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Modified Particle Swarm Optimization for Non-smooth Non-convex Combined Heat and Power Economic Dispatch

机译：非光滑非凸热电联产经济调度的改进粒子群算法

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摘要

This article presents modified particle swarm optimization to solve the non-smooth non-convex combined heat and power economic dispatch problem. Valve-point loading and prohibited operating zones of conventional thermal generators are taken into account. Particle swarm optimization performs well for small-dimensional and less complicated problems but fails to locate global minima for complex multi-minima functions. This article proposes Gaussian random variables in the velocity term, which improves search efficiency and guarantees a high probability of obtaining the global optimum without significantly impairing the speed of convergence and the simplicity of the structure of particle swarm optimization. The effectiveness of the proposed method has been verified on two test systems. The results of the proposed approach are compared with those obtained by other evolutionary methods. It is found that the proposed modified particle swarm optimization based approach is able to provide a better solution.
机译：本文提出了改进的粒子群算法来解决非光滑非凸热电联产经济调度问题。考虑了常规热力发电机的阀点负载和禁止运行区域。粒子群优化方法在处理小尺寸和复杂性较小的问题时效果很好，但无法为复杂的多最小值函数定位全局最小值。本文提出了速度项中的高斯随机变量，它提高了搜索效率，并保证了获得全局最优的高概率，而不会显着影响收敛速度和粒子群优化结构的简单性。该方法的有效性已在两个测试系统上得到验证。将所提出的方法的结果与通过其他进化方法获得的结果进行比较。发现所提出的基于改进的粒子群优化的方法能够提供更好的解决方案。

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