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Monarch Butterfly Optimization-Based Computational Methodology for Unit Commitment Problem
Electric Power Components and Systems ( IF 1.7 ) Pub Date : 2021-05-02 , DOI: 10.1080/15325008.2021.1908458
Vineet Kumar 1 , Ram Naresh 1
Affiliation  

Abstract

—This paper provides a computational methodology based on monarch butterfly optimization (MBO) to find a solution to the problem of cost-based unit commitment (CBUC). The binary variables of unit commitment problems are handled by modifying the continuous-time nature of the monarch butterfly algorithm. Thermal unit generation, uptime, downtime, ramp rate limits as well as system reserve are considered in the test systems. The computational approach has many parts that not only minimize the cost function but also handle the mixed constraints of the commitment problem. The effect of thermal turbine valve-point loading is also taken into consideration. The computational technique has been used to solve a ten-unit original system and five scaled-up adaptations obtained from this base system. The results obtained are in agreement with the recent results available in the literature. Comparative analysis shows the effectiveness of the proposed MBO-based solution methodology in terms of operating costs and execution time in relation to other techniques.



中文翻译:

基于帝王蝶优化的单元承诺问题计算方法

摘要

—本文提供了一种基于君主蝴蝶优化(MBO)的计算方法,以找到基于成本的单位承诺(CBUC)问题的解决方案。通过修改君主蝴蝶算法的连续时间性质来处理单元提交问题的二进制变量。在测试系统中考虑了热单元发电、正常运行时间、停机时间、斜坡率限制以及系统储备。计算方法有很多部分,不仅可以最小化成本函数,还可以处理承诺问题的混合约束。还考虑了热力涡轮阀点载荷的影响。该计算技术已被用于解决一个十个单元的原始系统和从该基本系统获得的五个按比例放大的适应性问题。获得的结果与文献中最近可用的结果一致。比较分析显示了所提议的基于 MBO 的解决方案方法在与其他技术相关的运营成本和执行时间方面的有效性。

更新日期:2021-06-24
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