Name
Title | ||
|---|---|---|
Enabling coupled models to predict the business impact of weather on electric utilities. |
Abstract | ||
|---|---|---|
Efficient, resilient, and safe operation of an electric utility is dependent on the local weather conditions at the scale of its infrastructure. This sensitivity to weather includes such factors as damage to distribution or transmission systems due to relative extremes in precipitation or wind, determining electricity demand and load, and power generation from renewable facilities. Hence, the avai... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1147/JRD.2015.2489478 | IBM Journal of Research and Development |
Keywords | Field | DocType |
Atmospheric modeling,Predictive models,Wind forecasting,Data models | Meteorology,Predictability,Renewable energy,Electric utility,Computer science,Real-time computing,Stochastic modelling,Transmission system,Weather forecasting,Reliability engineering,Electricity generation,Numerical weather prediction | Journal |
Volume | Issue | ISSN |
60 | 1 | 0018-8646 |
Citations | PageRank | References |
1 | 0.41 | 7 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lloyd A. Treinish | 1 | 84 | 13.67 |
| J. P. Cipriani | 2 | 8 | 1.44 |
| A. P. Praino | 3 | 4 | 0.96 |
| Amith Singhee | 4 | 347 | 22.94 |
| H. Wang | 5 | 5 | 0.89 |
| Mathieu Sinn | 6 | 10 | 3.65 |
| Vincent Lonij | 7 | 1 | 1.09 |
| Jean-Baptiste Fiot | 8 | 10 | 1.98 |
| Bei Chen | 9 | 26 | 9.11 |