Research On Wind Power Consumption Method Based On Controllable Electric Heating Scheme

Due to the depletion of fossil fuels and the demand for environmental protection,the demand for clean energy is gradually increasing.Wind power,as a well-developed new energy,plays an important role in the power system,but wind curtailment during heating period is serious.In view of wind curtailment,how to effectively reduce redundant wind power is the key to solve the problem.According to the heating characteristics in cold regions,a method is proposed to improve the system’s wind power absorption capacity by controlling the demand side response of the client.In this paper,a scheme which is based on the predicted wind power output designs to absorb wind power by electric heating.Firstly,Markov model,BP neural network and GA-BP neural network were used for wind power generation prediction under incomplete data.To modeling of the wind farm,processing the measured data of wind farm,on the one hand,first-order Markov model is set up under four different space prediction simulations,on the other hand BP neural algorithm is used to train the prediction model of simulation.On this basis,genetic algorithm is used for optimization.The final prediction effect comparing three groups,according to the actual situation to choose the optimal method of wind power.Considering the characteristics of the predicted wind power output and the residents’ comfort requirements for heating in winter,the paper classifies different users’ electricity consumption behaviors,takes the indoor temperature as the regulating lever,and designs a non-interactive distributed electric heating system model to improve the wind power consumption capacity of the system valley by realizing load awakening.By considering the influence of electricity price on users’ electricity behavior,the interactive distributed electric heating system model was established,and the characteristics of the optimization model were comprehensively comparedunder the normal electricity price,time-of-use electricity price and real-time electricity price.On this basis,the temperature control interval and electricity price interval were optimized and the optimal control strategy was determined.Through simulation analysis,the introduction of distributed electric heating system can obviously reduce the wind abandoning phenomenon,and the electricity price lever can effectively affect the load response of the user end.With appropriate temperature control interval and electricity price interval,the wind power absorption capacity of the system will be further improved,which proves the feasibility and effectiveness of the proposed dynamic optimization control strategy.Wind power consumption research on electric heating can improve wind curtailment,and the research in this paper is based on actual operation data of wind farms and actual user load data,so it proves the feasibility and effectiveness of dynamic optimal control strategy for wind power consumption in electric heating system.Research on wind power consumption in electric heating can improve the wind abandoning phenomenon and improve the power economy of power grid.In addition,the research in this paper is based on real meteorological data,wind power output data and user loads in a certain area.Therefore,the experimental results have certain theoretical significance and guiding function for the future research on the consumption of surplus wind power.