Results 121 to 130 of about 8,580 (164)

Short Term Load Forecasting Using XGBoost

2019
For efficient use of smart grid, exact prediction about the in-future coming load is of great importance to the utility. In this proposed scheme initially we converted daily Australian energy market operator load data to weekly data time series. Furthermore, we used eXtreme Gradient Boosting (XGBoost) for extracting features from the data.
Raza Abid Abbasi, Nadeem Javaid, Muhammad Nauman Javid Ghuman, Zahoor Ali Khan, Shujat ur Rehman, Amanullah   +5 more
openaire   +1 more source

A hierarchical neural model in short-term load forecasting

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000
This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up of two self-organizing map nets-one on top of the other. It has been successfully applied to domains in which the context information given by former events plays a primary role.
Otávio Augusto Salgado Carpinteiro, Agnaldo J. R. Reis, Alexandre P. Alves da Silva   +2 more
openaire   +1 more source

A Methodology for Short-Term Load Forecasting

IEEE Latin America Transactions, 2017
Demand forecasting is important for electrical analysis development by utilities. It requires low error levels in order to reach reliability in electrical analysis. However, the demand for energy has dissimilar profiles variations depending on the type of day, weather conditions and geographical area.
j. Jiménez, K. Donado, C. G. Quintero
openaire   +1 more source

Fuzzy interaction regression for short term load forecasting [PDF]

Fuzzy Optimization and Decision Making, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tao Hong 0003, Pu Wang
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Robust short-term load forecasting

International Workshop on Systems, Signal Processing and their Applications, WOSSPA, 2011
Analyzing the stochastic characteristics of electric consumption series in many countries shows the presence of atypical observations or outliers. Outliers are deviant data points that do not follow the model of the majority of observations. They significantly degrade the accuracy of conventional day-ahead estimation and forecasting methods even if ...
Yacine Chakhchoukh, Abdelhak M. Zoubir
openaire   +1 more source

Short Term Load Forecasting Based on Weather Load Models

IFAC Proceedings Volumes, 1987
Abstract A stochastic weather load model for on-line forecasting of hourly load demands with lead times of 1 to 168 hours is presented. The proposed model considers the effect of up to 3 weather variables. The multi-input (hourly weather variables) and single output (hourly loads) stochastic process is modeled as an Auto Regressive-Moving Average ...
S. Vemuri, B. Hoveida, S. Mohebbi
openaire   +1 more source

Studies on the forecasting errors of the short term load forecast

Proceedings. International Conference on Power System Technology, 2003
A deep research on the short-term load forecasting error has been given in this paper according to the time series theory. The relationship between the model and forecasting error has been investigated. A method proposed could be used to direct how to improve the forecasting accuracy. Instances of different methods test its feasibility.
G. Mu, Y.H. Chen, null Liu ZF, W.D. Fan
openaire   +1 more source

Short-term load forecasting using a long short-term memory network

2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2017
Load forecasting is an essential part of a power system. It enhances the energy-efficiency and reliable operation of the power system. As depicted in the proposal of the smart grid, an increasing number of smart meters have been being installed in many utilities on a global scale.
Chang Liu, Zhijian Jin, Jie Gu 0005, Robert Caiming Qiu   +3 more
openaire   +1 more source

Long short term memory networks for short-term electric load forecasting

2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017
Short-term electricity demand forecasting is critical to utility companies. It plays a key role in the operation of power industry. It becomes all the more important and critical with increasing penetration of renewable energy sources. Short-term load forecasting enables power companies to make informed business decisions in real-time.
Apurva Narayan, Keith W. Hipel
openaire   +1 more source

Local Regression-Based Short-Term Load Forecasting

Journal of Intelligent and Robotic Systems, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources