Wind-thermal power system dispatch using MLSAD model and GSOICLW algorithm

详细信息    查看全文

• 作者：Y.Z. Li ; ^a ; ^b ; ^c ; ^{Yuanzheng_Li@hust.edu.cn} ; L. Jiang^d ; Q.H. Wu^d ; P. Wang^e ; H.B. Gooi^b ; K.C. Li^a ; Y.Q. Liu^c ; P. Lu^f ; M. Cao^g ; J. Imura^h
• 关键词：Power system dispatch ; Wind power ; Profit ; Downside risk ; Optimization algorithm
• 刊名：Knowledge-Based Systems
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：116
• 期：Complete
• 页码：94-101
• 全文大小：824 K
• 卷排序：116

文摘

The decision support model of mean-lower semi-absolute deviation (MLSAD) and the optimization algorithm of group search optimizer with intraspecific competition and lévy walk (GSOICLW) are presented to solve wind-thermal power system dispatch. MLSAD model takes the profit and downside risk into account simultaneously brought by uncertain wind power. Using a risk tolerance parameter, the model can be converted to a single-optimization problem, which is solved by an improved optimization algorithm, GSOICLW. Afterwards, both the model and the algorithm are tested on a modified IEEE 30-bus power system. Simulation results demonstrate that the MLSAD model can well solve wind-thermal power system dispatch. The study also verifies GSOICLW obtains better convergent dispatching solutions, in comparison with other evolutionary algorithms, such as group search optimizer and particle swarm optimizer.