Research On Load Modeling Based On On-line Data

The digital simulation of power system is the main tool for power system planning、 design and operation. The accuracy of simulation results is important for the safety, reliability and economic operation of the power system. As the basis of digital simulation, the accuracy of the load model is a great impact on the simulation results. However, due to the complexity, dispersion and randomness of the load itself, the research of the load modeling is always a difficult problem in power field. This paper discusses some problems in the process of load modeling.Sufficient data are the basis of the load modeling. This paper compares several access methods of the required data for load modeling, including the load measurement device, SCADA, WAMS, FRMS. With the development of fault recording technology, propose using the widespread fault recording device for load modeling, not only small investment and a lot of fault recorder data can be fully applied. This way can effectively solve the time-variation and geographic dispersion problem of the load.The traditional statistical synthesis method, steady state test method for static load modeling is limited to carrying out regularly, unable to solve the time-variation problem of the load. The on-line static load modeling is proposed on the basis of steady-state data of the fault recording device in the paper. Combining with the statistical synthesis method, classify according to the time characteristic, form the load model parameter library of the corresponding types, then according to the corresponding real-time data using the recursive least squares method correct the parameters of each model library on-line, obtain load models under different time scales, so it can be convenient for the user to choose models according to need and can effectively solve the time-variation problem of the load. Simulating with the summer typical daily data from Ri-Zhao, the results show that the proposed method is correct and effective.For dynamic load modeling, aiming at the time-varying, studies were focused on the classification and comprehensive method. However, this method did not study on the effect of classification from the view of application with the load characteristic, moreover this method cause difficulty in practical application. The on-line dynamic load modeling is proposed on the basis of disturbance data of the fault recording device in the paper, using the same modeling method with online static load modeling. For the parameters correction of the dynamic load model, the method of recursive correction load modeling based on incremental learning is proposed in the paper. On the basis of the model parameters obtained by the historical samples, correcting the original model parameters online with each new disturbance data. By this way we can only save the model parameters without saving all the historical data, so that we can improve the efficiency of load modeling. Load modeling with the PSASP simulation data, the results show that this method is correct and effective. Comparing this method with the parameters weighting-mean method and the clustering center method based on standard test data, the results show that this method is more convenient to be carried out and the precision is much higher.The access of distributed generation brings difficulty to the traditional research of the load modeling. For the generalized load modeling with distributed generation, dynamic simulation system with distributed generation is built based on EPRI-9node system by PSASP in this paper. Comparing the influence of the different distributed power capacity ratio on load modeling, then the synthesis load model of asynchronous machine in parallel with static load is adopted to describe the regional load characteristics with distributed generation, at the last the applicability of the model is verified on different load level. The simulation results show that synthesis load model of asynchronous machine in parallel with distributed generation is correct and effective in describing the regional load with distributed generation.