首页> 外文会议>SEMCCO 2011;International conference on swarm, evolutionary, and memetic computing >Static/Dynamic Environmental Economic Dispatch Employing Chaotic Micro Bacterial Foraging Algorithm
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Static/Dynamic Environmental Economic Dispatch Employing Chaotic Micro Bacterial Foraging Algorithm

机译:混沌微细菌觅食算法的静态/动态环境经济调度

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Environmental Economic Dispatch is carried out in the energy control center to find the optimal thermal generation schedule such that power balance criterion and unit operating limits are satisfied and the fuel cost as well as emission is minimized. Environmental economic dispatch presents a complex, dynamic, non-linear and discontinuous optimization problem for the power system operator. It is quite well known that gradient based methods cannot work for discontinuous or nonconvex functions as these functions are not continuously differentiable As a result, evolutionary methods are increasingly being proposed. This paper proposes a chaotic micro bacterial foraging algorithm (CMBFA) employing a time-varying chemotactic step size in micro BFA. The convergence characteristic, speed, and solution quality of CMBFA is found to be significantly better than classical BFA for a 3-unit system and the standard IEEE 30-bus test system.
机译:在能源控制中心进行环境经济调度,以找到最佳的热发电计划,从而满足功率平衡标准和单位运行限制,并最大程度地减少燃料成本和排放。环境经济调度为电力系统运营商提出了复杂,动态,非线性和不连续的优化问题。众所周知,基于梯度的方法不适用于不连续或非凸函数,因为这些函数无法连续微分。结果,越来越多地提出了进化方法。本文提出了一种在微BFA中采用时变趋化步长的混沌微细菌觅食算法(CMBFA)。对于3单元系统和标准IEEE 30总线测试系统,CMBFA的收敛特性,速度和解决方案质量明显优于传统BFA。

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