Evaluation And Application Of Residents' Demand Response Potential Under Time-of-use Electricity Pricing Environmen

The wide access of renewable energy brings more randomness and volatility to the power supply,which challenges the stable operation of the power system.Demand side response plays an important role in the operation and management of smart power grid.Among them,peak valley TOU plays a significant role in peak cutting and valley filling,stable load and so on.It is very necessary to implement TOU and formulate corresponding price policies.By assessing the demand response potential of users,formulate reasonable price policies to stimulate the response potential of users,guide users to scientifically change their way of using electricity,and play a positive role in the safe and stable operation of the power system.First,the theory of demand side response and TOU is discussed.Based on the theory of demand elasticity in economics,the price elasticity matrix of demand is established and modified.Considering the consumer psychology to analyze the sensitive area of electricity price change,the load transfer model of users under the guidance of TOU price is constructed.Secondly,a comprehensive demand response potential index combining the demand response potential and response speed of users is established,and the demand response potential of residents is evaluated by the load transfer model of users.The effects of different pricing policies on response potential are discussed.Then,the method of fuzzy membership degree and fuzzy clustering is used to divide the power consumption period of the load curve.The objective of peak-valley TOU price is described,and a multi-objective optimization model of peak-valley TOU price is established considering multiple constraints.The Ant lion algorithm is introduced and improved,and its effectiveness is verified on single objective and multi-objective test functions,and the solving process of the model is given.Finally,an example is given to verify the model.Firstly,the optimization model of peak-valley TOU was solved to obtain the results.Secondly,the peak-valley inversion constraint conditions were described and the constraint was added to the model for solving,and its influence on the results was compared.Then,the peak-valley inversion constraint was added into the optimization model,and the optimal electricity price under different conditions was solved considering the combination of different objectives and satisfaction with electricity consumption,and different optimization results were compared.Considering the absorption of PV,the equivalent curve is obtained by combining the load curve with the PV output,and the optimal TOU price is obtained by optimizing the equivalent curve considering the PV absorption.Secondly,Based on the combination of demand response potential and response speed of users,establish a comprehensive demand response potential index,and the demand response potential is evaluated by the load transfer model of users.This paper discusses the influence of different electricity price policies and electricity consumption time division on the response potential and compares the demand response potential of different users.Then,the method of fuzzy membership degree and fuzzy clustering is used to divide the power consumption period of the load curve.The multi-objective optimization model of peak-valley TOU price was established by taking into account the actual conditions of users and the power supply side.Describe the solution flow of NSGA-Ⅱ algorithm and model.Finally,the model is verified by solving an example.Firstly,the peak-valley TOU optimization model established in the previous section is solved to obtain the results.Secondly,the peak-valley inversion constraint conditions are described and the constraint is added to the model for solving,and its influence on the results is compared.Then,the peak-valley inversion constraint is added into the optimization model,and the Pareto optimal solution set under different conditions is solved,and the compromise optimal solution of the solution set is calculated,and the TOU tariff policy under this goal is obtained.