The optimization algorithm of power capacity increase in industrial park based on 0-1 integer linear programming

Xinxin Huang; Gang Xu; Yunfei Chen; Guoyi Wang; Jiawei Chen; Wei Peng

doi:10.1117/12.2627904

22 April 2022 The optimization algorithm of power capacity increase in industrial park based on 0-1 integer linear programming

Xinxin Huang, Gang Xu, Yunfei Chen, Guoyi Wang, Jiawei Chen, Wei Peng

Author Affiliations +

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 1216328 (2022) https://doi.org/10.1117/12.2627904
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

As it increasingly sharps in the city, the contradiction of power supply load sees the phenomenon of heavy overload and equipment redundancy, which caused by the un-synchronization of power grid development and load growth is obvious. And the distribution network capacity increase demand is growing. The first choice to increase the capacity of distribution network is using the 0-1 integer linear programming model. Therefore, according to the capacity increase demand of current distribution network, the paper come up with an optimization algorithm of power capacity increase which basing on 0-1 integer linear programming model, and it is applied to industrial park to carry out specific experiments. The experimental results show that this method can realize the demand of power capacity increase and optimize the operation mode of distribution network. It plays a great role in improving the intelligent level of distribution network.

Citation Download Citation

Xinxin Huang, Gang Xu, Yunfei Chen, Guoyi Wang, Jiawei Chen, and Wei Peng "The optimization algorithm of power capacity increase in industrial park based on 0-1 integer linear programming", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 1216328 (22 April 2022); https://doi.org/10.1117/12.2627904

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