Yang Weihong

Dynamic characteristics clustering of electric loads based on Kohonen neural network

The characteristics clustering of electric loads are of great importance to the Measurement-Based Modeling method. In this paper, a new method based on Kohonen self-organization neural network is presented for the characteristics clustering of dynamic loads. At first, the model of every group of load disturbance data is established, and then the responses of the load models to the same voltage excitation and the pre-disturbance active power of the loads are incorporated into the feature vectors. At last, Kohonen neural network is introduced to cluster. Many sets of load data measured from North China Power System in three years (1996–1998) have been dealt with using the method. The results show load characteristics have rule though they are random and time-varying. The feasibility of the Measurement-Based Modeling approach is also proved.

New thoughts of urban power network planning which building the urban power network structure system

Urban power network structure planning is an important aspect of urban power network planning. In this paper, for adapting to the urban power requirements development of the new stage, the views which building the city power network structure system is put forward to carry out the urban power network planning. This can be systematically and comprehensively to guide the city power network structure planning at all levels so as to better adapt to the structure of the coordination of transmission and distribution grid to match the requirements of the development. Building the urban power network structure system will have an important impact for the city power network planning ideas and methods.