.-Y. Chow, “An ems research and development fast prototyping platform for disaster relief,” 2025, (accepted).
[3] H. Tian, A. Alhaji, Z. Long, and M.-Y. Chow, “Microgrids for post-disaster power restoration application,” in 2024 IEEE 33rd International Symposium on Industrial Electronics (ISIE). IEEE, 2024, pp. 1-6.
