An enhanced firefly algorithm to multi-objective optimal active/reactive power dispatch with uncertainties consideration

An enhanced firefly algorithm to multi-objective optimal active/reactive power dispatch with uncertainties consideration
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DOI:
10.1016/j.ijepes.2014.09.008
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发表时间:
2015
影响因子:
5.2
通讯作者:
R. Liang;Jia-Ching Wang;Yie-Tone Chen;Wan-Tsun Tseng
R. Liang;Jia-Ching Wang;Yie-Tone Chen;Wan-Tsun Tseng
中科院分区:
工程技术2区
文献类型:
--
作者:
R. Liang;Jia-Ching Wang;Yie-Tone Chen;Wan-Tsun Tseng

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提出了一种改进的萤火虫算法,用于求解具有负荷和风力发电不确定性的多目标有功和无功优化调度问题。同时考虑有功和无功的优化调度。在无功调度中,通过控制变压器有载分接开关的位置、电容器的无功注入量以及备用母线和PV母线的电压来减小线路损耗和负荷母线的电压偏差。在有功调度中,考虑网损的经济调度是为了获得火电机组的有功出力,降低燃料成本。该算法在萤火虫算法的基础上,对萤火虫算法的公式和参数进行了更新和修改,并采用变异策略和局部随机搜索来增强算法的探索和搜索能力。以IEEE 30节点系统为例,验证了该方法在考虑不确定性的多目标有功无功优化调度问题中的有效性。将该方法的结果与其他算法的结果进行了比较。结果表明,该方法比其他算法获得了更有利的解决方案。
This paper presents an enhanced firefly algorithm for solving multi-objective optimal active and reactive power dispatch problems with load and wind generation uncertainties. The optimal dispatches of active and reactive power were considered simultaneously. In reactive power dispatch, the load tap changer positions of transformers, the reactive power injection of capacitors, and the voltages of slack bus and PV buses are controlled to reduce the transmission line losses and the voltage deviations of load buses. In active power dispatch, economic dispatch including losses is used to obtain the active power outputs of thermal generating units and to decrease the fuel costs. The proposed algorithm was based on a firefly algorithm, the formula and parameters of which were updated and modified, and a mutation strategy and local random search were used to enhance the exploration and search capabilities of the algorithm. The IEEE 30-bus system was used to demonstrate the effectiveness of the proposed method for solving multi-objective optimal active and reactive power dispatch problems while considering uncertainties. The results of the proposed method were compared with the results of other algorithms. The results showed that the proposed method achieved a more favorable solution than the other algorithms.