基于反向回溯搜索算法的经济负荷调度

Moumita Pradhan, P. Roy, T. Pal
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引用次数: 2

摘要

针对大规模经济负荷调度问题,提出了一种反向回溯搜索算法。传统回溯搜索算法(BSA)的主要缺点是产生的是局部最优解,而不是全局最优解。提出的OBSA方法是一个高度约束的优化问题,必须通过满足负载需求、发电限制、禁止操作区域、匝道速率限制和阀点负载效应等几个约束来最小化总发电成本。该方法已应用于三个测试系统,并提供了独特、快速的解决方案。新的启发式OBSA方法成功地应用于由13台和140台热机组成的三个测试系统中。测试结果是根据各种方法来判断的。仿真结果表明,该算法与传统的BSA、对抗入侵杂草优化(OIWO)、shuffle差分进化(SDE)和对抗实编码化学反应优化(ORCCRO)等方法相比,具有较好的有效性和准确性。这清楚地表明,新的OBSA方法可以实现非线性电场问题的有效和可行的求解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Economic Load Dispatch Using Oppositional Backtracking Search Algorithm
In this paper, an oppositional backtracking search algorithm (OBSA) is proposed to solve the large scale economic load dispatch (ELD) problem. The main drawback of the conventional backtracking search algorithm (BSA) is that it produces a local optimal solution rather than the global optimal solution. The proposed OBSA methodology is a highly-constrained optimization problem has to minimize the total generation cost by satisfying several constraints involving load demand, generation limits, prohibited operating zone, ramp rate limits and valve point loading effect. The proposed method is applied for three test systems and provides the unique and fast solutions. The new heuristic OBSA approach is successfully applied in three test systems consisting of 13 and 140 thermal generators. The test results are judged against various methods. The simulation results show the effectiveness and accuracy of the proposed OBSA algorithm over other methods like conventional BSA, oppositional invasive weed optimization (OIWO), Shuffled differential evolution (SDE) and oppositional real coded chemical reaction optimization (ORCCRO). This clearly suggests that the new OBSA method can achieve effective and feasible solutions of nonlinear ELD problems.
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