Optimal Solution in Generator Selection

Optimal Solution in Generator Selection

Zhong Zheng1*, Yu Cao2, Hairui Zhang2, Weiming Jing3, Qian Cao4

1College of Electrical Engineering & New Energy, China Three Gorges University, Yichang, 443002, China.
2College of Science, China Three Gorges University, Yichang, 443002, China.
3College of Computer and Information Technology, China Three Gorges University, Yichang, 443002, China.
4College of Foreign Languages, China Three Gorges University, Yichang, 443002, China.

Journal of Theoretical and Applied sciences

This paper focuses on the application of nonlinear programming in solving the optimal selection strategy of generator. A nonlinear programming model for optimal scheme selection was established. Comparative analysis, numerical combination analysis and sensitivity analysis were used to solve the problem, and MATLAB, LINGO and other software were used to assist the calculation. According to the actual background provided in this paper, it can be concluded that the minimum cost of this factory in a week of power failure is 1868443.7 yuan without charging. If the remaining 20% of the battery is taken into account, the minimum charge is 2575502.0 yuan. After obtaining the results, the sensitivity analysis was carried out to improve the practicability of the results.

Keywords:  Nonlinear programming model; Sensitivity analysis; Numerical combination analysis

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How to cite this article:
Zhong Zheng, Yu Cao, Hairui Zhang, Weiming Jing, Qian Cao. Optimal Solution in Generator Selection. Journal of Theoretical and Applied Sciences, 2020, 3:16. DOI:10.28933/jtas-2020-02-0505

1. Sen Tian. Research on generation – coal cost model based on linear programming technology[J]. Business management, 2017(S2):249-251.
2. Huichun Li, Zhemin Li, Ziyang Mao. A combined taxi dispatching model based on integer linear programming[J]. Transportation research, 2018, 4(05):35-42.
3. Chao Cai, Jianzhong Ding, Feng Lv, Haixing Yuan, Ying Zhu, Guoqiang Sun, Zhinong Wei. Optimization of distribution network fault indicator based on integer linear programming model [J/OL]. Power system protection and control: 1-9[2019-07-17].
4. Ying Zhao, Jing Gao. Theoretical thinking of sensitivity analysis and its application in business decision-making[J]. Radio and television university institute of technology, 2005(04):17-18+20.
5. Shengping Yu, Qinghua Wu, Kun Liu, Jiahao Chen. A test method for infinitely many optimal solutions of linear programming models[J]. Journal of hubei university for nationalities (natural science edition), 2017,35(03):278-281.