Decision-Making for Electricity Retailers: A Brief Survey

被引:113
作者
Yang, Jiajia [1 ]
Zhao, Junhua [2 ]
Luo, Fengji [3 ]
Wen, Fushuan [4 ,5 ,6 ]
Dong, Zhao Yang [1 ]
机构
[1] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia
[2] Chinese Univ Hong Kong Shenzhen, Shenzhen 518100, Peoples R China
[3] Univ Sydney, Sch Civil Engn, Sydney, NSW 2006, Australia
[4] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China
[5] Univ Teknol Brunei, Bandar Seri Begawan BE1410, Brunei
[6] Elect Power Res Inst, CSG, Guangzhou 510080, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Terms Electricity retail; retail pricing; retail energy forecasting; demand side management; decision-making; EXTREME LEARNING-MACHINE; LOAD DISAGGREGATION; OPTIMAL STRATEGY; SELLING PRICE; POWER GRIDS; MARKET; MODEL; DEMAND; RISK; ENERGY;
D O I
10.1109/TSG.2017.2651499
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the continuous development of smart grid and further restructuring of power industry, modern power systems have been transformed to complex cyber-physical systems characterized with high renewable energy penetrations, distributed facilities, advanced metering, and communication technologies, as well as ever-increasing customer awareness. These new development trends pose significant challenges for electricity retailers and call for innovative decision-making methods. To help researchers and engineers have a better overview of the state-of-the-art on electricity retail decision-making schemes, this paper aims to survey the latest progress on this subject. Some critical and open issues in this field are also discussed.
引用
收藏
页码:4140 / 4153
页数:14
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