Research On Static Parameter Detection And Identification Of Power Grid Branch Based On SCADA Measurement

With the rapid economic growth,the structure of power grid is becoming increasingly large and complex,and the requirement for safe,economic and stable operation of power grid is further improved.The importance of EMS system for power grid dispatching center is self-evident.As the core component of EMS system,state estimation is the basis of other advanced applications,and directly affects the intelligent analysis and decision-making of power grid dispatching.Correct network parameters not only directly affect the results of state estimation,but also provide an important basis for realizing automatic operation of power grid.However,the parameter data stored in EMS system always deviates from the actual network parameters for some reasons.Therefore,it is of great significance to study the detection and identification algorithm of the static parameters of power network branches to provide reliable basic data support for EMS system.According to the characteristics of SCADA measurement system and the types of measurement data,this paper proposes a static parameter detection and identification algorithm for power network branch based on SCADA measurement.The parameter detection process based on Lagrange multiplier method is carried out in the whole network.Then,the suspected branch is taken as the center,and the local part network is formed by searching outward.The parameter identification and correction process is running on the local area.For the spatial dimension,by taking parameters into the state space,the measurement equations with parameters as state vector are derived according to various types of SCADA measurement.The trusted parameters are added to the measurement equation as pseudo-measurement,which improves the measurement redundancy.On this basis,a fixed point iteration scheme with parameters as state vector is established based on the weighted least squares estimation of voltage,and the two nested iteration estimation process for network parameters is illustrated.For the time dimension,two different processing strategies are proposed for multiple history measurement section data.For each processing strategy,the specific application of the parameter detection and identification algorithm proposed in this paper using multi-section measurements is described in detail.Finally,taking the IEEE 118-bus test system as an example,the effectiveness of the proposed algorithm is verified,and the influence of measurement noise and bad data against the identification algorithm is discussed.