基于贝叶斯正则化反向传播神经网络的传输损耗分配

N. Choudhury, S. Goswami
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引用次数: 3

摘要

由于重组后电力系统运行方式的改变,在解除管制的电力市场中分配输电损失已成为一个重要问题。将损耗分配给各参与方的难点在于传输损耗具有相互耦合性,因此没有可接受的工程解决方案。博弈论方法可能是一种可接受的方法,因为它们是基于个体玩家的满意度而开发的。另一方面,博弈论方法作为一种独立的求解工具,由于需要处理大量的数据来解决单个案例,应用博弈论方法也很困难。因此,本文提出了博弈论和神经网络的结合作为一种替代解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transmission loss allocation using Bayesian regularization backpropagation ANN
Allocating losses due to transmission in deregulated power market has become an important issue due to the changed operating mode of restructured power system. The difficulty with the job of loss allocation to the participating players lies in the fact that transmission losses have mutual couplings thus having no acceptable engineering solutions. Game theoretic approach might be an acceptable approach as they are developed based on the satisfaction of the individual players. Applying game theoretic approach on the other hand, as an independent solution tool is also difficult as it needs handling of huge data to solve a single case. A combination of the game theory and neural network thus is proposed here as an alternative solution.
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