Load model is one of the most important elements in power system operation and control. However, owing to its complexity, load modeling is still an open and very difficult problem. Summarizing our work on measurement-based load modeling in China for more than twenty years, this paper systematically introduces the mathematical theory and applications regarding the load modeling. The flow chart and algorithms for measurement-based load modeling are presented. A composite load model structure with 13 parameters is also proposed. Analysis results based on the trajectory sensitivity theory indicate the importance of the load model parameters for the identification. Case studies show the accuracy of the presented measurement-based load model. The load model thus built has been validated by field measurements all over China. Future working directions on measurement-based load modeling are also discussed in the paper.

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.

The representation of load dynamic characteristics remains an area of great uncertainty and has become a limiting factor for power system analysis and control. The random nature of the load makes load modeling a very difficult problem, which becomes even more challenging when the field measurements increase and the recorded dataset becomes large. This paper proposes a novel concept of modeling load based on support vectors (SVs) of load data. A three-stage procedure to find SVs of the recorded load dataset is presented. Then the load model is built on the SVs. Although the model is derived from only a small subset of the original dataset, it has a strong generalization capability to describe dynamics of the whole dataset. However, the computational burden on the modeling process is much relieved since only a small subset of data is involved. The proposed method also answers the question on how data should be grouped and how many load models should be built as data are accumulated. This paper infers that, although the data space where the load varies seems indefinite and big, its characteristic can be captured and modeled in a much smaller subspace. The presented method is shown to be effective by the case study on Hushitai substation.

The energy function method developed so far assumes that the active load is constant. However, most of the actual load is voltage dependent, which hinders the application of the energy analysis method to the actual power system. On the other hand, the fast development of measurement techniques, especially the wide area measurement systems (WAMS) applied widely in worldwide power system nowadays, presses for the on-line transient stability analysis tools based on the system measurements. The voltage-dependent load into the energy analysis of power system transient stability is discussed. The effect of the comprehensive load characteristics on the system energy is discussed and a WAMS-based energy indicator on the system stability status is proposed. The indicator is easy to be calculated and thus real-time in the operation centre is monitored. The proposed method does not rely on any specific load model, and various load characteristics on different buses can be considered. Simulations on two test systems verify the effectiveness of the proposed method.

Power system is a classical example of complex systems. In this paper it is shown that the power industry in China is facing a tremendous challenge. Then the complexity in power systems is investigated. First, the cascade failure in power systems is analyzed, and compared with sand-pile model. Then we show that the agent-based modelling is a proper way for power network. Mathematically, the geometric dynamics and differential inclusion are useful tool for the stability analysis of large scale power systems. As for power market, the game theory and generalized control system model are proposed. For a complex power system, an evolutive model may be more accurate in description and analysis. Finally, certain newly developed numerical method in power system computation is introduced. Overall, we are convinced that the theorem of complexity, combined with modern control theory, may be the right way to answer the challenge faced by the power industry in China.