无管制电力系统中基于LR和ABC算法的发电机组优化调度以实现发电机组效益最大化

2013 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC) Pub Date : 2013-04-17 DOI:10.1109/ICCPEIC.2013.6778502

R. Ashok kumar, K. Asokan, S. Ranjith Kumar

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引用次数: 5

摘要

放松管制的电力行业提高了电力生产和分配的效率，并以较低的价格提供了更可靠的电力。在放松管制的环境中，公用事业公司不需要满足总负荷需求。发电公司(genco)以最大化自身利润为目标，而不是牺牲社会效益。无管制电力系统中的盈利单位承诺与传统的盈利单位承诺有着不同的目标。本文提出了拉格朗日松弛(LR)和人工蜂群(ABC)算法的混合模型，用于解决基于利润的单位承诺问题。在10台24小时试验系统上对该方法进行了试验，并给出了数值结果。仿真结果表明，与现有方法相比，该方法能有效地实现GENCO利润最大化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimal scheduling of generators to maximize GENCOs profit using LR combined with ABC algorithm in deregulated power system

Deregulated power industries increase the efficiency of electricity production, distribution and more reliable electricity at low prices. In a deregulated environment, utilities are not required to meet the total load demand. Generation companies (GENCOs) schedule their generators with an objective to maximize their own profit rather than compromising on social benefit. Profit Unit commitment (PBUC) in deregulated power system has a different objective than that of traditional unit commitment.. This paper presents a hybrid model between Lagrangian Relaxation (LR) and an artificial bee colony (ABC) algorithm, to solve the profit-based unit commitment problem. The proposed approach is investigated on ten units 24 hour test system and numerical results are tabulated. Simulation results shows that this approach effectively maximize the GENCO's profit when compared with existing methods.

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2013 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)

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