Research On The Optimal Time Of Use Price Decision Model And Its Impact Based On The Customer Response Mechanism

Time of use(TOU)price strategy induces people to adjust the power consumption behavior by the customer response to the period price difference.A reasonable TOU price model can reduce the fluctuation of load curves and improve the reliability of power system.There are some problems in the study of TOU price,such as the low precision of period partitioning,the TOU price model fails to consider the optimization of power flow distribution and the lack of feedback on period partitioning and price optimization.In view of this,under the support by the National Natural Science Foundation of China(No.51607051)“Research on risk assessment and optimization of active distribution system considering demand response”,this paper takes the optimal TOU price decision model as the research goal which is based on the period partitioning algorithm and TOU price optimization model.The main contents are as follows:(1)The research on the optimal peak-flat-valley period partitioning model based on the moving boundary technique.The typical daily load sequence and reasonable peak-flat-valley period partitioning are necessary for carrying out TOU price optimization.In order to consider the total load of the TOU price formulation cycle,improve the period partitioning accuracy and reduce the period partitioning calculate time,the typical daily load is constructed by averaging loads in time sequence,and an optimal peak-flat-valley period partitioning model based on the moving boundary technique is established with the minimum mean square distance of typical daily load sequence as the objective function in this paper.The proposed model is applied to the reliability test system,and the results show that the model can not only comprehensively consider the load of the TOU price formulation cycle,but also improve the accuracy and efficiency of period partitioning.(2)The research on the influence and optimization of TOU price on the node voltage and active power loss of distribution system.The TOU strategy affects the power consumption which leads to the redistribution of power flow.Therefore,this paper defines the daily node voltage fluctuation and daily active power loss as the evaluation indices for describing the influence of TOU strategy on the node voltage fluctuation and active power loss.The load curves are used to combined with the indices to construct the optimal TOU price decision model considering the node voltage and active power loss of distribution system.The particle swarm optimization algorithm with constriction coefficient is used to complete the optimization of the model.The proposed model is applied to IEEE-14 bus system,and the results show that the method has a great significance on improving the power quality and the economic benefits of electrical distribution system.(3)The research on the optimal TOU price optimization model and customer satisfaction considering bidirectional feedback effect.The traditional TOU price strategy separates the period partitioning and the price optimization in the order of priority,although the results of the former is the input data of the latter,the feedback effect of TOU price optimization on the period partitioning is not considered,which leads to the price optimization results are not globally optimal.Therefore,this paper studies the period partitioning algorithm based on the feedback from price optimization results.Since the traditional satisfaction degree model is only for the single type customer,this paper proposes the satisfaction degree model which considering the load proportion coefficients.The proposed model is applied to the reliability test system,and the results show that the method can not only reduce load fluctuation,enhance power system reliability,but also improve the satisfaction degree of customers.