A Set-Membership approach to short-term electric load forecasting
| Autor: | Jimena Diaz, Jose Vuelvas, Fredy Ruiz, Diego Patiño |
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| Jazyk: | Spanish; Castilian |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Revista Iberoamericana de Automática e Informática Industrial RIAI, Vol 16, Iss 4, Pp 467-479 (2019) |
| Druh dokumentu: | article |
| ISSN: | 1697-7912 1697-7920 |
| DOI: | 10.4995/riai.2019.9819 |
| Popis: | This work presents a model for the short-term forecast of electric load, based on Set-Membership techniques. The model is formed by a periodic component and an adaptive non-linear autoregressive component. The identifications set of the non-linear model is increased at each estimation step. The model is evaluated in a case study with more than 13.000 samples of hourly sampled energy demand, registered during three years at a rural town in Colombia. The performance of the estimator is evaluated and confronted to a linear autoregressive model and a standard Set-Membership model with fixed identification set. Results show that the proposed estimator is able to predict demand with an RMS error below 2.5% for validation data, using just a 5% of the available dataset for the model identification. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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