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Hopfield lagrange network based method for economic emission dispatch problem of fixed-head hydro thermal systems

机译:基于Hopfield拉格朗日网络的固定水头热力系统经济排放调度方法

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摘要

This paper proposes a Hopfield Lagrange Network (HLN) based method (HLNM) for economic emission dispatch of fixed head hydrothermal systems. HLN is a combination of Lagrange function and continuous Hopfield neural network where the Lagrange function is directly used as the energy function for the continuous Hopfield neural network. In the proposed method, HLN is used to find a set of non-dominated solutions and a fuzzy based mechanism is then exploited to determine the best compromise solution among the obtained ones. The proposed method has been tested on four hydrothermal systems and the obtained results in terms of total fuel cost, emission, and computational time have been compared to those other methods in the literature. The result comparisons have indicated that the proposed method is favorable for solving the economic emission dispatch problem of fixed-head hydrothermal systems.
机译:本文提出了一种基于Hopfield Lagrange网络(HLN)的固定水头热力系统经济排放调度方法(HLNM)。 HLN是Lagrange函数和连续Hopfield神经网络的组合,其中Lagrange函数直接用作连续Hopfield神经网络的能量函数。在所提出的方法中,HLN用于找到一组非支配解,然后利用一种基于模糊的机制来确定所获得的最优解。所提出的方法已经在四个水热系统上进行了测试,并且将获得的总燃料成本,排放量和计算时间方面的结果与文献中的其他方法进行了比较。结果比较表明,该方法有利于解决固定头水热系统的经济排放调度问题。

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