Research On Electricity Consumption Analysis And Optimization Of Residential Users

The rapid economic development has resulted in a significant increase in the total power consumption of the society.The burden of the power system has been increased during peak time.Demand-side management is one of the important methods of power system peak cutting.How to effectively implement demand-side management has become an urgent problem.Residential user is one of the main bodies of implementing demand-side management.Studying residential user’ electricity consumption characteristics,analyzing their demand response potential and optimizing their electricity consumption patterns can not only help users save energy and reduce consumption but also provide a reference for the power grid to make demand response plans.In this thesis,residential user’s electricity consumption behavior is studied and a demand response potential assessment model is established and the electricity consumption pattern is optimized.The main work of this thesis can be summarized as the following three parts:(1)The basic framework of residential electricity consumption analysis is given,the factors affecting the residential user load are analyzed and the typical residential load characteristics are summarized.Firstly,the basic framework of residential electricity consumption analysis is introduced,including data acquisition,data processing and data analysis.Secondly,the influencing factors of load characteristics are studied from two aspects of natural factors and social factors and the characteristics of load of residents are summarized.Finally,the load characteristics of typical household appliances such as washing machines,dryers and air conditioners are introduced.(2)An evaluation model of demand response potential for residential users is established and a method for calculating response potential is provided.First,the relevant theories of demand response potential are introduced,including demand response technology,power demand-side resources and the concept of demand response potential.Then,for the electricity consumption equipment of residential users,the demand response potential calculation index is designed and the demand response potential calculation method and specific analysis scenario are given from the two aspects of peak cutting potential and valley filling potential.Finally,taking a user’s actual power consumption as an example,the demand response potential of different seasons and different working days is analyzed.(3)A Complex-PSO algorithm is proposed and the electricity consumption behavior of residential users is optimized based on this method.Firstly,the load model is established by classification.Secondly,the electricity consumption optimization model of residential users considering alternative energy is established.Economy and satisfaction is considered comprehensively in this model with maximum load constraints.Then,the Particle Swarm Algorithm is used to improve the performance of Complex Method.An improved algorithm called Complex-PSO algorithm is proposed.Aiming at the problem of inconsistent optimization variable types,a three-stage approach was used to solve the model.Finally,the applicability of the proposed algorithm to the optimization model is verified.The work presented in this thesis can not only provide a certain reference for the power enterprise to make a demand response plan but also provide ideas for energy saving of residential users.