外文翻譯---人工神經(jīng)網(wǎng)絡(luò)在短期負(fù)荷預(yù)測中的應(yīng)用

1、外文文獻(xiàn)原文:Artificial Neural Networks in Short Term load ForecastingK.F. Reinschmidt, President B. LingStone h Webster Advanced Systems Development Services, Inc.245 Summer Street Boston, U 0221 0Phone: 617-589-1 84 1Abstrac

2、t：We discuss the use of artificial neural networks to the short term forecasting of loads. In this system, there are two types of neural networks: non-linear and linear neural networks. The nonlinear neural network is us

3、ed to capture the highly non-linear relation between the load and various input parameters. A neural networkbased ARMA model is mainly used to capture the load variation over a very short time period. Our system can achi

4、eve a good accuracy in short term load forecasting.Key words: short-term load forecasting, artificial neural network1、IntroductionShort term (hourly) load forecasting is an essential hction in electric power operations.

5、Accurate shoirt term load forecasts are essential for efficient generation dispatch, unit commitment, demand side management, short term maintenance scheduling and other purposes. Improvements in the accuracy of short te

6、rm load forecasts can result in significant financial savings for utilities and cogenerators.Various teclmiques for power system load forecasting have been reported in literature. Those include: multiple linear regressio

7、n, time series, general exponential smoothing, Kalman filtering, expert system, and artificial neural networks. Due to the highly nonlinear relations between power load and various parameters (whether 2、Variables Afferti

8、ng Short-Term LoadSome of the variables affecting short-term electxical load are:TemperatureHumidityWind speedCloud coverLength of daylightGeographical regionHolidaysEconomic factorsClearly, the impacts of these variable

9、s depend on the type of load: variations in temperature, for example, have a larger effect on residential and commercial loads than on industrial load. Regions with relatively high residential loads will have higher vari

10、ations in short-term load due to weather conditions than regions with relatively high industrial loads. Industrial regions, however, will have a greater variation due to economic factors, such as holidays.As an example,