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Electric power systems load forecasting: a survey

PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376), 2003
This 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
openaire   +1 more source

Electric Power Load Forecasting Based on Multivariate LSTM Neural Network Using Bayesian Optimization

Electrical Power and Energy Conference, 2020
With rapid growth and development around the world, electricity consumption is increasing day by day. As the production and consumption of electricity is simultaneous, an electric power load forecasting technique with higher accuracy can play a pivotal ...
Mohammad Munem, T. M. Rubaith Bashar, Mehedi Hasan Roni, Munem Shahriar, T. Shawkat, Habibur Rahaman   +5 more
semanticscholar   +1 more source

Real time load forecast in power system

2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 2008
This 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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Short‐term power load forecasting based on multi‐layer bidirectional recurrent neural network

IET Generation, Transmission & Distribution, 2019
Accurate power load forecasting is of great significance to ensure the safety, stability, and economic operation of the power system. In particular, short-term power load forecasting is the basis for grid planning and decision making.
Xianlun Tang, Yuyan Dai, Ting Wang, Yingjie Chen   +3 more
semanticscholar   +1 more source

Power load forecasting using neural canonical correlates

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
We (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, null Shang Jen Chuang, C. Fyfe   +2 more
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Power system load forecasting using smoothing techniques

International Journal of Systems Science, 1978
This 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, K. K. BISWAS, A. K. MAHALANABIS   +2 more
openaire   +1 more source

Power Grid Load Forecasting Using a CNN-LSTM Network Based on a Multi-Modal Attention Mechanism

Applied Sciences
Optimizing short-term load forecasting performance is a challenge due to the non-linearity and randomness of electrical load, as well as the variability of system operating patterns.
Wangyong Guo, Shijin Liu, Liguo Weng, Xingyu Liang   +3 more
semanticscholar   +1 more source

The Power Load Forecasting by Kernel PCA

2010
We 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, Chiung-Hsing Chen, Shang-Jen Chuang, Ting-Chia Ou   +3 more
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Short-term power load forecasting for combined heat and power using CNN-LSTM enhanced by attention mechanism

Energy, 2023
Anping Wan, Qing Chang, Khalil Al-Bukhaiti, Jiabo He   +3 more
semanticscholar   +1 more source

Improving Power Load Forecasting using FIS

2022 IEEE 13th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2022
Maninder Singh, Indu Batra, Balbir Bob Gill, Ajay Kakkar   +3 more
openaire   +1 more source