In a comprehensive way, load forecasting in power system stands for predicting the load to be nearly accurate, which is a basic necessary step for maintaining the efficiency of Gencos, Discoms, and other participants of the electrical energy market. This chapter represents a solution methodology ...
2.The simulation results show that the orthogonal decomposition feature expansion based process neural networks is supprior to time-domain feture expansion based proscess neural networks in training speed,veracity in prediction,and more suitable for the application of electric load forecasting.结果表明,基...
This article describes the basic method of ultra-short-term load forecasting include the Linear Extrapolation, Kalman Filter Method, Time Series Method, Artificial Neural Networks and Support Vector Machine Algorithm. Then, it summarizes the commonly use
J. Zeng, "A new short-term load forecasting method of power system based on EEMD and SS-PSO", Neural Computing and Applications, vol. 24, no. 3-4, (2014), pp. 973-983.Liu Z, Sun W, Zeng J. A new short-term load forecasting method of power system based on EEMD and SS-PSO ...
Electric Power System of Serbia:塞尔维亚电力系统 14 Short-term load forecasting based on an adaptive hybrid method 电力系统保护Power System Protection(part2) A hybrid economic indices based short-term load forecasting system 电力系统自动化(Power system automation) 电力系统负荷预测及其方法研究 电力...
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6) short-term load forecasting system 短期负荷预测系统 1. It designs an efficient short-term load forecasting system which takes elements like temperature and types of dates into special consideration. 针对电力系统受多种因素影响的特点,应用模糊逻辑理论和人工神经网络两种方法,发挥各自优势,设计出一个...
6) power load forecasting 电力负荷预测 1. Short-term power load forecasting based on MRA and regression analysis; 基于MRA与回归分析法的短期电力负荷预测 2. Multifactor-influenced combined gray neural network models for power load forecasting; 多因素影响的灰色神经网络组合电力负荷预测 3. In view...
Based on the rough set theory forecast and artificial neural network,a new method of load forecasting is put forward.The rough set is used to analyze the condition attributes reduction based on uncertain and incomplete original data.These attributes are then applied to the artificial neural network...
Unified weekly peak load forecasting for fast growing power systemForecasting demand and energy for power systems in developing countries is a difficult task; the difficulty stems from shortage of appropriate data and is also due to the high growth rate of both electric demand and load related ...