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In power generating industry, load forecasting plays an important part. In oder to improve the economic and social benefits, and to help the decision of construction of generating plant, the forecasting of electric demand is necessary. According to the actual situation and method of grey theory, and by using the grey model, we try to found out the electricity consumption of the the next 5 years.
This paper deals with the power load forecasting for medium and long term using based on Principal Component Regression Analysis. The paper first reviews the research achievement of the load forecasting and its relationship with economic development, then introduces the basic theory of the principal component analysis and principal component regression analysis model. Finally, taking Beijing as an...
Accurate wind speed forecasting is essential for predicting the wind power output. The wind speed is randomness, so the forecasting is very difficult. Least squares support vector machines (LSSVM) for load forecasting requires the identification of relevant parameters by expert experiment, this paper proposed a combination of adaptive particle swarm optimization the relevant parameters of least square...
For non-linear and gray of power load forecasting, this paper proposed a new combining forecasting model. First optimize the parameters of the GM(1, 1, ??) forecasting model with ant colony algorithm, and predict a set of load values; then predict another set of load values with Auto-regressive integrated moving average model (ARIMA). The forecasting results of ant colony gray model and ARIMA model...
Time series forecasting is an important aspect of dynamic data analysis and processing, in science, economics, engineering and many other applications there exists using the historical data to predict the problem of the future, and is one considerable practical value of applied research. Time series forecasting is an interdisciplinary study field, this paper is under the guidance of the introduction...
This paper describes the basic principle of seasonal multiplicative model in time series and the GARCH model, applies the former to forecast the monthly peak load, and then uses the latter to amend the forecasting error. Calculating the real data of a regional power grid, results show the forecasting precision and effect of the error modifying model.
Accurate forecasting of electricity load has been one of the most important issues in the electricity industry. Modern data mining methods have played a crucial role in forecasting electricity load. Support vector machines (SVMs) have been successfully employed to solve nonlinear regression and time series problems. Based on the Nystro??m approximation and the primal-dual formulation of the least...
GM(1,1) forecasting model has the advantages of few sample data required, easy calculation, high prediction accuracy in short terms, examination, etc. it is extensively applied in the load forecasting. However, it has its localization. The greater the gray level of data is greater, the lower the prediction precision is. Besides, it is not suitable for long term forecasting of economy to step backwards...
Middle-long forecasting of electric power is the guarantee for the healthy development of the electric industry. In this paper, several forecasting methods are measured by several indexes, and then the entropy method is used to form a comprehensive index to set up the object function of genetic algorithm. Next the genetic algorithm is used to calculate the weight of every forecasting method. At last,...
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