Assessing and Comparing Short Term Load Forecasting Performance
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 co...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/8/2054 |
| _version_ | 1797570137618907136 |
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| author | Pekka Koponen Jussi Ikäheimo Juha Koskela Christina Brester Harri Niska |
| author_facet | Pekka Koponen Jussi Ikäheimo Juha Koskela Christina Brester Harri Niska |
| author_sort | Pekka Koponen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T20:21:41Z |
| format | Article |
| id | doaj.art-d22e75cf791b4e678a346ce8b5eacdfc |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T20:21:41Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-d22e75cf791b4e678a346ce8b5eacdfc2023-11-19T22:12:03ZengMDPI AGEnergies1996-10732020-04-01138205410.3390/en13082054Assessing and Comparing Short Term Load Forecasting PerformancePekka Koponen0Jussi Ikäheimo1Juha Koskela2Christina Brester3Harri Niska4VTT, Technical research Centre of Finland, Smart Energy and Built Environment, P.O. Box 1000, FI-02044 Espoo, FinlandVTT, Technical research Centre of Finland, Smart Energy and Built Environment, P.O. Box 1000, FI-02044 Espoo, FinlandDepartment of Electrical Engineering, Tampere University, P.O. Box 1001, FI-33014 Tampere, FinlandDepartment of Environmental and Biological Sciences, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, FinlandDepartment of Environmental and Biological Sciences, University of Eastern Finland, P.O. Box 1627, FI-70211 Kuopio, FinlandWhen 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.https://www.mdpi.com/1996-1073/13/8/2054short term load forecastingperformance criteriapower systemscost analysis |
| spellingShingle | Pekka Koponen Jussi Ikäheimo Juha Koskela Christina Brester Harri Niska Assessing and Comparing Short Term Load Forecasting Performance Energies short term load forecasting performance criteria power systems cost analysis |
| title | Assessing and Comparing Short Term Load Forecasting Performance |
| title_full | Assessing and Comparing Short Term Load Forecasting Performance |
| title_fullStr | Assessing and Comparing Short Term Load Forecasting Performance |
| title_full_unstemmed | Assessing and Comparing Short Term Load Forecasting Performance |
| title_short | Assessing and Comparing Short Term Load Forecasting Performance |
| title_sort | assessing and comparing short term load forecasting performance |
| topic | short term load forecasting performance criteria power systems cost analysis |
| url | https://www.mdpi.com/1996-1073/13/8/2054 |
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