Research on the balance optimization of investment demand and investment capability of power grid enterprises

被引:1
|
作者
Sha Yuheng [1 ]
Qian, Ma [2 ]
Chao, Xu [2 ]
Xue, Tan [3 ]
Jun, Yan [4 ]
Zhang Yuqian [4 ]
机构
[1] State Grid Corp Dev Planning Dept, Beijing 100031, Peoples R China
[2] State Grid Jiangsu Elect Power Co Ltd, Nanjing 210024, Jiangsu, Peoples R China
[3] State Grid Energy Res Inst Co Ltd, Beijing 102211, Peoples R China
[4] Tianjin Tianda Qiushi Power New Technol Co Ltd, Tianjin 300392, Peoples R China
关键词
Investment capability; Investment demand; Main component analysis; Quantum genetic algorithm; Dynamic balance;
D O I
10.1016/j.egyr.2023.05.151
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In the context of the in-depth advancement of the power system reform and the increasingly stringent supervision of state-owned assets and state-owned enterprises, it is urgent to clarify the balance between investment demand and investment capacity of the power grid. First, the investment capacity and investment demand estimation models are established respectively, and then a dynamic balance optimization model between investment capacity and investment demand is established. By adjusting the range of adjustable indicators of the investment ability and demand calculation model, the objective is set to be the smallest difference between the investment ability and the investment need, the Quantum Genetic Algorithm is used to solve the problem. And consider future development scenarios to achieve a dynamic balance between investment ability and the investment need. Through the analysis of calculation examples, it is known that the investment capacity of a certain place is 630 million yuan, and the investment demand is 661 million yuan. Combined with the development of related factors affecting the investment in the future, when the relevant factors are at a certain value, the two reach a balance, and the investment scale after the balance is 649 million yuan, which verifies the feasibility of investment optimization of the investment scale, so as to support the investment decision of power grid. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:943 / 950
页数:8
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