Han Zhen-xiang

A reduced-order method for estimating the stability region of power systems with saturated controls

In a modern power system, there is often large difference in the decay speeds of transients. This could lead to numerical problems such as heavy simulation burden and singularity when the traditional methods are used to estimate the stability region of such a dynamic system with saturation nonlinearities. To overcome these problems, a reduced-order method, based on the singular perturbation theory, is suggested to estimate the stability region of a singular system with saturation nonlinearities. In the reduced-order method, a low-order linear dynamic system with saturation nonlinearities is constructed to estimate the stability region of the primary high-order system so that the singularity is eliminated and the estimation process is simplified. In addition, the analytical foundation of the reduction method is proven and the method is validated using a test power system with 3 buses and 5 machines.

A KIND OF GENERALIZED HOPFIELD CONTINUOUS MODEL AND ITS APPLICATION TO THE OPTIMAL DISTRIBUTION OF REACTIVE POWER SOURCES IN POWER SYSTEMS

At first, a kind of new neural network model named Generalized Hopfield Continuous Model is proposed. And then, the behavior and the ability to solve constrained optimization problems via the proposed model are analyzed and discussed. The advantages of the proposed model over the Hopfield Continuous Model are described. Finally, the application of the proposed model to the optimal distribution of reactive power sources in power systems is investigated and formulated. An example is served for illustrations, the result shows the feasibility of the proposed method.

An electricity price model with consideration to load and gas price effects.

Some characteristics of the electricity load and prices are studied, and the relationship between electricity prices and gas (fuel) prices is analyzed in this paper. Because electricity prices are strongly dependent on load and gas prices, the authors constructed a model for electricity prices based on the effects of these two factors; and used the Geometric Mean Reversion Brownian Motion (GMRBM) model to describe the electricity load process, and a Geometric Brownian Motion (GBM) model to describe the gas prices; deduced the price stochastic process model based on the above load model and gas price model. This paper also presents methods for parameters estimation, and proposes some methods to solve the model.

A cluster analysis of power producer's bidding using average electricity price difference-integration model

An average electricity price difference-integration model is proposed in this paper. This model can transform the units biding curve of power producer in market into an one-dimensional feature vector which can reflect the change of bidding curve quite conformably, so can implement classification of units biding using cluster analysis. Through clustering calculation of bidding curve from Zhejiang electricity market, it is shown that bidding curve can be classified accurately and efficiently using 20-segment model and square sum of deviations.

TRANSIENT STABILIZATION OF MULTIMACHINE POWER SYSTEMS BY VARIABLE STRUCTURE SYSTEM CONTROL

In this paper, the variable structure control system theory is applied to design the transient stability control law for multimachine power systems, which is a decentralized control approach where local controllers can guarantee the asymptotically stability of the system by obtaining and calculating subsystems state information only. Furthermore, we extend above approach to the case where the change of the system structure need not be known exactly, with known the changing range only. The proposed approaches are verified by a test power system, the simulating results show that those control approaches are effective.

Transient Stabilization of Multimachine Power Systems by Variable Structure System Control

Abstract In this paper, the variable structure control system theory is applied to design the transient stability control law for multimachine power systems, which is a decentralized control approach where local controllers can guarantee the asymptotically stability of the system by obtaining and calculating subsystems state information only. Furthefmore, we extend above approach to the case where the change of the system structure need not be known exactly, with known the changing range only. The proposed approaches are verified by a test power system, the simulating results show that those control approaches are effective.