TY - JOUR
T1 - Multi-agent optimal allocation of energy storage systems in distribution systems
AU - Zheng, Yu
AU - Hill, David J.
AU - Dong, Zhao Yang
N1 - Funding Information:
Manuscript received September 1, 2016; revised December 25, 2016, March 9, 2017, and May 5, 2017; accepted May 9, 2017. Date of publication May 18, 2017; date of current version September 15, 2017. This work was supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region under Theme-Based Research Scheme through Project T23-701/14-N. Paper no. TSTE-00647-2016. (Corresponding author: Yu Zheng.) Y. Zheng is with the Department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong (e-mail: [email protected]).
Publisher Copyright:
© 2010-2012 IEEE.
PY - 2017/10
Y1 - 2017/10
N2 - A variety of optimal methods for the allocation of a battery energy storage system (BESS) have been proposed for a distribution company (DISCO) to mitigate the transaction risk in a power market. All the distributed devices are assumed to be owned by the DISCO. However, in future power systems, more parties in a distribution system will have incentives to integrate BESS to reduce operational cost. In this paper, an enhanced BESS optimal allocation method is proposed for multiple agents in a distribution system. First, the electricity market mechanism is extended to a distribution system, and the corresponding energy transaction process is modeled for different agents, such as wind farms, solar power stations, demand aggregators, and the DISCO. The uncertainties of renewable energy and demand are addressed using stochastic methods. In the proposed transaction model, the integration of BESS can help an agent to reduce the operational cost, also defined as the payoff function. Next, game theory is introduced in this paper to investigate the interactions among the agents and to determine the BESS integration plans. The agents are built as players who are willing to minimize their payoff functions in the proposed non-cooperative game. The Nash equilibrium, which is the best strategy for the players, is proved to exist. Such equilibrium can be solved using an iterative algorithm. The proposed BESS allocation method for the multi-agent system is verified for two cases, and the payoff reductions are quantified based on the proposed distribution energy transaction mechanism.
AB - A variety of optimal methods for the allocation of a battery energy storage system (BESS) have been proposed for a distribution company (DISCO) to mitigate the transaction risk in a power market. All the distributed devices are assumed to be owned by the DISCO. However, in future power systems, more parties in a distribution system will have incentives to integrate BESS to reduce operational cost. In this paper, an enhanced BESS optimal allocation method is proposed for multiple agents in a distribution system. First, the electricity market mechanism is extended to a distribution system, and the corresponding energy transaction process is modeled for different agents, such as wind farms, solar power stations, demand aggregators, and the DISCO. The uncertainties of renewable energy and demand are addressed using stochastic methods. In the proposed transaction model, the integration of BESS can help an agent to reduce the operational cost, also defined as the payoff function. Next, game theory is introduced in this paper to investigate the interactions among the agents and to determine the BESS integration plans. The agents are built as players who are willing to minimize their payoff functions in the proposed non-cooperative game. The Nash equilibrium, which is the best strategy for the players, is proved to exist. Such equilibrium can be solved using an iterative algorithm. The proposed BESS allocation method for the multi-agent system is verified for two cases, and the payoff reductions are quantified based on the proposed distribution energy transaction mechanism.
KW - Distribution system
KW - electricity markets
KW - energy storage system
KW - game theory
KW - multi-utilities
KW - renewable energy
UR - https://www.scopus.com/pages/publications/85030151732
U2 - 10.1109/TSTE.2017.2705838
DO - 10.1109/TSTE.2017.2705838
M3 - Article
AN - SCOPUS:85030151732
SN - 1949-3029
VL - 8
SP - 1715
EP - 1725
JO - IEEE Transactions on Sustainable Energy
JF - IEEE Transactions on Sustainable Energy
IS - 4
ER -