Name
Abstract | ||
|---|---|---|
Solar photovoltaics (PV), one of the most promising and rapidly developing renewable energy technologies, has evolved towards becoming a main renewable electricity source. It is termed variable energy resources since solar irradiance is intermittent in nature. This variability is a critical factor when predicting the available energy of solar sources. Capital and operational costs associated with solar PV implementation are highly affected when inaccurate predictions are carried out. This paper presents a new forecasting model for solar PV by utilizing historical inter-minute data to outline a short-term probabilistic model of solar. The proposed methodology employs a probabilistic approach to predict short-term solar PV power based on uncertain basis functions. The PV forecasting model is applied to power generation from a 13.5 kW rooftop PV panel installed on the Distributed Energy, Communications, and Controls (DECC) laboratory at Oak Ridge National Laboratory. The results are compared with standard time series approach, which have shown a substantial improvement in the prediction accuracy of the total solar energy produced. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CISS.2017.7926158 | 2017 51st Annual Conference on Information Sciences and Systems (CISS) |
Keywords | Field | DocType |
very short-term solar photovoltaic power forecasting,uncertain basis function,renewable energy resource technology,renewable electricity source,solar irradiance,solar energy source,solar PV implementation,historical inter-minute data,short-term probabilistic model,PV forecasting model,rooftop PV panel,Distributed Energy Communications and Controls laboratory,Oak Ridge National Laboratory,DECC laboratory,standard time series approach,power 13.5 kW | Mathematical optimization,Renewable energy,Simulation,Computer science,Photovoltaics,Solar energy,Probabilistic forecasting,Distributed generation,Solar irradiance,Photovoltaic system,Reliability engineering,Electricity generation | Conference |
ISBN | Citations | PageRank |
978-1-5090-2697-5 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jin Dong | 1 | 24 | 6.94 |
| Teja P. Kuruganti | 2 | 3 | 3.30 |
| Seddik M. Djouadi | 3 | 216 | 42.08 |