Research On Electric Heating Load Aggregation Management To Promote Wind Power Consumption

In recent years,China has vigorously promoted the use of electricity instead of coal.The promotion and application of electric heating can effectively reduce the use of coal resources,help to adjust the structure of terminal energy consumption,improve the proportion of electricity in terminal energy consumption,promote the active consumption of renewable energy such as wind and solar energy,promote energy cleaning and reduce air pollution.However,there are also a series of problems in the large-scale development of electric heating.Firstly,electric heating increases the load of power grid,and the wind power output has greater volatility and uncertainty,which affects the safe and stable operation of power grid.In addition,the cost of clean heating is high,the enthusiasm of ordinary users to use electric heating is low,and the electric heating heat source station also relies on government subsidies.Electric heating load has some flexible characteristics,including the flexible characteristics of heat source and the heating flexibility of users.Through load aggregation,wind power can be further absorbed and the income of participants can be improved.This paper studies the basic concept and system architecture of load aggregator,analyzes the basic policies of domestic auxiliary service market,and puts forward the aggregation mode of centralized electric heating load and decentralized electric heating load.The aggregated electric heating load needs to participate in the power grid dispatching.Due to the uncertainty of wind power,this paper uses Latin hypercube sampling to generate multiple possible wind power output scenarios.In the process of optimal management,a multi-objective optimization model of electric heating dispatching is constructed.The objective function is to minimize the abandoned air volume,the compensation amount,the increased power consumption and the reserve amount.Considering the constraints of electric heating load and power system,the optimal whale algorithm is used to solve the optimization problem.In the example analysis,four scenarios are set in the text,scenario 1 does not consider electric heating load scheduling,scenario 2 considers centralized electric heating load scheduling,scenario 3 considers decentralized electric heating load scheduling,and scenario 4comprehensively considers centralized and decentralized electric heating load scheduling.The example analysis shows that the aggregation management of centralized electric heating load and decentralized electric heating load can improve the wind power consumption capacity of electric heating load.The economic analysis of heat source station and users shows that participating in load aggregation can effectively improve the profitability of electric heating heat source station and improve the anti risk ability;participating in load aggregation can reduce the cost of decentralized heating users and enhance the enthusiasm of users to choose decentralized electric boiler heating.The results of example analysis verify the effectiveness of this model,and provide a reference for the aggregation management of electric heating.