TY - JOUR
T1 - Distributed energy trading for an integrated energy system and electric vehicle charging stations
T2 - A Nash bargaining game approach
AU - Wang, Yifei
AU - Wang, Xiuli
AU - Shao, Chengcheng
AU - Gong, Naiwei
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/8
Y1 - 2020/8
N2 - The increasing concerns of energy utilization and climate change have promoted the permeation of various smart energy subsystems on the distribution level, such as integrated energy systems (IESs) and electric vehicle charging stations (EVCSs). These subsystems typically act separately during operation and their transaction values have not yet been well investigated. In this paper, we propose an energy trading model based on the Nash bargaining game to study cooperative benefits between an IES and several EVCSs. The proposed model not only considers individual interests, but also enables the players to fairly benefit from cooperation. In particular, the uncertainties of the market prices, renewable energies and integrated demand response are considered. To ensure that the entire game is computationally tractable, the original problem is decomposed into a major energy trading problem and an additional payment bargaining problem. Furthermore, a distributed algorithm based on modified Benders decomposition is used to overcoming the players’ privacies. The results show the considerable benefits where the costs of the IES may be reduced by 3.89% and the profits associated with the EVCSs may be increased by at least 7.8%. The proposed algorithm is proven to be able to find the optimal global solutions efficiently and accurately.
AB - The increasing concerns of energy utilization and climate change have promoted the permeation of various smart energy subsystems on the distribution level, such as integrated energy systems (IESs) and electric vehicle charging stations (EVCSs). These subsystems typically act separately during operation and their transaction values have not yet been well investigated. In this paper, we propose an energy trading model based on the Nash bargaining game to study cooperative benefits between an IES and several EVCSs. The proposed model not only considers individual interests, but also enables the players to fairly benefit from cooperation. In particular, the uncertainties of the market prices, renewable energies and integrated demand response are considered. To ensure that the entire game is computationally tractable, the original problem is decomposed into a major energy trading problem and an additional payment bargaining problem. Furthermore, a distributed algorithm based on modified Benders decomposition is used to overcoming the players’ privacies. The results show the considerable benefits where the costs of the IES may be reduced by 3.89% and the profits associated with the EVCSs may be increased by at least 7.8%. The proposed algorithm is proven to be able to find the optimal global solutions efficiently and accurately.
KW - Distributed algorithm
KW - Electric vehicle charging stations
KW - Integrated energy systems
KW - Nash bargaining theory
UR - https://www.scopus.com/pages/publications/85082764584
U2 - 10.1016/j.renene.2020.03.006
DO - 10.1016/j.renene.2020.03.006
M3 - 文章
AN - SCOPUS:85082764584
SN - 0960-1481
VL - 155
SP - 513
EP - 530
JO - Renewable Energy
JF - Renewable Energy
ER -