具有非线性代价函数的多目标发电调度蛾流优化

M. Alam, M. Sulaiman, M. Sayem, M. M. A. Ringku, Shahriar Imtiaz, R. Khan
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引用次数: 0

摘要

将成功历史流量优化(SHMFO)与火力发电机组阀点负荷相结合,解决了联合经济排放调度问题。该阀点负荷问题是一个包括发电机容量限制和功率平衡在内的多目标非线性优化问题。阀点负荷引起发电机组输入输出特性的振荡,使CEED问题成为一个不完全优化问题。作为验证SHMFO有效性的基准测试系统,对IEEE 30总线系统进行了研究。将该方法与其他优化策略进行比较,揭示了其优越性,证明了其解决CEED问题的能力。OPF是一个单目标或多目标问题,对发电机能力、线路容量、母线电压和功率流平衡进行限制,以最大限度地减少燃料成本、排放、传输损耗、电压偏差等。数值结果表明,该算法在单次运行中具有成本效益、多样性和收敛性。结果表明,SHMFO比其他算法性能更好,是解决OPF问题的绝佳选择。在非支配解上,采用了一种基于与理想解相似度排序偏好的方法(TOPSIS)来建立最佳折衷解(BCS)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Success History Moth Flow Optimization for Multi-Goal Generation Dispatching with Nonlinear Cost Functions
Combined Economic Emission Dispatch (CEED) is resolved by combining Success History Moth Flow Optimization (SHMFO) and valve-point loading of thermal generators. This SHMFO the valve-point loading problem is a multi-objective nonlinear optimization problem including generator capacity limits and power balance. The valve-point loading causes oscillations in the input-output characteristics of generating units, hence rendering the CEED problem an imperfect optimization problem. As a benchmark test system for validating the efficacy of SHMFO, IEEE 30-bus systems are studied. Comparing the SHMFO method to other optimization strategies revealed its superiority and proved its capacity to resolve the CEED issue. The OPF is framed as a single or multiobjective problem with restrictions on generator capability, line capacity, bus voltage, and power flow balance to minimize fuel cost, emission, transmission loss, voltage deviation, etc. The numerical findings indicate that the SHMFO algorithm can provide cost-efficiency, diversity, and convergence in a single run. SHMFO performs better than the other algorithms and is an excellent choice for addressing the OPF problem, as shown by the results. On non-dominated solutions, a method adapted from the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is used to establish the Best Compromise Solution (BCS).
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