基于重要度的风力发电系统可靠性优化分析

doi:10.12005/orms.2023.0380

运筹与管理 ›› 2023, Vol. 32 ›› Issue (12): 15-21.DOI: 10.12005/orms.2023.0380

基于重要度的风力发电系统可靠性优化分析

兑红炎¹, 张雨露¹, 刘朝¹, 张云安²

1.郑州大学管理学院,河南郑州 450001;
2.国防科技大学智能科学学院,湖南长沙 410073

收稿日期:2021-12-02 出版日期:2023-12-25 发布日期:2024-02-06
通讯作者: 刘朝(1986-), 男,河南郑州人,硕士,研究方向:系统工程和可靠性。
作者简介:兑红炎(1982-),男,河南新郑人,博士,教授,研究方向:系统可靠性和重要度;张雨露(1999-),女,河南商丘人,硕士,研究方向:系统可靠性;张云安(1983-),男,广西桂林人,博士,副教授,研究方向:复杂系统可靠性。
基金资助:
国家自然科学基金资助项目(72071182,U1904211);教育部人文社科规划基金资助项目(20YJA630012);河南省科技攻关(222102520019);河南省高校科技创新人才支持计划(22HASTIT022);河南省高等学校青年骨干教师培养计划(2021GGJS007)

Importance Measure-based Reliability Optimization of a Wind Power System

DUI Hongyan¹, ZHANG Yulu¹, LIU Zhao¹, ZHANG Yunan²

1. School of Management, Zhengzhou University, Zhengzhou 450001, China;
2. Intelligence Science College, National University of Defense Technology, Changsha 410073, China

Received:2021-12-02 Online:2023-12-25 Published:2024-02-06

摘要/Abstract

摘要： 风力发电具有随机性、间歇性和波动性等特点,风力发电系统容易受外部环境影响而发生故障。供给节点影响风力发电系统可靠性,节点故障导致风力发电系统故障,造成人力、物力和财力的损失。为避免严重的经济损失,本文提出基于重要度的风力发电系统可靠性优化模型。首先,基于风速特性定义风力发电系统可靠性。然后,给出风力发电系统Birnbaum重要度和综合重要度,分析节点对风力发电系统可靠性的影响程度;然后通过重要度梯度对风力发电系统进行可靠性优化。最后针对某风力发电系统,分析节点和系统可靠性,给出不同重要度下节点对系统可靠性的影响。基于不同重要度评估固定资源约束下故障节点的维修顺序,通过重要度梯度评估风力发电系统可靠性提升最快方向。结果表明,基于重要度梯度对风力发电系统可靠性优化具有一定可行性。

关键词: 可靠性, 重要度, 风力发电系统, 梯度

Abstract: With the increase in the number of wind turbines and installed capacity, the scale of wind power systems has increased and become more complex. Nodes affect wind power system reliability, and node failures lead to wind power system failures, resulting in human, material and financial losses. Therefore, how to accurately assess the reliability of wind power generation system is crucial for the whole grid network. Evaluating the degree of influence of nodes on the wind power system through importance theory and optimizing the reliability of the wind power system through gradient theory can help managers identify and solve the wind power system reliability problems. In this paper, the wind power generation system reliability optimization problem is addressed, and the wind power generation system reliability importance model is established based on the importance theory. Based on Birnbaum’s importance degree and comprehensive importance degree respectively, the impact of faulty nodes on wind power generation system reliability enhancement under fixed resource constraints is evaluated, so that the wind power generation system reliability can be quickly restored to the optimal state. Then the fastest direction of wind power generation system reliability enhancement is evaluated by importance gradient analysis.
To avoid serious economic losses, this paper presents a reliability optimization model of the wind power system. Firstly, the reliability of the wind power generation system based on wind speed characteristics is proposed. Secondly, the Birnbaum importance measure and integrated importance measure of the wind power system are given, and the influence of nodes on wind power system reliability is analyzed. Then the reliability of the wind power system is optimized by the importance gradient. Finally, for a wind power system, the node and system reliability are analyzed, and the influence of nodes on the system reliability under different importance measures is given. The maintenance sequence of failed nodes under fixed resource constraints is evaluated based on different importance measures. The fastest direction of reliability improvement of the wind power system is evaluated through the importance gradient. In order to find out the fastest growing direction of wind power system reliability so that the system reliability can be optimized, the importance of different nodes needs to be ranked and gradient calculated.
The simulation assumptions are as follows. It is assumed that the nodes are independent of each other, and the reliability of the demand node obeys an exponential distribution with a failure rate of 0.006/week for the demand node. The reliability of the supply node is obtained from the probability of supply and demand electricity consumption, and the failure rate of the supply node is 0.004/week, 0.006/week, 0.005/week, 0.005/week, 0.008/week, 0.007/week, respectively. Based on the monthly electricity consumption of 65 kWh in 2020, the demanded electricity consumption per unit of time of the population in a region is 20 kW, and the wind turbine operation cycle is 60 weeks.
Substituting the above assumptions into the Birnbaum importance, comprehensive importance model respectively, the following conclusions are obtained. According to the Birnbaum importance degree, the priority ranking of supply node reliability on wind power generation system reliability is node G8, node G13, node G1, node G11, node G2, node G5, among which, node G8 has the greatest influence on wind power generation system reliability, and the change of node G8’s state makes the greatest change in system reliability. Based on the combined importance, the priority ranking of the supply node reliability impact on the performance of the wind power generation system is node G8, node G13, node G11, node G1, node G2, and node G5, where node G8 has the greatest impact on the wind power generation system reliability, and the change in the state of node G8 makes the greatest change in the reliability of the system.
According to the Birnbaum importance gradient model of the wind power system, the following results can be obtained. The Birnbaum importance of the wind power generation system at point A is (I^BI₁,I^BI₃)=OA. The direction of the vector R is the direction in which the reliability of the wind power system is growing the fastest. Therefore, the manager should make the reliability of node G1, node G3 and node G8 closer to point A to ensure that the system reliability grows along the fastest direction.
According to the integrated importance gradient model of the wind power generation system, the following results can be obtained. The vector U is normal to the surface Q, and the point of intersection between the two is B. The projection point of the vector on the gradient U is C. The integrated importance of node G1 at point B is I^IIM₁=‖OB‖·‖OC‖. In a multistate system, managers should make the probability of the node G1 in different states converge to the point B, to ensure that the system reliability grows along the fastest direction.

Key words: reliability; importance measure; wind power system;gradient

中图分类号:

N945

兑红炎, 张雨露, 刘朝, 张云安. 基于重要度的风力发电系统可靠性优化分析[J]. 运筹与管理, 2023, 32(12): 15-21.

DUI Hongyan, ZHANG Yulu, LIU Zhao, ZHANG Yunan. Importance Measure-based Reliability Optimization of a Wind Power System[J]. Operations Research and Management Science, 2023, 32(12): 15-21.

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基于重要度的风力发电系统可靠性优化分析

Importance Measure-based Reliability Optimization of a Wind Power System

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