TY - GEN
T1 - An electricity trade model for multiple power distribution networks in smart energy systems
AU - Cui, Tiansong
AU - Wang, Yanzhi
AU - Nazarian, Shahin
AU - Pedram, Massoud
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/29
Y1 - 2014/10/29
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84930987077&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84930987077&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2014.6939261
DO - 10.1109/PESGM.2014.6939261
M3 - Conference contribution
AN - SCOPUS:84930987077
T3 - IEEE Power and Energy Society General Meeting
BT - 2014 IEEE PES General Meeting / Conference and Exposition
PB - IEEE Computer Society
T2 - 2014 IEEE Power and Energy Society General Meeting
Y2 - 27 July 2014 through 31 July 2014
ER -