[Show abstract][Hide abstract] ABSTRACT: Load model plays important role in the dynamic simulation of power system. The time-varying property of load in short-time appears to be stochastic in long-term. Thus the approach in this paper to study the statistical regularity of load characteristic vector, based on probability distribution and statistics, gives references to the choice and application of load model and its parameters. This paper proposes the following approaches. First, the differential equation model is transformed into continuous state space model, and is solved for the time-domain response curve against step input. Second, the characteristic parameters of response curve, represented by [k<sub>t</sub> T<sub>f</sub>,k<sub>s</sub>], are distilled as the characteristic vector of load property. 69 sets of effective sampling data from Yuzhuang substation of Cangzhou region in China were studied for the character parameters of load model, from which useful conclusions of the load model variety regularity have been got.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a selection method for the phasor measurement placement. Taking the transient stability into account, this paper constructs a data platform of phasor measurement units. This platform not only copes with the limited sample but also supplies scientific rules for phasor measurement placement. We can acquire more knowledge of the phasor measurement units by this platform. The IEEE 39-Bus test system is employed to demonstrate the validity of the proposed approach.
[Show abstract][Hide abstract] ABSTRACT: Synchronized phasor measurement units (PMUs) have evolved into a practical tool for measurement of power system voltage and current phasors. It can enhance many present applications such as state estimators, stability controls, and remedial action schemes, and they can also serve as disturbance monitors. Since the quantities measured by PMUs are voltage and current phasors, the linear relation between them holds when modeling the branches in the network. This feature permits linear state estimation process, thus avoiding repetitive manipulations with large matrices in iterative procedure as it is in the traditional case. This significantly reduces the computational time and errors level. This paper describes several methods for Phasor Measurement Unit (PMU) placement with the aim of linear static state estimation of power system networks. These methods are depth first, graph theoretic procedures and simulated annealing method as well as tabu search method and Genetic algorithms. The effectiveness and flexibility of these proposed algorithms are illustrated with numerical simulation using some IEEE test system.
[Show abstract][Hide abstract] ABSTRACT: The authority of unit maintenance scheduling belongs to PX and not to each generates company in China electricity market. It is a considerable problem for PX to make maintenance scheduling to play fair, to balance the declaring demand between generate companies and to undertake the reliability of grid. The benefit bodies classify into n+2 kinds: n generate companies, the grid company and "society". According to this analysis, the maintenance scheduling model is represented as multi-objective optimum problem. The objects are so much that the mathematics solution is difficult. If weighting average method is adapted to shift these to single object, the physical meaning of the weighting is not clear. On the basis of analyzing the gain and loss of all economic entities, n+2 objective functions are changed to 2 objective functions and weighting average method is adapted to realize the single objective function optimum. The physical meaning of the weighting is explained as the compromise between the efficiency and fair.
[Show abstract][Hide abstract] ABSTRACT: The traditional methods for load forecasting can not supply the required accuracy for the engineering application because we only get limited history data sets and the factors that affect the load forecasting are complex. This paper presents a new framework for the power system short-term load forecasting: firstly, this paper establishes the feature selection model and uses floating search method to find the feature subset; then this paper makes use of the support vector machines to forecast the load and takes full advantage of the SVM to solve the problem with small sample and nonlinear. Hence the accuracy of the estimation result is improved and a better generalization ability is guaranteed. The EUNITE network is employed to demonstrate the validity of the proposed approach.
[Show abstract][Hide abstract] ABSTRACT: This paper presents a data mining framework for the historical data of measurement and simulation units. Taking example for transient stability prediction, this paper establishes a data mining flow. The data market of transient stability is built up by all kinds of data sources. The data market is convenient for online analytical processing. At the same time, many model of data mining can be constructed based on the data market. We can acquire more knowledge of the power system transient stability. The IEEE 39-Bus test system is employed to demonstrate the validity of the proposed approach.
[Show abstract][Hide abstract] ABSTRACT: In the deregulated power industry, the increasing number of power marketers and independent power generators increases the variability of power flow patterns in the transmission system, thereby reducing the ability of transmission planners and operators to predict the critical operating conditions and limits. Consequently, the small signal stability problem becomes more complex. And the existing standard methods and tools for small-signal stability are not able to perform security analysis in the claimed response time required for online use. Under this background, we propose a novel approach for power system small signal stability analysis and control which combines the state-of-the-art small signal analysis tools, data mining, and the synchronized phasor measurement techniques.
[Show abstract][Hide abstract] ABSTRACT: Application of artificial neural network (ANN) in the design of an adaptive power system stabilizer is presented in this paper. ANN and Prony analysis were used to track the dynamic characteristics of the generator and the power systems, then the controller is designed. Test results show that the proposed ANN PSS can perform well over a wide range of operating conditions and provide better dynamic performance than a fix parameter conventional PSS (CPSS).