Research On The Clearing Mechanism Of Electricity Day-ahead Market

The construction of China ’ s electricity spot market is entering the in-depth promotion stage.Spot market price signal plays a key role in realizing the optimal allocation of power resources,but some spot pilot areas directly use load forecasting data for day ahead market clearing,which leads to the distortion of day ahead market price and is difficult to guide the optimal allocation of power resources.Promoting the construction of bilateral day ahead market is the key to solve the problem of price signal distortion.However,under different market modes,the clearing modes of bilateral day ahead market are quite different.At the same time,under the same market mode,the different mechanism design of each link of day ahead market will also lead to the difference of clearing modes,which will directly affect the final operation results of power market and the optimal allocation mode of power resources.Therefore,in the initial stage of the construction of China’s electricity spot market,it has important theoretical research value and practical significance to study the clearing mechanism of bilateral day ahead market and clarify the impact of mechanism design differences in each link of the day ahead market on the market operation results.This paper first studies the mechanism design of bilateral day ahead market under different market models.Sort out the organization of market-oriented transactions under the centralized market model and the decentralized market model,and study the influence of the choice of market model on the design of the day-ahead market clearing mechanism.Combining with the practice methods of day-ahead market clearing in typical areas of Northern Europe and the United States,and comparing the current situation of day-ahead market construction in China’s spot market pilot provinces,it points out the problems existing in the day-ahead market construction in some pilot provinces.Secondly,this paper studies the differences in the design of the day-ahead market clearing mechanism in the centralized market.The centralized bilateral day-ahead market includes two parts: day-ahead market clearing and Reliability Unit Commitment(RUC).The design differences of the RUC directly affect the way of day-ahead market clearing.Therefore,this paper is based on the design of the US day-ahead market clearing mechanism.First,it sorts out the RUC mechanism design methods in various regions of the United States,refines the key elements of RUC products,constructs corresponding generic models for each key element,and analyze the impact of key elements design differences on day ahead market.Subsequently,combining RUC product practices in the three typical regions of New York,Texas,and California,and based on the generic model,a clearing model for each link of the day-ahead market in each region was established.Finally,through IEEE118 node system,the paper analyzes the multi scene simulation examples,studies the influence of different RUC design methods on the market operation results,summarizes the impact and adaptability analysis.Finally,this paper proposes a clearing mechanism for the joint optimization of day ahead market clearing and RUC.Analyze the defects of the sequential optimization of day ahead market clearing and RUC in the United States at the present stage,puts forward the mechanism of joint optimization of day ahead market clearing and RUC,and establishes joint optimization models for different RUC trading targets,and gives the mathematical derivation formula of price formation mechanism under each joint optimization clearing model,propose a mechanism for the joint optimization of day-ahead market clearing and RUC,and separately establish joint optimization model for each RUC trade mark,and conduct mathematical derivation of the price formation mechanism under each joint optimization model.The multi-scenario simulation arithmetic analysis by IEEE118 node system shows that the joint optimization model can achieve more efficient utilization of power resources,reduce the total power supply cost of the system,and the power purchase cost of market participants.