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Load Nowcasting: Predicting Actuals with Limited Data

Assessing and Comparing Short Term Load Forecasting Performance

VTT, Technical research Centre of Finland, Smart Energy and Built Environment, P.O. Box 1000, FI-02044 Espoo, Finland
Department of Electrical Engineering, Tampere University, P.O. Box 1001, FI-33014 Tampere, Finland
Department of Environmental and Biological Sciences, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, Finland
Author to whom correspondence should be addressed.
Energies 2020, 13(8), 2054;
Received: 13 March 2020 / Revised: 15 April 2020 / Accepted: 17 April 2020 / Published: 20 April 2020
(This article belongs to the Special Issue Short-Term Load Forecasting 2019)
When identifying and comparing forecasting models, there may be a risk that poorly selected criteria could lead to wrong conclusions. Thus, it is important to know how sensitive the results are to the selection of criteria. This contribution aims to study the sensitivity of the identification and comparison results to the choice of criteria. It compares typically applied criteria for tuning and performance assessment of load forecasting methods with estimated costs caused by the forecasting errors. The focus is on short-term forecasting of the loads of energy systems. The estimated costs comprise electricity market costs and network costs. We estimate the electricity market costs by assuming that the forecasting errors cause balancing errors and consequently balancing costs to the market actors. The forecasting errors cause network costs by overloading network components thus increasing losses and reducing the component lifetime or alternatively increase operational margins to avoid those overloads. The lifetime loss of insulators, and thus also the components, is caused by heating according to the law of Arrhenius. We also study consumer costs. The results support the assumption that there is a need to develop and use additional and case-specific performance criteria for electricity load forecasting. View Full-Text
Keywords: short term load forecasting; performance criteria; power systems; cost analysis short term load forecasting; performance criteria; power systems; cost analysis
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MDPI and ACS Style

Koponen, P.; Ikäheimo, J.; Koskela, J.; Brester, C.; Niska, H. Assessing and Comparing Short Term Load Forecasting Performance. Energies 2020, 13, 2054.

AMA Style

Koponen P, Ikäheimo J, Koskela J, Brester C, Niska H. Assessing and Comparing Short Term Load Forecasting Performance. Energies. 2020; 13(8):2054.

Chicago/Turabian Style

Koponen, Pekka, Jussi Ikäheimo, Juha Koskela, Christina Brester, and Harri Niska. 2020. "Assessing and Comparing Short Term Load Forecasting Performance" Energies 13, no. 8: 2054.

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