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Regional Power Load Forecasting Based on PSOSVM
2018 IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC), 2018Power load forecasting is the basic work of power grid construction planning. Accurate load forecasting is a key requirement for modern power system planning and economic and safe operation. This paper first introduces the background and significance of power load forecasting, research status at home and abroad, and review of power load forecasting ...
Guoqiang Ji +4 more
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Power Load Forecasting Using a Refined LSTM
Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019The power load forecasting is based on historical energy consumption data of a region to forecast the power consumption of the region for a period of time in the future. Accurate forecasting can provide effective and reliable guidance for power construction and grid operation. This paper proposed a power load forecasting approach using a two LSTM (long-
Dedong Tang +4 more
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Heterogeneous ensemble for power load demand forecasting
2016 IEEE Region 10 Conference (TENCON), 2016Electricity load demand is the fundamental building block for all utilities planning. The load demand data has nonlinear and non-stationary characteristics, which make it difficult to be predicted accurately by just computational intelligence or ensemble methods.
Aruna Charukesi Palaninathan +2 more
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Risk adjusted forecasting of electric power load
2014 American Control Conference, 2014Load forecasting of energy demand is usually focused on mean values in related statistical models and ignores rare peak events. This paper provides Extreme Value Theory analysis of the peak events in electrical power load demand. It estimates risk of the peak events by combining forecast of the mean with extreme value modeling of distribution tail. The
Saahil Shenoy, Dimitry Gorinevsky
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Electric power systems load forecasting: a survey
PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376), 2003This work reviews the latest works on load forecasting, classifying them according to presented methods and models, as statistical, intelligent systems, neural networks and fuzzy logic. As there are many different models and methods, we have studied the principal ones considering classical statistical and modern methods like neural networks and fuzzy ...
A.D.P. Lotufo, C.R. Minussi
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Real time load forecast in power system
2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 2008This paper presents an overview of different practical techniques to forecast the load for real time applications. The accuracy of load forecast often determines the amount of energy to be procured in the imbalance market. Therefore to reduce exposures to real-time risks and obtain economic, reliable and secure operations of power system, an accurate ...
H. Daneshi, A. Daneshi
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Power load forecasting using neural canonical correlates
Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002We (1998, 1999) have previously derived a neural network implementation of the statistical technique of canonical correlation analysis. We have then extended the network so that it may find nonlinear correlations in data sets. In this paper we demonstrate the capabilities of the network (both linear and nonlinear) on an artificial data set and ...
null Pei Ling Lai +2 more
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Power system load forecasting using smoothing techniques
International Journal of Systems Science, 1978This paper deals with short-term load forecasting problem for a power system, The load demand at any particular instant is assumed to follow a time-Beries model. A predictor is developed which identifies the coefficients of the time series in an on-line fashion.
GULAB SINGH +2 more
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The Power Load Forecasting by Kernel PCA
2010We use one year's subset to train the Support Vector Machines (SVM) and the next year's data was used for testing with Kernel Principal Components Analysis (KPCA). This is clearly not optimal for a non-stationary time series such as we have here nevertheless the MAPE of peak load data set with back-propagation neural network [Chuang et al., 1998] is 3 ...
Fang-Tsung Liu +3 more
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Improving Power Load Forecasting using FIS
2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2022Maninder Singh +3 more
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