DocumentCode :
3439986
Title :
Optimal management of local energy trading in future smart microgrid via pricing
Author :
Yuan Wu ; Xiaoqi Tan ; Liping Qian ; Tsang, Danny H. K.
Author_Institution :
Coll. of Inf. Eng., Zhejiang Univ. of Technol., Hangzhou, China
fYear :
2015
fDate :
April 26 2015-May 1 2015
Firstpage :
570
Lastpage :
575
Abstract :
In this paper, we investigate optimal management of local energy trading in future smart micro-grid (SMG) via pricing. In SMG, energy consumers and providers, in addition to trading with utility company, can also perform local energy trading controlled by a local trading manager (LTM) for reaping benefits. We first quantify the benefits achieved by the consumers and providers from local trading and then formulate a two-layered optimization framework to investigate i) how the energy consumers and providers maximize their benefits via appropriately adjusting their local trading decisions in response to the LTM´s pricing, and ii) how the LTM adjusts its price in local market to benefit the consumers and providers as much as possible while guaranteeing a required gain for itself. We propose two algorithms to solve the layered optimization problem and perform numerical experiments with practical data set to validate the proposed local trading model and the algorithms.
Keywords :
distributed power generation; optimisation; power system management; LTM; SMG via pricing; energy trading; local trading manager; optimization framework; optimization problem; smart microgrid via pricing; utility company; Algorithm design and analysis; Companies; Conferences; Niobium; Numerical models; Optimization; Pricing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Communications Workshops (INFOCOM WKSHPS), 2015 IEEE Conference on
Conference_Location :
Hong Kong
Type :
conf
DOI :
10.1109/INFCOMW.2015.7179446
Filename :
7179446
Link To Document :
بازگشت