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Renewable Energy-Based Economic Load Dispatch Using Two-Step Biogeography-Based Optimization and Butterfly Optimization Algorithm

机译:基于可再生能源的经济负载调度,采用基于两步生物地理的优化和蝶优化算法

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摘要

This article introduces a unified approach to solve economic load dispatch (ELD) problem of an integrated power system that comprise of traditional thermal power units and renewable sources of energy such as wind energy (WE) and solar photovoltaic (PV) sources; employing a two-step optimization method consisting of Biogeography Based Optimization (BBO) and Butterfly Optimization Algorithm (BOA). BOA imitates the mating and food search process of butterflies for solving the problems associated with global optimization. Nonlinear characteristics of thermal generators is considered in the problem. Weibull distribution is used for determining the uncertainness in availability of wind power and Lognormal PDF is employed for calculating the availability of solar power. The efficacy, robustness and supremacy of the two-step BBO-BOA (hBBO-BOA) technique, compared to various other approaches in literature, are demonstrated by the simulation results. The outcome is quite inspiring, indicates that proposed hBBO-BOA is an efficient approach in order to solve different ELD problems.
机译:本文介绍了解决了一种统一的方法来解决集成电力系统的经济负载调度(ELD)问题,包括传统的火电机和可再生能源,如风能(我们)和太阳能光伏(PV)源;采用两步优化方法,包括基于生物地理的优化(BBO)和蝶形优化算法(BOA)。蟒蛇模仿蝴蝶的配合和食品搜索过程,以解决与全局优化相关的问题。在问题中考虑了热发电机的非线性特性。 Weibull分布用于确定风电和Lognormal PDF的不统计不确定用于计算太阳能的可用性。通过仿真结果证明了与文献中的各种其他方法相比,两步BBO-BOA(HBBO-BOA)技术的功效,鲁棒性和至高无上。结果是非常鼓舞人身的,这表明提出的HBBO-BOA是一种有效的方法,以解决不同的ELD问题。

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