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Interval-based differential evolution approach for combined economic emission load dispatch

机译:基于区间的差分演化方法用于组合经济排放负荷分配

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In this paper we propose an Interval based Differential Evolution (IDE) algorithm, an improved version of Differential Evolution (DE) algorithm using interval arithmetic. After estimating the global minimum roughly, the IDE algorithm constructs a mechanism which updates the upper bound of global minimum at each generation and defines an efficient termination criterion. Also at each generation it modifies the new population using the subset of current population and thus reduces the computational effort. We apply the proposed algorithm to the Combined Economic Emission Load Dispatch (CEELD) problem which obtains the optimal amount of generated power for the thermal generating units in the system by simultaneously minimising the fuel and emission costs. We find the proposed algorithm to be more efficient than the conventional DE when applied to IEEE 6 generators system. We also find that these results using the IDE algorithm are better than some recently reported evolutionary algorithms.
机译:在本文中,我们提出了一种基于间隔的差分进化(IDE)算法,这是一种使用间隔算法的差分进化(DE)算法的改进版本。在粗略估计全局最小值之后,IDE算法构造一种机制,该机制可以在每一代更新全局最小值的上限,并定义有效的终止条件。同样在每一代,它都使用当前总体的子集修改新总体,从而减少了计算量。我们将提出的算法应用于联合经济排放负荷分配(CEELD)问题,该问题通过同时最小化燃料和排放成本来获得系统中火电机组的最佳发电量。我们发现,所提出的算法在应用于IEEE 6生成器系统时比传统的DE更有效。我们还发现,使用IDE算法的这些结果比一些最近报道的进化算法要好。

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