全球智库信息集成服务系统(G2TT): Design of the incentive mechanism in electricity auction market based on the signaling game theory.

G2TT

来源类型	Article
规范类型	其他
DOI	10.1016/j.energy.2009.12.036
ISBN	0360-5442
	Design of the incentive mechanism in electricity auction market based on the signaling game theory.
	Liu, Zhen; Zhang, Xiliang; Lieu, Jenny
发表日期	2010-01-08
出处	Energy
出版者	Elsevier
出版年	2010
页码	1813-1819
语种	英语
摘要	At present, designing a proper bidding mechanism to decrease the generators’ market power is considered to be one of the key approaches to deepen the reform of the electricity market. Based on the signaling game theory, the paper analyzes the main electricity bidding mechanisms in the electricity auction markets and considers the degree of information disturbance as an important factor for evaluating bidding mechanisms. Under the above studies, an incentive electricity bidding mechanism defined as the Generator Semi-randomized Matching (GSM) mechanism is proposed. In order to verify the new bidding mechanism, this paper uses the Swarm platform to develop a simulation model based on the multi-agents. In the simulation model, the generators and purchasers use the partly superior study strategy to adjust their price and their electricity quantity. Then, the paper examines a simulation experiment of the GSM bidding mechanism and compares it to a simulation of the High-Low Matching (HLM) bidding mechanism. According to the simulation results, several conclusions can be drawn when comparing the proposed GSM bidding mechanism to the equilibrium state of HLM: the clearing price decreases, the total transaction volume increases, the profits of electricity generators decreases, and the overall benefits of purchasers increases.
URL	http://sro.sussex.ac.uk/id/eprint/73723/
来源智库	Science Policy Research Unit (United Kingdom)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/467671
推荐引用方式 GB/T 7714	Liu, Zhen,Zhang, Xiliang,Lieu, Jenny. Design of the incentive mechanism in electricity auction market based on the signaling game theory.. 2010.