基于粒子群优化技术的复合绝缘子剩余寿命估算

P. Ashitha, S. Ganga
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引用次数: 1

摘要

近年来,世界见证了对绿色能源和燃料的推动。这导致了可再生能源与现有电网的整合。随着可再生能源领域的发展迈出了巨大的步伐,考虑和提高输电线路的容量也同样重要。在高电压水平下向用户端传输电力是可取的,以减少发生的线路损耗。但在更高的电压下传输电力;在几百千伏的量级上,再次对架空输电线路绝缘子的设计和使用寿命估计构成限制因素。本文对架空输电线路用复合绝缘子的寿命估算进行了研究。在过去的几十年里,复合绝缘子在架空输电线路上的应用得到了迅速发展。复合硅绝缘子作为架空输电线路使用时,受到风、雨、紫外线辐射、温度、机械、热和电气等多种应力的影响,大大降低了其使用寿命。因此,预测这些绝缘子的寿命是至关重要的。本文研制了一种能够预测复合绝缘子寿命的模糊控制器。采用粒子群优化(PSO)技术提高了模型的精度。采用模糊逻辑控制器的Mamdani模型,结合三角隶属函数和高斯隶属函数。结果表明,采用多隶属函数规则集的粒子群优化调谐控制器比不进行优化的模糊控制器误差更小。将优化前后的仿真结果与实验数据进行了比较,验证了系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Remaining life estimation of a overhead composite insulator using particle swarm optimization technique
In the recent years the world has witnessed a push towards green energy and fuels. This has resulted in the integration of renewable energy into the existing grids. With the developments in renewable energy sector taking mammoth steps, it is equally important to consider and enhance the transmission line capacities. Transmission of power to the consumer end is desirable to be done at high voltage levels to reduce the line losses that occur. But the transmission of power at higher voltages; in the magnitude of several hundreds of kilovolts, again pose a limiting factor in the design and useful life estimation of overhead transmission line insulators. In this paper, the life estimation of composite insulators used in overhead transmission lines is studied. The use of composite insulators for overhead transmission lines picked up momentum over the last few decades. Composite silicone insulators when being used as overhead transmission lines, are subjected to multiple stresses some of them being, wind, rain, ultra violet radiations, temperature, mechanical, thermal and electrical, which reduces their life drastically. Hence the prediction of life time of these insulators is of prime importance. In this paper a fuzzy logic controller is developed which is capable of predicting the life of composite insulators. Particle swarm optimization (PSO) technique is used to enhance the accuracy of the model. Mamdani model of fuzzy logic controller is used, with a combination of Triangular and Gaussian membership functions. It is found that the particle swarm optimization tuned controller with multi membership function rule set gives lower error than a fuzzy logic controller without optimization. The result obtained from simulation with and without optimization is compared with the experimental data available to validate the effectiveness of the proposed system.
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