Multiple Entities Game Bidding Optimization For Joint Operation Of Renewable Station And Reserve Resources

The sustainable consumption of wind power is a major problem in our current electric power field.According to the requirements of relevant national policies and the continuous innovation of power market reform,the consumption of wind power generation will be realized in the form of guaranteeing the purchase of electricity and participating in market competition.However,the output power of wind power generation has intermittency,uncertainty and uncontrollability,which is a great challenge to the accuracy and stability of its participation in competitive bidding in the electricity market.In recent years,with the continuous deepening of the research on demand-side user response resources,it has been widely concerned to use them as backup resources to assist new energy to participate in the electricity market.However,what form of Demand Response(DR)resources can assist wind power generation to participate in market bidding,how to match resources between the two,and how to formulate the price mechanism are still a series of extremely challenging problems.Taking wind power producer participating in day-ahead electricity market bidding as the target,this paper establishes wind power producer optimal bidding model with risk quantization and Demand Response Aggregator(DRA)resource optimal scheduling model.Study the interactive mechanism of resource matching between wind power producer and DRA in the bidding process.Firstly,the scientific matching of resources between multiple wind power producers and a DRAs,joint bidding and multi-agent bidding mechanism in the power market are explored.Secondly,further marketized DR Resources,elaborated how to carry out interactive matching of DR Resources when multiple wind power producers and multiple DRAs participate in the electricity market and how to use the game theory method to describe the bidding mechanism of multi-agent wind power producers facing the grid and the non-cooperative pricing mechanism between multi-agent DRAs.The specific research work of this paper is as follows:(1)Aiming at the bidding operation problems of wind power producer in day-ahead and real-time power trading market,this paper studies the bidding strategy of single agent DRA and multi-agent wind power producers jointly participating in the market based on random Cournot game.First of all,based on the classical Cournot game theory,we design the price mechanism of multi-agent wind power producers joint bidding for the electricity market and the price mechanism of positive and negative DR Resources for DR.Secondly,based on Conditional Value-at-Risk(CVa R)method,a distributed optimization model for multi-agent wind power producers and DR Resource joint bid weighing with risk quantification is established.The distributed solution simulation of the model is carried out by using the Alternating Direction Multiplier Method.The effectiveness and rationality of the proposed strategy in various aspects of wind power producer bidding stability and balanced multi-agent interests are verified.The theoretical proof of game equilibrium solution is given.(2)Aiming at the economy and accuracy of resource interaction matching between multiagent wind power producers and multi-agent DRA under the marketization of DR Resources,the joint bidding optimization strategy of multi-agent DRA and multi-agent wind power producers based on Stackelberg multi-master and multi-slave game is studied.Firstly,a twolayer multi-master and multi-slave game framework with multi-agent DRA as the leader and multi-agent wind power producers as the follower is established.In the leadership level,the non-cooperative game method is used to model and analyze the bidding relationship of DR Resources among multi-agent DRA,forming the price mechanism based on the noncooperative game theory.The multi-agent wind power producers in the follower hierarchy decides the purchase amount of DR Resources according to the power difference of bidding quantity in the day-ahead power market and the resource price set by the upper echelon.By using particle swarm optimization algorithm and GUROBI nested optimization algorithm,the model is simulated to solve the distributed solution.The validity and rationality of the proposed strategy in the accuracy of resource matching between multi-agent DRA and multiagent wind power producers and the bidding stability of wind power producer are verified.The theoretical proof of the multi-agent and multi-agent game equilibrium solution is given.