Name
Abstract | ||
|---|---|---|
The increasing penetration of renewable energy sources and the need to adjust to the future demand requires adopting measures to improve energy resources management, especially in buildings. In this context, PV generation forecast has an essential role in the energy management entities by preventing problems related to intermittent weather conditions and allowing participation in incentive programs to reduce energy consumption. This paper proposes an automatic model for the day-ahead PV generation forecast, combining several forecasting algorithms with the expected weather conditions. To this end, this model communicates with a SCADA system, which is responsible for the cyberphysical energy management of an actual building. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-86230-5_14 | PROGRESS IN ARTIFICIAL INTELLIGENCE (EPIA 2021) |
Keywords | DocType | Volume |
Energy management system, Forecast, PV generation | Conference | 12981 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brigida Teixeira | 1 | 0 | 2.37 |
| Tiago Pinto | 2 | 68 | 25.43 |
| Pedro Faria | 3 | 136 | 25.00 |
| Zita A. Vale | 4 | 390 | 85.67 |