Gan Deqiang

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.

Notice of Retraction Optimal Power Flow of Receiving Power Network Considering Distributed Generation and Environment Pollution

By the fact that more and more distributed generations located in receiving power network, proper power arrangement of distributed generations is presented to optimize active power flow of receiving power network. Considering different effect on environment of various distributed generation, environment value index of contamination is used to evaluate the effect on environment of contamination. Based on it a model of environment cost included charge of emission and cost of environment guard against pollution is established. And then a model of OPF included environment cost is established by penalty function method. And primal dual interior point method is used to solve it. At last, simulation test is carried out on data of a receiving power network. The result indicates that cost and loss can be debased at one time, environment pollution can be reduced, on condition that considering environment cost, production cost and loss.