Research On Optimization Strategy Of User Side Step Time Of Use Price

With the rapid development of China’s economy,people’s demand for electricity is also increasing year by year.Due to the large difference of power demand in various industries,the current power consumption situation in China is characterized by large power consumption in peak period,small power consumption in valley period and extremely unbalanced power demand in each period,which leads to the failure of safe and stable operation of power grid.The peak valley TOU(Time of use)price policy alleviates the serious fluctuation of power grid load to a great extent and improves the stability of power grid operation.However,the traditional peak valley time of use TOU pricing policy has some problems,such as inaccurate peak valley time division,imperfect pricing mechanism and so on.Therefore,in view of the existing shortcomings,this paper makes an in-depth study,and the specific work is as follows:1.Aiming at the problem of imprecise peak valley time division,a seasonal peak valley time division strategy based on improved fuzzy c-means clustering algorithm is proposed.Firstly,the annual load data is preprocessed;then the processed annual load data is divided according to the principle of season division,and the seasonal load curve is established;finally,the improved fuzzy c-means clustering algorithm is used to divide the peak and valley periods of seasonal load curve.The simulation results show that this strategy can divide the peak valley period more accurately,laying a foundation for the determination of peak valley TOU price.2.Aiming at the imperfect pricing mechanism of peak valley time of use TOU price,an optimization strategy of peak valley step TOU price based on Eagle Colony Algorithm and considering the income of power suppliers is proposed.Firstly,a mathematical model of time of use TOU price is established,which is based on consumer psychology,takes the minimum peak valley difference as the objective function,and satisfies the interests of users and power suppliers at the same time.Then,a ladder TOU price system is established based on the TOU price.Finally,the model is solved by the Eagle Colony Algorithm.The experimental results show that this method not only effectively reduces the peak valley difference,improves the overall load rate,but also reduces the total electricity expenditure of users,and ensures the basic income of the power supply company.3.Aiming at the contradiction between the two objectives of improving customer satisfaction and reducing peak valley difference,a multi-objective peak valley step TOU price optimization strategy based on MOPSO algorithm is proposed.Firstly,a multi-objective TOU price model is established,and then MOPSO algorithm is used to solve the model.The simulation results show that the strategy can obtain the optimal compromise solution that minimizes the peak valley difference while maintaining the maximum customer satisfaction.The optimal compromise solution can meet the needs of users and power suppliers to the maximum extent,so as to achieve a win-win situation.