基于风险的配电变压器检修计划优化研究

发布时间：2018-07-12 12:45

本文选题：状态检修 + 风险　；参考：《华北电力大学》2015年硕士论文

【摘要】：配电变压器作为配电网中关键设备之一,本文阐述了对其实施状态检修的必要性。分析比较现有的状态检修决策思想可知,基于风险的状态检修以其能够兼顾设备运行可靠性及经济性的优点,越来越受到亲睐。根据风险的概念,电力系统的风险评估是要评估失效事件发生的概率和失效事件发生后果的严重程度。为了描述设备的老化过程,本文中提出了基于多状态马尔科夫过程的设备停运概率模型,考虑到预防性检修对设备停运概率的影响,对停运模型进行了修正;考虑到不同类型负荷的负荷损失量相同时,造成的电网收益损失不同,据此建立了计及负荷类型的电网收益损失模型;考虑到故障及检修等风险,计及电网运行的等式约束、不等式约束及检修约束等约束条件,建立了基于风险的配电变压器检修计划优化模型;人工蜂群算法在搜索过程中能够很好地兼顾食物源的探索和开采过程,每次迭代能够同时进行全局搜索和局部搜索,在一定程度上减小了收敛到局部最优解的概率,因此,越来越受到人们的亲睐。但是作为一种智能算法,仍不可避免的存在收敛速度慢、陷入局部最优的缺点,因此,本文采用混沌搜索算子对算法进行了改进,并通过测试函数验证了优化算法的优越性;以RBTS-BUS2系统为算例,对系统的22台配电变压器建立了基于风险的检修优化模型,并采用基于混沌搜索的人工蜂群算法对优化模型进行了求解和分析,验证了所提出模型和所采用算法的有效性和合理性。
[Abstract]:Distribution transformer is one of the key equipments in distribution network. By analyzing and comparing the existing status based maintenance decision ideas, it is known that the risk-based condition based maintenance is more and more popular because of its advantages of both reliability and economy of equipment operation. According to the concept of risk, power system risk assessment is to evaluate the probability of failure events and the severity of the consequences of failure events. In order to describe the aging process of equipment, this paper presents a probability model of equipment outage based on multi-state Markov process. Considering the influence of preventive maintenance on equipment outage probability, the outage model is modified. Considering that the load loss of different load types is the same, the power network income loss model considering the load type is established, and considering the risks such as failure and maintenance, the equation constraints of power network operation are considered. The optimization model of maintenance plan for distribution transformers based on risk is established under the constraints of inequality and maintenance, and the artificial bee colony algorithm is able to take into account the exploration and exploitation of food sources in the process of searching. Each iteration can perform both global and local search simultaneously, which reduces the probability of convergence to the local optimal solution to a certain extent, so it is becoming more and more popular. However, as an intelligent algorithm, it is inevitable that the convergence speed is slow and the algorithm falls into local optimum. Therefore, chaotic search operator is used to improve the algorithm, and the superiority of the optimization algorithm is verified by testing function. Taking RBTS-BUS2 system as an example, a risk-based maintenance optimization model is established for 22 distribution transformers, and the optimization model is solved and analyzed by artificial bee colony algorithm based on chaotic search. The validity and rationality of the proposed model and the proposed algorithm are verified.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM421

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