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Short-term load forecasting based on load profiling
2013 IEEE Power & Energy Society General Meeting, 2013 Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility
Ramos, Sérgio +3 more
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Detection, mining and forecasting of impact load in power load forecasting
Applied Mathematics and Computation, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jianzhou Wang, Zhixin Ma, Lian Li
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Spatial Load Forecasting Based on Load Forecasting Reliability
Applied Mechanics and Materials, 2014A spatial load forecasting method based on reliability of load forecasting is proposed. It calculates the correlation of wave comprehensive index, variance, maximum predictable ability of each power supply small area’s historical load data by using the analysis theory of grey degree based on the analysis of load forecasting error last target year.
Bai Xiao, Hao Wang, Gang Mu
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Ensemble Learning for Load Forecasting
IEEE Transactions on Green Communications and Networking, 2020In this paper, an ensemble learning approach is proposed for load forecasting in urban power systems. The proposed framework consists of two levels of learners that integrate clustering, Long Short-Term Memory (LSTM), and a Fully Connected Cascade (FCC) neural network.
Lingxiao Wang 0004 +3 more
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Load Forecasting for Transmission Planning
IEEE Power Engineering Review, 1984This paper investigates the load forecasting needs of transmission planning, using the planning of two utility systems as an example. Two aspects are investigated. One, the effect of forecasting error on the planning of a transmission system, and two, procedures required to produce forecasts. Several conclusions are developed.
H. Willis, H. Tram
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Forecasting data for load flow
Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No.04CH37521), 2004In order to achieve a more secure and economic operation of a power system its state should be known not only in the present but some time ahead. Transmission system operators do not have the same security margins like they had in the past. Most of the tools of security assessment operate on-line and provide valuable input to the system operators ...
Delimar, Marko +2 more
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2021 International Conference on Intelligent Technologies (CONIT), 2021
Since the electricity demand is increasing globally, load forecasting techniques have become immensely important in forecasting the electricity demands and it also helps the policy makers. The aim of our project is to perform short-term load forecasting, i.e. up to a week ahead.
Ujjwal Singh +3 more
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Since the electricity demand is increasing globally, load forecasting techniques have become immensely important in forecasting the electricity demands and it also helps the policy makers. The aim of our project is to perform short-term load forecasting, i.e. up to a week ahead.
Ujjwal Singh +3 more
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Load Forecasting and Operation Strategy Design for CCHP Systems Using Forecasted Loads
IEEE Transactions on Control Systems Technology, 2015Operation strategy of combined cooling, heating, and power (CCHP) systems is designed to collect users’ load information to determine the energy input to the system and power flow inside the system. Most of the current operation strategies are designed by assuming that accurate loads during the next time interval are already known. To solve the problem
Mingxi Liu +2 more
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A Fast and Stable Forecasting Model to Forecast Power Load
International Journal of Pattern Recognition and Artificial Intelligence, 2015As the traditional gray forecasting model GM(1, 1) has poor performance in forecasting the fast-growing power load, we present a chaotic co-evolutionary particle swarm optimization (CCPSO) algorithm, one with better efficiency than the PSO algorithm. Based on the GM(1, 1) model, the CCPSO algorithm is adopted to solve the values of parameters a and b ...
Li-Zhi Tan +5 more
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Neural-wavelet Methodology for Load Forecasting
Journal of Intelligent and Robotic Systems, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rong Gao 0002, Lefteri H. Tsoukalas
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