考虑供需综合因素的电网检修计划最优决策模型

doi:10.11930/j.issn.1004-9649.202003202

中国电力 ›› 2021, Vol. 54 ›› Issue (6): 159-167.DOI: 10.11930/j.issn.1004-9649.202003202

考虑供需综合因素的电网检修计划最优决策模型

刘辉¹, 江千军², 桂前进², 王磊¹, 田宏强¹, 王京景¹, 杨贺钧³

1. 国网安徽省电力有限公司，安徽合肥 230001;
2. 国网安庆供电公司，安徽安庆 246000;
3. 安徽省新能源利用与节能省级实验室（合肥工业大学），安徽合肥 230009

收稿日期:2020-03-27 修回日期:2020-08-26 发布日期:2021-06-05
作者简介:刘辉(1978-),男,博士,高级工程师,从事电网运行分析与控制研究,E-mail:relayliu@163.com;杨贺钧(1985-),男,通信作者,博士,讲师,从事电力系统规划与可靠性研究,E-mail:cquyhj@126.com
基金资助:
国网安徽省电力有限公司科技项目(5212D018008X)；国家自然科学基金资助项目(51607051)

Optimal Decision-making Model for Power Grid Maintenance Scheduling Considering Comprehensive Supply-Demand Factors

LIU Hui¹, JIANG Qianjun², GUI Qianjin², WANG Lei¹, TIAN Hongqiang¹, WANG Jingjing¹, YANG Hejun³

1. State Grid Anhui Electric Power Co., Ltd., Hefei 230001, China;
2. State Grid Anqing Power Supply Company, Anqing 246000, China;
3. Anhui Provincial Laboratory of Renewable Energy Utilization and Energy Saving (Hefei University of Technology), Hefei 230009, China

Received:2020-03-27 Revised:2020-08-26 Published:2021-06-05
Supported by:
This work is supported by Science and Technology Project of State Grid Anhui Electric Power Co., Ltd. (No.5212D018008X) and National Natural Science Foundation of China (No.51607051)

摘要/Abstract

摘要： 电网检修停电决策严重影响供电可靠性和用户满意度，实际电网检修计划主要以适合单一计划检修停电事件的主观经验决策为主导，但该方式难以实现多重检修计划停电事件的最优化决策问题，且现有方案仅考虑降低检修停电电量，仍需要兼顾检修侧与用户侧各方利益。为此提出了考虑供需综合因素的电网多重停电事件最优决策方法。首先，建立考虑多重停电事件的电网最优检修计划停电决策模型，该模型以最小化停电电量（电网侧）、最小化用户用电失望度（用户侧）和最大化设备停电时间差异度（检修侧）等构建多目标函数，以停电电量约束、特殊事件约束等为约束函数。其次，为提高优化效率，建立基于比例系数法的电网最优检修停电决策单目标函数优化模型；再次，构建基于惩罚函数的适应值优化模型，采用遗传算法对最优检修停电决策问题进行求解；最后，采用实际电网案例进行仿真分析，并验证所提模型和算法的正确性与有效性。

关键词: 电网检修, 停电决策, 遗传算法, 优化模型, 多重停电

Abstract: Power grid outage decision-making for maintenance significantly affects the power supply reliability and customer’s satisfactions. The actual maintenance schedule for power grid is subjected to the subjective experience decision-making which is suitable for single maintenance outage plan. However, this method is difficult to achieve the optimal decision-making for multiple outage events, and the existing scheme only considers reducing the amount of outage power, instead of the interests of both the maintenance side and the user side. Therefore, we propose an optimal decision-making method for multiple outage events with consideration of the comprehensive supply-demand factors. Firstly, an outage decision-making model is established for optimal power grid maintenance scheduling with consideration of multiple outage events. In this model, the multi-objective function is constructed with minimized power outage (at grid side), minimized disappointment degree of user’s power consumption (user side) and maximized difference degree of equipment outage time (maintenance side), and the constraints of outage power and special events are used as constraint functions. Secondly, in order to improve the optimization efficiency, a single-objective function optimization model is constructed for optimal power grid outage decision-making based on the proportional coefficient method. Thirdly, a fitness optimization model is constructed based on the penalty function, and the genetic algorithm is used to solve the optimal outage decision-making problem. Finally, a real power grid case is used for simulation analysis, which has verified the correctness and effectiveness of the proposed model and algorithm.

Key words: equipment maintenance, outage decision-making, genetic algorithm, optimization model, multiple outages

刘辉, 江千军, 桂前进, 王磊, 田宏强, 王京景, 杨贺钧. 考虑供需综合因素的电网检修计划最优决策模型[J]. 中国电力, 2021, 54(6): 159-167.

LIU Hui, JIANG Qianjun, GUI Qianjin, WANG Lei, TIAN Hongqiang, WANG Jingjing, YANG Hejun. Optimal Decision-making Model for Power Grid Maintenance Scheduling Considering Comprehensive Supply-Demand Factors[J]. Electric Power, 2021, 54(6): 159-167.

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考虑供需综合因素的电网检修计划最优决策模型

Optimal Decision-making Model for Power Grid Maintenance Scheduling Considering Comprehensive Supply-Demand Factors

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Optimal Decision-making Model for Power Grid Maintenance Scheduling Considering Comprehensive Supply-Demand Factors

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