Optimization scheduling strategy of microgrid system based on multi-agent system

Shi Qiu; Zhe Chen; Guangyong Yang; Yuyang Song

doi:10.1117/12.3030519

5 June 2024 Optimization scheduling strategy of microgrid system based on multi-agent system

Shi Qiu, Zhe Chen, Guangyong Yang, Yuyang Song

Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 131634T (2024) https://doi.org/10.1117/12.3030519
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China

Abstract

The traditional optimal scheduling of microgrid usually only considers the optimal allocation strategy of one energy form, and lacks research on the interaction effects of multiple energy sources. Aiming at the problem that a large number a variety of energy sources interact with the operation of multi-energy microgrid, this paper designs an optimal scheduling strategy of multi-energy microgrid based on multi-agent system. Firstly, multi-agent technology is used to model renewable energy, natural gas and energy storage modules respectively, and the network topology of micro-grid CPS is constructed based on Petri net theory. Then, taking the minimum running cost and the maximum utilization of clean energy as the optimization goal, comprehensive consideration of equipment constraints, energy balance and other factors, the multi-energy microgrid optimization scheduling model is established. Finally, simulation results show solve the problem that a large number of multiple energy sources interact to affect the operation of the multi-energy microgrid.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shi Qiu, Zhe Chen, Guangyong Yang, and Yuyang Song "Optimization scheduling strategy of microgrid system based on multi-agent system", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 131634T (5 June 2024); https://doi.org/10.1117/12.3030519

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