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Deterministically guided differential evolution for constrained power dispatch with prohibited operating zones

机译:确定性引导的差分进化,用于受禁运行区域的受限功率分配

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This paper presents a new approach to solve economic load dispatch (ELD) problem in thermal units with non-convex cost functions using differential evolution technique (DE). In practical ELD problem, the fuel cost function is highly non linear due to inclusion of real time constraints such as valve point loading, prohibited operating zones and network transmission losses. This makes the traditional methods fail in finding the optimum solution. The DE algorithm is an evolutionary algorithm with less stochastic approach to problem solving than classical evolutionary algorithms.DE have the potential of simple in structure, fast convergence property and quality of solution. This paper presents a combination of DE and variable neighborhood search (VNS) to improve the quality of solution and convergence speed. Differential evolution (DE) is first introduced to find the locality of the solution, and then VNS is applied to tune the solution. To validate the DE-VNS method, it is applied to four test systems with non-smooth cost functions. The effectiveness of the DE-VNS over other techniques is shown in general.
机译:本文提出了一种新的方法,利用差分演化技术(DE)解决具有非凸成本函数的热力机组的经济负荷分配(ELD)问题。在实际的ELD问题中,由于包含了实时限制,例如阀点负载,禁止的工作区域和网络传输损耗,燃油成本函数是高度非线性的。这使得传统方法无法找到最佳解决方案。 DE算法是一种进化算法,与传统的进化算法相比,其解决问题的随机性较小。DE具有结构简单,收敛速度快和求解质量高的潜力。本文提出了DE和变量邻域搜索(VNS)的组合,以提高解的质量和收敛速度。首先引入差分进化(DE)来找到解决方案的局部性,然后应用VNS来调整解决方案。为了验证DE-VNS方法,该方法被应用于具有不平滑成本函数的四个测试系统。总体上显示了DE-VNS相对于其他技术的有效性。

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