Calculation of transmission system losses for the Taiwan Power Company by the artificial neural network with time decayed weight

W. Chu, Bin Chen, Pao-Chang Mo
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引用次数: 2

Abstract

For energy conservation and improvement of power system operation efficiency, how to reduce the transmission system losses becomes an important topic of grave concern. To understand the cause, and to evaluate the amount, of the losses are the prior steps to diminish them. To simplify the evaluation procedure without losing too much accuracy, this paper adopts the artificial neural network, which is a model free network, to analyze the transmission system losses. As the artificial neural network with time decayed weight has the capability of learning, memorizing, and forgetting, it is more suitable for a power system with gradually changing characteristics. By using this artificial neural network, the estimation of transmission system losses will be more precise. In this paper, comparison is made between the results of artificial neural network analysis and polynomial loss equations analysis.
基于时间衰减权值的人工神经网络计算台湾电力公司输电系统损耗
为了节能和提高电力系统运行效率,如何降低输电系统损耗成为人们高度关注的重要课题。了解损失的原因,评估损失的数额,是减少损失的首要步骤。为了简化评估过程而不损失太多的准确性,本文采用无模型网络人工神经网络对输电系统的损失进行分析。由于具有时间衰减权值的人工神经网络具有学习、记忆和遗忘的能力,因此更适合于具有逐渐变化特性的电力系统。利用该人工神经网络可以更精确地估计输电系统的损耗。本文将人工神经网络分析结果与多项式损失方程分析结果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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