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.

对后验仿真准确度的研究是电力系统仿真可信度研究的重要组成部分，但当仿真与实测有差异时，如何进行仿真验证工作成为一个难题。根据广域测量系统(WAMS)能够提供独立于模型和参数的动态过程同步数据的特点，提出了基于WAMS的电力系统分层分块的动态仿真验证策略。分层策略利用电网由不同电压等级所组成的特点将电网分层，在不同层次上进行仿真验证;分块策略则是利用电网结构按照元件和区域的思想将系统进行解耦来实现仿真验证。通过上述策略，将WAMS量测值作为电网数值仿真的动态等值输入，实现了仿真的解耦，缩小了定位引起仿真误差元件的区间。结合电力系统仿真软件PSS/E给出了基于WAMS的分层分块仿真验证策略的工程实现途径。

电力系统稳定域边界的逼近一直是应用能量函数方法分析电力系统暂态稳定的难点。基于半张量理论，文中给出了逼近电力系统稳定域边界的矩阵方程。通过矩阵运算，可以获得电力系统稳定域边界的高阶逼近表达式。所提出的算法没有对系统进行任何形式的非线性变换，不需要求解系统所有的特征根与特征向量，也无需进行时域积分；算法充分保留了系统的非线性结构，形式简洁。由于该算法完全基于矩阵运算，因此非常适于计算机实现。

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.