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Nonconvex Dynamic Economic Power Dispatch Problems Solution Using Hybrid Immune-Genetic Algorithm

机译:基于混合免疫遗传算法的非凸动态经济电力调度问题求解

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摘要

The objective of dynamic economic dispatch (DED) problem is to determine the generation schedule of the committed generation units, which minimizes the total operating cost over a dispatch period, while satisfying a set of constraints. The effect of valve points and prohibited operating zones (POZs) in the generating units\u27 cost functions makes the DED a highly nonlinear and nonconvex optimization problem with multiple local minima. Considering the ramp-rate limits and transmission losses makes the DED problem even more complicated. Hence, proposing an effective solution method for this optimization problem is of great interest. This paper presents a novel heuristic algorithm to solve DED problem of generating units by employing a hybrid immune-genetic algorithm. To illustrate the effectiveness of the proposed approach, four test systems that consist of different numbers of generating units are studied. The valve-point effects, POZs, and ramp-rate constraints along with transmission losses are also considered in simulation cases. The results obtained through the proposed method are compared with those reported in the literature. These results substantiate the applicability of the proposed method for solving the constrained DED problem with nonsmooth cost functions.
机译:动态经济调度(DED)问题的目的是确定承诺的发电单元的发电计划,从而在满足一组约束的同时最大程度地降低调度期间的总运营成本。发电单位成本函数中的阀门点和禁止运行区域(POZ)的影响使DED成为具有多个局部最小值的高度非线性和非凸优化问题。考虑到斜率限制和传输损耗,DED问题变得更加复杂。因此,提出一种针对该优化问题的有效解决方法非常重要。本文提出了一种新颖的启发式算法,通过采用混合免疫遗传算法来解决发电机组的DED问题。为了说明所提出方法的有效性,研究了由不同数量的发电机组组成的四个测试系统。在模拟情况下,还考虑了阀点效应,POZ和斜坡率约束以及传输损耗。通过提议的方法获得的结果与文献报道的结果进行了比较。这些结果证实了所提出方法用于解决具有不平滑成本函数的约束DED问题的适用性。

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