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Local Short Term Electricity Load Forecasting: Automatic Approaches [PDF]
2017 International Joint Conference on Neural Networks (IJCNN), 2017 Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging development of smart grid technologies is posing new challenges as well as
Bianchi, Filippo Maria +2 more
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Short-Term Load Forecasting [PDF]
Proceedings of the IEEE, 1988 Some of the decision and control functions discussed in this book require knowledge of future load behavior. In unit commitment, for example, hourly system loads for the next 24–72 hours are required. Some unit commitment programs even require knowledge of future loads for the next week, i.e., 168 hours.
G. Gross, F.D. Galiana
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Short Term Load Forecasting [PDF]
, 2019 AbstractElectrification of transport and heating, and the integration of low carbon technologies (LCT) is driving the need to know when and how much electricity is being consumed and generated by consumers. It is also important to know what external factors influence individual electricity demand.
Maria Jacob +2 more
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Short-Term Load Forecasting: The Similar Shape Functional Time Series Predictor [PDF]
, 2012 We introduce a novel functional time series methodology for short-term load forecasting. The prediction is performed by means of a weighted average of past daily load segments, the shape of which is similar to the expected shape of the load segment to be
Paparoditis, Efstathios +1 more
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Short-Term Electricity Load Forecasting with Machine Learning [PDF]
Information, 2021 An accurate short-term load forecasting (STLF) is one of the most critical inputs for power plant units’ planning commitment. STLF reduces the overall planning uncertainty added by the intermittent production of renewable sources; thus, it helps to minimize the hydrothermal electricity production costs in a power grid.
Aguilar Madrid, Ernesto, António, Nuno
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Analysis load forecasting of power system using fuzzy logic and artificial neural network [PDF]
, 2017 Load forecasting is a vital element in the energy management of function and execution purpose throughout the energy power system. Power systems problems are complicated to solve because power systems are huge complex graphically widely distributed and ...
A Mostafa, Salama +7 more
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Exploiting road traffic data for very short term load forecasting in smart grids [PDF]
, 2014 If accurate short term prediction of electricity consumption is available, the Smart Grid infrastructure can rapidly and reliably react to changing conditions.
Aparicio, J +5 more
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Short-Term Electric Load Forecasting Based on a Neural Fuzzy Network [PDF]
, 2003 Electric load forecasting is essential to improve the reliability of the ac power line data network and provide optimal load scheduling in an intelligent home system.
Lam, HK, Leung, FHF, Ling, SH, Tam, PKS
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Energy Household Forecast with ANN for Demand Response and Demand Side Management [PDF]
, 2016 This paper presents a short term load forecasting with artificial neural networks. Despite the great imprevisibility, it is possible to forecast the electricity consumption of a household with some accuracy, similarly to that the electricity utilities ...
Carlos, Cardeira +3 more
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Federated Learning for Short-Term Residential Load Forecasting
IEEE Open Access Journal of Power and Energy, 2022 Load forecasting is an essential task performed within the energy industry to help balance supply with demand and maintain a stable load on the electricity grid. As supply transitions towards less reliable renewable energy generation, smart meters will prove a vital component to facilitate these forecasting tasks.
Christopher Briggs +2 more
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