Abstract
As an efficient organization form of distributed energy resources with high permeability, microgrid (MG) is recognized as a promising technology with the promotion of various clean renewable sources. Due to uncertainties of renewable sources and load demands, optimizing the dispatch of controllable units in microgrid to reduce economic cost has become a critical issue. In this paper, an economic dispatch optimization model for microgrid including distributed generation and storage is established with the considering of inherent links between intervals, which aims to minimize the economic and environmental costs. In order to solve the optimization problem, a novel swarm intelligence algorithm called fireworks algorithm with momentum (FWAM) is also proposed. In the algorithm, the momentum mechanism is introduced into the mutation strategy, and the generation of the guiding spark is modified with the historical information to improve the searching capability. Finally, in order to verify the rationality and effectiveness of the proposed model and algorithm, a microgrid system is simulated with open data. The simulation results demonstrate FWAM lowers the economic cost of the microgrid system more effectively compared with other swarm intelligence algorithms such as GFWA and CMA-ES.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (Grant No. 62076010), and partially supported by Science and Technology Innovation 2030 - “New Generation Artificial Intelligence” Major Project (Grant Nos.: 2018AAA0102301 and 2018AAA0100302). (Ying Tan is the corresponding author.)
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Li, M., Tan, Y. (2022). Economic Dispatch Optimization for Microgrid Based on Fireworks Algorithm with Momentum. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2022. Lecture Notes in Computer Science, vol 13344. Springer, Cham. https://doi.org/10.1007/978-3-031-09677-8_29
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DOI: https://doi.org/10.1007/978-3-031-09677-8_29
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