Modeling Method Applied To Load Control Of Cyber Physical Power System

Nowadays,the development of smart grid together with the promotion of energy internet has made the interaction between physical system and cyber system more and more complicated.Modern power system is no longer the conventional power device network;instead,it has evolved into a cyber physical power system,which is also known as CPPS.CPPS can optimize the whole performance of power system by realizing the coordinated operation of computing device,sensing equipment,communicating device,physical equipment,etc.Therefore,coupling models and related analysis methods are imperative for precise description of CPPS objects and flexible representation of CPPS characteristics.For one thing,it is of theoretical value to study the interaction among the complex communication system,the multi-information system and the physical power system in CPPS;for another,it has practical guiding significance to the rational generation of load control strategy for CPPS.Researches on modeling and analysis method applied to load control of CPPS is carried out.To make up for the disadvantages of method segmentation of physical system and information system,this paper takes load control as a breakthrough.Based on different timescale load control modes,modeling and analysis methods for CPPS are explored in both emergency dispatching mode(milliseconds or seconds)and routine dispatching mode(minutes or longer).In emergency dispatching mode,a matrix-based modeling method for CPPS is proposed,together with an emergency load control strategy considering the impact of communication delay.In routine dispatching mode,a multi-information-based aggregation modeling method for CPPS is put forward,as well as a routine load control strategy considering aggregated response potentials.The specific works are as follows.As for the emergency dispatching mode,a matrix-based modeling method for the coupling system is set up to comb and quantify the complex interaction mechanism of information flow and energy flow in the applications of power system control center.In this method,the basic unit of CPPS is abstracted from the actual power system applications.Then,logical association of physical layer,secondary device layer,communication layer and information layer are quantitatively described by the correlation matrix method.Next,the external characteristics of the secondary device nodes and communication nodes are described by expandable multivariate sets.Therefore,a complete CPPS model is formed and the application architecture based on this model is proposed.Finally,the model is verified through an actual power system case study.Based on the matrix-based modeling method for the coupling system,the communication delay in load control system is calculated.Then,the correlation between CPPS communication latency and quantity of load control is studied considering frequency nadir.Next,a fast load control strategy is put forward,with all the aforementioned factors considered.Finally,the strategy is tested through an actual power grid analysis.As for the routine dispatching mode,a multi-information-based load aggregation model is built.When analysing large scale end-user load aggregate response potentials,load physical dynamics,end-user comforts and constraints of response times are taken into consideration.In addition,an equivalent response potential(ERP)index is then created to calculate the potential response capacity quantitatively.The influence of different factors on the aggregate potentials is studied through a case study as well.Based on the aggregate response potentials of large scale active load,a hierarchical control strategy via load aggregator(LA)is proposed,considering both the evaluation of potential response capacity of large-scale residential loads and optimal allocation of response demand to each individual load.In the upper strategy,ERP index is utilized to guide the allocation of total response demand to each LA.In the lower strategy,an optimal allocation model is built to determine the response status of each residential load per minute,ensuring end-user satisfaction and demand response requirements.The aggregate model and control strategy are verified valid through case studies.