Wind-thermal Generation Coalition Formation And Bidding Strategy In Electricity Spot Market

Non-water renewable energy,represented by wind power,has been developed rapidly with the promotion of countries all over the world because of its clean,low-carbon,and environmental protection characteristics.It is the policy orientation for the development of renewable energy in the future to promote non-subsidy integration of renewable energy generation and give play to the decisive role of the electricity market in resource allocation.Also,it is an inevitable requirement of the electricity market reform.Renewable energy power has severe uncertainty,leading to a market bidding deviation in the electricity spot market.The deviation will increase market balance cost,bring market risk,and weaken the competitiveness of renewable energy like wind power.At present,the development of the electricity spot market in China is in a primary stage.It can reduce the bidding risk of wind power to participate in the spot market through combined bidding with controllable resources such as thermal power units.The competitiveness and enthusiasm of wind power participating in the market can be improved.However,wind-thermal combined bidding strategy is a kind of risk-sharing behavior in the spot market.Thus,the feasibility of combined bidding will be affected when the risk propensities of power generation stakeholders are different.At the same time,it should be further clarified how to form the optimal coalition when wind power and thermal power units belong to different stakeholders.In addition,considering the accuracy difference of wind power prediction at different time scales of day-ahead and intraday,a multi-stage market transaction strategy should be developed to ensure the market performance of the wind-thermal coalition.Finally,considering the mathematical characteristics of the bidding model,it is necessary to study the suitable optimization algorithm.This thesis studies the optimal coalition formation and the combined bidding strategy for a wind farm and multi-stakeholder thermal power units.In order to study the influence of power generation stakeholders’ risk propensities on the combined bidding strategy and its feasibility,robust and opportunity models are established.Based on the information gap decision theory(IGDT),the separate and the combined bidding strategies for the wind farm and thermal power units in the day-ahead spot market are considered in the face of uncertain market parameters.The risk feasibility evaluation index is proposed based on the fluctuation range of uncertain variables for different combination forms of stakeholders.At the same time,the economic feasibility standard based on Kaldor-Hicks efficiency is used to reflect the economic feasibility region,providing a strategic basis for the optimal coalition structure formation of combined bidding.In order to obtain the optimal bidding coalition form of a wind farm and multi-stakeholder thermal power units,a coalition-utility-oriented sequential coalition structure formation method and a corresponding combined bidding strategy are proposed.The coalition structure graph is introduced into the field of combined bidding in power systems.The combination relationship of a single wind farm and multi-agent thermal power units is described using the star graph.Moreover,the technique for order preference by similarity to ideal solution(TOPSIS)is used to prioritize the alternative coalition structure.The multiple evaluation criteria,including the revenue,the wind power accommodation,the imbalance penalty,and the carbon emission,are considered.As the coalition structure graph is simplified,the retrieval quantity of coalition structures is reduced.A day-ahead robust bidding strategy is developed under the objective orientation of comprehensive utility maximization in the day-ahead market,and the fast optimal coalition formation for wind-thermal combined bidding can be realized.In order to realize the strategic connection between the day-ahead market bidding and the intra-day operation for the wind-thermal coalition,ensuring the performance of the self-scheduling,a rolling correction strategy for the wind-thermal coalition is proposed on the basis of the intra-day market transaction.Aiming to maximize the total utility of the day-ahead and the intra-day bidding,the deviation between the day-ahead bidding and the ultra-short-term prediction results is corrected in the intra-day market using the bilateral matching trading method.The rolling correction strategy can provide a connection scheme between the day-ahead market bidding and the intra-day operation,reducing the amount of self-scheduling deviation between the electricity market bidding and the physical operation.Therefore,the feasibility of spot market bidding can be carried out physically,ensuring the implementation of the market contract for the wind-thermal coalition.In order to solve the combined bidding optimization model with discontinuity points,a dual fitness value-based chaotic particle swarm optimization algorithm with constraints handling is proposed.The solution functions of parametric equations are used to deal with the equality constraints in the model to ensure that the equality constraints are satisfied.A dual fitness function is constructed to deal with inequality constraints and is used as a criterion for selecting the quality of particles.Also,the particle population was mutated based on chaotic Cat mapping in the iterative process to improve population diversity and avoid particle premature.The test results of the mathematical test function and engineering model show that the proposed algorithm performs well in both feasible region search and optimal solution search.