An electricity trade model for multiple power distribution networks in smart energy systems

Tiansong Cui, Yanzhi Wang, Shahin Nazarian, Massoud Pedram

Research output: Chapter in Book/Entry/PoemConference contribution

1 Scopus citations


The future smart energy systems are projected to be decentralized power networks, each consisting of various types of renewable power generators that serve a small group of energy users. Interaction between different power networks through energy trading over a marketplace provides the chance to fully utilize the capacity of each power generator type. As a result of this interaction, the power generation and distribution levels can be decided for each time slot in order to achieve a maximal utility. In this paper, an electricity trade model is introduced for decentralized power networks to deal with the utility maximization problem. In the proposed model, multiple power networks can trade among each other and thus each of them can achieve a utility increase from making use of its comparative advantage on power generation during a certain period of time. The model is studied from several special scenarios to a more general scenario and an efficient solution is presented for each scenario. Experimental result validates the accuracy and efficiency of the presented solutions.

Original languageEnglish (US)
Title of host publication2014 IEEE PES General Meeting / Conference and Exposition
PublisherIEEE Computer Society
ISBN (Electronic)9781479964154
StatePublished - Oct 29 2014
Externally publishedYes
Event2014 IEEE Power and Energy Society General Meeting - National Harbor, United States
Duration: Jul 27 2014Jul 31 2014

Publication series

NameIEEE Power and Energy Society General Meeting
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933


Other2014 IEEE Power and Energy Society General Meeting
Country/TerritoryUnited States
CityNational Harbor

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering


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