Research On Trading Strategies Of Flexible Load Aggregator Participating In Renewable Energy Dissipation In Grid

In recent years,with the continuous development of the power industry and the continuous expansion of the scale of renewable energy,serious abandonment of wind and light has occurred in China.In order to solve the problem of renewable energy consumption in the power grid,it is difficult to continue from the power generation side alone,and the demand-side response potential should be fully tapped.Flexible load aggregator(FLA),as a new generation of operating entities participating in the electricity market transaction,provides new research ideas for the consumption of renewable energy.The FLA can negotiate with renewable energy power producers on the transaction price of energy consumption through bilateral transactions,and sign power purchase contracts,thereby achieving the purpose of energy consumption.This article starts with solving the problem of renewable ene rgy consumption,and studies FLA’s bidding strategy for bilateral transaction negotiations.The main work and research results are as follows:(1)Summarized the mechanism of FLA’s participation in the electricity market to consume renewable energy in the bilateral trading market,analyzed the types of bilateral trading methods of FLA in the electricity market.Considering the development status of China’s power industry,the article introduced the market members of bilateral contract transactions and their functions,negotiation methods,settlement methods and transaction processes of bilateral contracts;the effects of different transaction environments and negotiation costs on FLA trading strategies and the trading strategies that FLA can take are studied.(2)A FLA fuzzy Bayesian learning model based on discount factor is established,and examples show that the strategy can significantly reduce the number of negotiations,save negotiation costs,and maximize the benefits of FLA.In this model,in response to the uncertainty of the trading envir onment and the incompleteness of information disclosure,FLA estimates uncertain information based on fuzzy probability theory.Considering that the FLA can continuously obtain the exact quote information of the counterparty during the transaction process,a fuzzy Bayesian learning model is established to correct the fuzzy estimation bias for uncertain information.Takes into account the effect of negotiation cost loss on trading strategies,and introduces a discount factor to adjust the FLA’s own reserve price.(3)In the bilateral trading model including multi-agent,a FLA bilateral trading strategy model based on an improved discount factor is established,The validity of the model is verified by an example.At the same time,it is analyzed that FLA can reduce the overall transaction price and maximize its own revenue by rationally setting the number of subagents.In this model,a multi-agent FLA bilateral transaction model is constructed taking into account the ever-expanding transaction volume and the risk of failure in the transaction.A discount factor is introduced into this type of bilateral transaction model based on the number of rounds of negotiation,the degree of completion and The own transaction price improves the traditional discount factor so that the FLA sub-agents can adjust their quote behavior in real time by sharing information with each other.