干旱区生态环境知识资源中心(Arid): Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution

Arid

DOI	10.1016/j.engappai.2019.01.013
	Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution
	He, Zhongzheng ; Zhou, Jianzhong 1; Qin, Hui ; Jia, Benjun ; Lu, Chengwei
通讯作者	Zhou, Jianzhong
来源期刊	ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
ISSN	0952-1976
EISSN	1873-6769
出版年	2019
卷号	81 页码:1-13
英文摘要	Hydropower as renewable, clean and cheap energy occupies a considerable share in power energy production. With more and more hydropower stations being established and involved in joint operation, long-term joint scheduling of hydropower station group (LJSHSG) has become a challenging constrained optimization problem, because of its characteristics of high dimension, nonlinearity and coupling. In order to deal with this problem effectively, the partition parameter adaptation differential evolution (PPADE) is put forward based on success-history based adaptive differential evolution (SHADE). PPADE uses a new mutation strategy current-to-pbest/U-Ip, which is improved with relaxing the index restrained condition and linearly decreased region of control parameter p with large initial value based on current-to-pbest/1 to prevent premature convergence. In addition, the partition parameter adaptation divides the population in descending order according to fitness and entry set into C partition so that each population partition corresponds to a partition of entry set for enhancing exploitation by faster and better boot parameter update in PPADE. Then numerical experiments of 10 benchmark functions in high dimension and low dimension have been done, it shows that PPADE with above improvement has stable convergence and high efficiency. With the PPADE compared with other improved DE algorithms in the LJSHSG problem of four completed hydropower stations, Xiluodu, Xiangjiaba, Three Gorges and Gezhouba, in the upper reaches of the Yangtze River, PPADE increases the power production compared to SHADE, EPSDE, CoDE and LSHADE in average best benefit by 9.06, 17.09, 35.69, 69.67 x 10(8) kWh in wet year. It demonstrates that PPADE has stable and efficient convergence to be a useful and reliable tool for LJSHSG problem. Then two hydropower stations under construction, Wudongde and Baihetan, are add into consideration to analysis compensation benefit of hydropower station group (HSG). The increments of the power production in the situation with Wudongde and Baihetan over without Wudongde and Baihetan on power production of four completed hydropower stations are 106.44 x 10(8) kWh, and decrements on deserted water of four completed hydropower stations are 14.22% in wet year. The result shows that joint operation of six hydropower stations and can significantly improve the power generation by reducing the spill water in four completed hydropower stations because of the increased regulation capacity from two hydropower stations under construction in the upper reaches of the Yangtze River.
英文关键词	Long-term scheduling Hydropower station groups Differential evolution algorithm Joint operation Parameter adaptation
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000468721700001
WOS关键词	ALGORITHM ; OPTIMIZATION ; OPERATION ; ENERGY ; GENERATION ; STORAGE
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Engineering, Multidisciplinary ; Engineering, Electrical & Electronic
WOS研究方向	Automation & Control Systems ; Computer Science ; Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215372
作者单位	1.Huazhong Univ Sci & Technol, Sch Hydropower & Informat Engn, Wuhan 430074, Hubei, Peoples R China; 2.Hubei Key Lab Digital Valley Sci & Technol, Wuhan 430074, Hubei, Peoples R China
推荐引用方式 GB/T 7714	He, Zhongzheng,Zhou, Jianzhong,Qin, Hui,et al. Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution[J],2019,81:1-13.
APA	He, Zhongzheng,Zhou, Jianzhong,Qin, Hui,Jia, Benjun,&Lu, Chengwei.(2019).Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,81,1-13.
MLA	He, Zhongzheng,et al."Long-term joint scheduling of hydropower station group in the upper reaches of the Yangtze River using partition parameter adaptation differential evolution".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 81(2019):1-13.