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Emergency Energy Management of Microgrid in Industrial Park Based on Robust Optimization

by Haoliang Yang*, Yonggang Dong, Zhifang Yang

Department of Electrical Engineering, Hebei Vocational University of Technology and Engineering, Xingtai, 054000, China

* Corresponding Author: Haoliang Yang. Email: email

(This article belongs to the Special Issue: Modeling of Artificial Intelligence controller for Microgrid and SmartGrid application)

Energy Engineering 2023, 120(12), 2917-2931. https://doi.org/10.32604/ee.2023.029167

Abstract

Reducing the impact of power outages and maintaining the power supply duration must be considered in implementing emergency energy dispatching in micro-networks. This paper studies a new emergency energy treatment method based on the robust optimal method and the industrial park micro-network with the optical energy storage system. After controlling the load input, a control strategy of adjusting and removing is proposed. Rolling optimal theory is applied to emergency energy scheduling based on a robust optimal mathematical model. A weighting factor is introduced into the optimal model to balance the importance of reducing and retaining the power supply. Uncertainty is designed to adjust the effect of uncertainty on the problem. The example shows that this method can flexibly set the weight coefficient and uncertainty value according to the actual situation so that the input of the control load can be optimized.

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APA Style
Yang, H., Dong, Y., Yang, Z. (2023). Emergency energy management of microgrid in industrial park based on robust optimization. Energy Engineering, 120(12), 2917-2931. https://doi.org/10.32604/ee.2023.029167
Vancouver Style
Yang H, Dong Y, Yang Z. Emergency energy management of microgrid in industrial park based on robust optimization. Energ Eng. 2023;120(12):2917-2931 https://doi.org/10.32604/ee.2023.029167
IEEE Style
H. Yang, Y. Dong, and Z. Yang, “Emergency Energy Management of Microgrid in Industrial Park Based on Robust Optimization,” Energ. Eng., vol. 120, no. 12, pp. 2917-2931, 2023. https://doi.org/10.32604/ee.2023.029167



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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