Paper Info
Title
Optimal Management Of Local Energy Trading In Future Smart Microgrid Via Pricing
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.
Year
Venue
Field
2015
2015 IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS)
Trading strategy,Mathematical optimization,Algorithm design,Numerical models,Computer science,Optimal management,Smart microgrid,Optimization problem,Energy trading
DocType
ISSN
Citations 
Conference
2159-4228
0
PageRank 
References 
Authors
0.34
8
4
Name
Order
Citations
PageRank
Yuan Wu153861.11
Xiaoqi Tan29114.79
Li Ping Qian352949.54
Danny H. K. Tsang494595.24