| With the rapid development of social economy,the pressure of fossil energy depletion and environmental degradation is increasing.Electric power industry is faced with how to improve the efficiency of electricity production and consumption in order to meet the growing demand for electricity.In our country,with the rapid development of economy and the rapid growth of electricity demand,which further highlight the contradiction between supply and demand,a large number of new power plants are being built around to meet the growing demand for electricity.However,just increasing the generating capacity to meet the demand brings many problems,such as the impact to environmental of large pollutant emissions,increasing generation leading to the insufficient capacity of power grid,etc.Under this background,it is an inevitable trend of power supply system to realize the optimization of supply and demand of power system through demand side management.In the context of the intelligent development of power system,the demand response is considered as an important technical means to realize power supply and demand coordination.However,the introduction of demand response will make the planning,operation and evaluation of smart power system and other aspects to consider the boundary conditions more complexly.And the current research is still unable to effectively support the large-scale application of demand response.Therefore,it is necessary to study the application of demand response resource in smart power system and evaluate the application efficiency of demand response resource in smart power system,so as to formulate appropriate strategies to guide,promote the optimization and upgrading of smart power system,and support the macro strategies of our country's energy revolution.The research content of this paper includes four main parts.One is to put forward the bilateral coordination and optimization of supply and demand theory based on the smart power system framework;the second is studying the smart power system's electric source planning model and coordination planning model of source and network,which consider the demand response;thirdly,the scheduling model of smart power system,which considers the demand response,is constructed;fourthly,this paper puts forward a comprehensive evaluation method,which is used to evaluate the application benefit of demand response in smart power system.Firstly,the theory of bilateral coordination optimization in the framework of smart power system is proposed.The research content is divided into two parts:firstly,using the complex adaptive system theory method to carry out a study on the evolution of smart power system development process,demonstrates the smart power system and the theory of complex adaptive system compatibility,and puts forward the framework of the evolution of complex adaptive system theory under the framework of smart power system;secondly,put forward a theory and method of smart power system of large scale system theory of supply and demand coordination optimization based on the analysis of the applicability of the theory of large scale system of smart power system,and puts forward the basic methods and key technologies of intelligent optimal hierarchical control of power system;reveals the significance and value of demand response optimization and coordination of supply and demand evolution smart power system,the resource application situation and future development trend of demand response in smart power system are analyzed.Second,a planning model of smart power system considering demand response has been built.The study consists of two parts:firstly,a power resource planning model of smart power system considering demand response and typical daily load curve.Optimization model for power supply side constrained by dynamic operation of the generators has been established to minimize the total cost.Based on this,a short time demand response factor considering price elasticity is put forward and be taking as constraint.By modifying the original objective function to maximize the interests of the electricity supplier and the user,the optimal planning model considering the demand response is proposed.The results show that the proposed model can meet the requirements of power generation expansion planning in power market,and promote the integration of renewable energy resources which have intermittent output characteristics.Secondly,the planning model of energy supply and demand network system for small scale area which includes the coordination of energy supply and transmission equipment is built.Benders decomposition optimization algorithm is chosen to solve the model.Through case analysis and simulation,it is proved that the proposed algorithm can be used to formulate a comprehensive planning scheme for the energy supply and demand network in a specific range,including the location and scale of the facilities.Third,a dispatching model of smart power system considering demand response is established.The multi-objective optimization objective function considering the lowest system cost,the highest system reliability and the highest emission reduction rate is designed.The main application scenarios of demand response and distributed power supply,energy storage,large power grid interaction,multi load,etc.are taken into account.A Tent mapping chaos optimization algorithm is used to improve the NSGA-?algorithm so as to solve the model with multi objectives.The case study shows that with the coordinate function of demand response and energy storage,the dispatch strategy presented by the proposed model is able to improve the characteristics of power system,the fluctuation of PV and wind power can be balanced.Fourth,a comprehensive evaluation method is proposed to evaluate the application effectiveness of demand response in intelligent power system.The government from the user side and grid side and the generation side and analyzes the demand response and mechanism of the main body of benefit;constructs the evaluation index system of the comprehensive benefits of demand response;entropy method and variation coefficient method of combination weighting of index system and evaluation model based on the TOPSIS principle was improved by using grey correlation degree and put forward a new comprehensive evaluation model to evaluate the comprehensive benefits of demand response;empirical studies indicate that demand response in the application of intelligent power system can bring social benefit and environment benefit significantly. |
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