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Bat Algorithm Implementation on Economic Dispatch Optimization Problem

机译：经济调度优化问题的蝙蝠算法实现

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摘要

Power plant is one of the substantial industry in a country since it supports various needs of people. Optimum cost for running this industry is a necessity so that power generated can be produce according to power demand with appropriate cost. Economic dispatch is an optimization approach in power system plant with objective function is to minimize cost by finding appropriate arrangement of generator output according electric requirement and capacity of the system. Previous researches have been proposed techniques to solve this problem, however a stable convergence and good computational efficiency is still required. Therefore, this paper proposes bat algorithm to minimize total generator cost from thermal power plant. Bat algorithm is one of nature inspired optimization problem which has advantage in stable convergence. The experiment results show that Bat algorithm is able to save approximately 1.23% compare to the actual cost and 0.12% to firefly algorithm.
机译：发电厂是一个国家的重要产业之一，因为它可以满足人们的各种需求。运行该行业的最佳成本是必不可少的，因此可以根据电力需求以适当的成本生产发电。经济调度是电厂系统中的一种优化方法，其目标功能是通过根据系统的电力需求和容量找到合适的发电机输出布置来最大程度地降低成本。已有研究提出了解决该问题的技术，但是仍然需要稳定的收敛性和良好的计算效率。因此，本文提出了蝙蝠算法以最小化火力发电厂的总发电成本。蝙蝠算法是自然启发式优化问题之一，具有稳定收敛的优势。实验结果表明，蝙蝠算法与实际成本相比可节省约1.23％，与萤火虫算法相比可节省0.12％。

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