Name
Abstract | ||
|---|---|---|
This work is a contribution to set a nodal electrical load's forecasting model on real time. The model named PRENOD uses the Holt & Winters's seasonal method. With other models, they constitute the management system of the Electricity and Gas Enterprise's high voltage network. The proposed model should contribute to under control the electrical constraints due to the flow of produced power in the network. Moreover, it enables to take into account the new acquisitions by an update of the optimal model's coefficients. Furthermore, a correction algorithm of erroneous acquisitions has been developed in order to guarantee data's reliability necessary for the forecasting model. The algorithm is inspired from the track signals. Eventually, the validation results are satisfying as the Mean Absolute Percentage Error MAPE does not exceed 10%. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.3166/jds.15.97-114 | JOURNAL OF DECISION SYSTEMS |
Keywords | Field | DocType |
Forecasting model, Real time, Nodal electrical load, Track signal | Mean absolute percentage error,Electrical network,Electrical load,Computer science,Electricity,Control theory,Mean squared error,Artificial intelligence,High voltage,Reel,Management science,Approximation error | Journal |
Volume | Issue | ISSN |
15 | 1 | 1166-8636 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oumhani Belmokhtar | 1 | 0 | 0.68 |
| Nacéra Aboun | 2 | 0 | 0.68 |
| Abdelghani Rehal | 3 | 0 | 0.34 |