Ancillary Services Pricing And Cost Allocation Model Of Thermal Power To Promote Wind Power Consumption

Due to the unsustainability of fossil fuels and the environmental pollution caused by them,renewable energy has gradually become the mainstream of energy development and utilization.Wind power develops rapidly in China.By the end of 2016,wind power installed capacity reached 169 million kilowatts,accounting for 9%of the total installed capacity.Due to the fluctuation and anti-peak characteristics of wind power,large-scale wind power grid has also brought about a series of problems,and the high rate of wind abandon has become one of the main factors that impeded the development of wind power.In order to promote the large-scale wind power consumption,it is necessary to ensure that the peak demand of wind power is satisfied.As the main provider of peaking services,the peaking capacity of the thermal power units can be directly related to the actual acceptance of wind power.Therefore,improving the pricing mechanism of ancillary service for thermal power units is very important to motivate the peak load regulation,so as to promote the wind power consumption and ensure a safe and stable operation of the power system.This paper firstly elaborates the current situation of thermal power units involved in ancillary service in domestic and international power markets.It is analyzed that the real reason why the domestic thermal power units are not highly motivated to peak load regulation is that the auxiliary service compensation mechanism is unreasonable and unfair.Based on the theory of electric power market,the market of the ancillary service is established in order to motivate thermal power units,and the thermal power units provide ancillary service by means of competition.In this paper,the traditional uniform clearing mechanism has been improved,and the reliability factor of ancillary service provided by thermal power units has been included in the previous quotation-based sorting rule,and a multi-objective programming optimal purchasing model considering synergistic capacity cost and power system stability is established.According to the optimal solution of each objective,Pareto optimal solution of multi-objective programming problem is obtained by the ideal point method.Then the ancillary service price and purchase cost are obtained based on the solution.On the basis of ancillary service price,questions of who will share the cost of ancillary service and how to share them are studied.This paper mainly analyzes the apportionment between wind farms by analyzing the distribution path of purchase cost.According to the analysis of the smoothing effect that the wind farms will have a certain extent of grid connection at the same time,a cooperative game approach is proposed to make grid-connected wind farms an alliance for cost sharing.A cost-sharing model of ancillary service is established,which is solved by the improved Shapley value method.Taking the different forecasting accuracy,qualification rate and reporting rate of each wind farm into account,the above three parameters are weighted by the entropy weight method to obtain a comprehensive index,that is,the wind power forecasting accuracy index.By using this index,the traditional Shapley value method is amended so that the wind farms with high wind power prediction accuracy can be apportioned appropriately less cost,resulting in a relatively fair apportionment result.At the same time,it has a certain positive impact on promoting the wind farm forecasting accuracy.The research in this paper provides a new idea for the pricing of ancillary services,and improves the discussion on the traditional pricing of quoted prices.It also makes a deeper analysis of the fairness of the cost-sharing,and provides a reference for the construction of ancillary service market in China.