No abstract

The accuracy of the load model has great effects on power system stability analysis and control. Based on our practice in China on modeling load from field measurements, this paper systematically develops a measurement-based composite load model. Principles guiding the load modeling practice are discussed based on detailed analysis on stochastic characteristics of the modeling procedure. The structure of the measurement-based composite load model is presented. A multicurve identification technique is described to derive parameters. The generalization capability of this built load model is also investigated in this paper. Two cases are studied to illustrate the accuracy of the developed load model on describing the load dynamic characteristics in the actual power system.

A load model is one of the most important elements in power system simulation and control. Recently, the constant impedance, constant current, and constant power load in combination with the induction motor load have been widely used as the composite load model, whose parameters are all identified from the field measurements in measurement-based load modeling practices so far. However, there is virtually no research conducted on whether all these parameters could really be identified. This paper investigates the possibility on reducing the number of composite load model parameters to be identified from field measurements. This paper first shows that direct application of the IEEE load motor parameters in the composite load model may be inadequate on describing the load dynamics over different operating status. Then the perturbation method is used to derive the trajectory sensitivities of the equivalent motor parameters, based on which the reduction on the identified parameters of the composite load model is presented. Two cases of measurement-based load modeling in North China and Northeast China are studied to illustrate the validity of the reduction method. It is shown that the reduction does not lose the model's capability on describing the load dynamics. The reduction on the number of identified parameters not only provides a possible way to solve the multi-valued load model problem based on the current practices on measurement-based load modeling, but it also facilitates building of the load model with more components included in it. Meanwhile, reducing the identified parameters reduces the identification time; thus, the proposed strategy significantly enhances the efficiency of the load modeling work.Index Terms-Composite load model, field measurements, power system stability, trajectory sensitivity.

A custom designed and well monitored substation communication network (SCN) can maintain the fast and reliable information transmission and lead to improved operation and management of a substation automation system (SAS). In order to achieve this goal, a traffic flow model, including a port connection model, a traffic flow source model and a traffic flow service model of a SCN is developed in this paper. Based on the traffic flow model, a traffic flow calculation algorithm is designed to obtain the distribution of traffic load and maximum message delay. In order to verify the accuracy of the proposed method, the SCN of a simplified substation is established in the laboratory. And the distribution of traffic load and maximum message delay calculated using the proposed method is compared to that measured by a network analyzer. Further more, possible applications, such as network device selection, network performance analysis and sensitivity analysis, of the proposed method are demonstrated based on a typical 220 kV substation.Index Terms-substation automation system (SAS), traffic flow analytical model, IEC 61850, traffic load distribution, maximum message delay distribution.

No abstract