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Design of the incentive mechanism in electricity auction market based on the signaling game theory

机译:基于信号博弈理论的电力拍卖市场激励机制设计

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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.
机译:目前,设计适当的降低发电商市场电价的招标机制被认为是深化电力市场改革的关键途径之一。基于信号博弈理论,分析了电力拍卖市场中主要的电力招标机制,并将信息干扰程度作为评估招标机制的重要因素。在以上研究的基础上,提出了一种被称为发电机半随机匹配(GSM)机制的激励性电力竞标机制。为了验证新的出价机制,本文使用Swarm平台开发了基于多主体的仿真模型。在仿真模型中,发电机和购买者使用部分优越的学习策略来调整其价格和电量。然后,本文研究了GSM出价机制的仿真实验,并将其与高低匹配(HLM)出价机制的仿真进行了比较。根据仿真结果,将拟议的GSM竞标机制与HLM的均衡状态进行比较,可以得出以下结论:清算价格下降,总交易量增加,发电机利润减少,购买者的整体利益增加。

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