Chaotic characters of power load and its forecasting for marine electric propulsion system;

Research and comparison of neural networks for forecasting mid-long term power load;

Gray neural network forecast of power loads based on relaitonal analysis method;

Improvements and measurements of parameter identification for electric load;

Design of electric load intelligent monitoring system based on GPRS network;

Design of large customer electric load data acquisition system based on wireless public network;

Discussion of using gas fired air conditioning to reduce electrical load;

The meteorological index-effective temperature (ET) is introduced to evaluate the im- pact of various meteorological factors on electrical load in Guangxi on the basis that the latter is heavily influenced by the former.

By analyzing and comparing various prediction methods and their features, gray model prediction method can be used for predicting the medium-term regional electrical load.

It is found that the meteorological elements affect directly electricity load.

The variation of electricity load is influenced by the weather,especially the temperature.

Short-term electricity load forecasting is important base of safe diapatch and economical operation in power system.

The middle and long term predictive methods for electric power load;

Identification and correction to anomalous electric power load data by t test;