Research On Comprehensive Scheduling Strategy For Residential Load Response Resources

With the gradual deepening of the reform of China’s power market,electricity customers are no longer the traditional role of the simple consumer,but was given the identity of important participants in a competitive market,and plays an important role to ensure system security and Economic operation through the implementation of demand response to power customers.In the traditional user classification,compared with industrial and commercial consumers,residential c onsumers have the characteristics of spatial dispersion,small power,large quantity and various kinds of appliances,so that the appliances of the resident consumers has the potential great advantage and the difficulty of control in the course of participating in the demand response.In this context,this paper aims at the comprehensive optimization scheduling strategy of resident consumers’ response resources as follows:Firstly,the classification method of residential response resource is proposed.By contrasting and summarizing the traditional load classification methods,the paper analyzes the physical characteristics and electrical characteristics of residential appliances,the impact and constraint of residential users’ behavior on electricity consumption,classifies the response resource of reside nts’ appliances,and builds their electricity consumption models,which provides the model foundation for the control strategy research of resident load.And then,the control strategy of the resident consumers’ response resource is studied.Based on the classification method of residential resource,the control patterns of response resource is studied.Then,according to the different types of loads and their control characteristics,the types of demand response that each kind of load can participate in are proposed.The control strategy of load response to demand is analyzed,and the corresponding response model is established.The object of optimization is the power of all kinds of appliances.The objective function of optimization is to minimize the electricity cost and reduction of the comfort,and normalize it.And the mixed integer linear programming algorithm is used to solve the model.By comparing the optimization results that participate in the incentive-based DR and the price-based DR,the user chooses to participate in one of the two for all types of load.Finally,the comprehensive scheduling strategy of residential consumers’ participation in demand response is studied in this paper.Through analyzing the control strategy of the residents ’response to the resources,the potential value of the residents’ participation in the demand response and the maximum reduction load power of each kind of appliances are obtained.And the demand response potential value matrix for different users and different periods is constructed.The load reduction orders issued by the system are allocated to each residential consumer through the demand response potential value matrix,and the reduction load of each appliance is further allocated to the various load respons e resources of the user according to the minimum degree of the reduction of electricity consumption comfort.The cooperative game alliance between the resident consumers and the load aggregator is constructed,and the demand response compensation is distri buted to each resident user according to the result of the load distribution and the Shapely Value of each consumers.