The Use of Probabilistic Forecasts: Applying them in Theory and Practice
| Autor: | Sue Ellen Haupt, John Zack, Timothy Miller, Matthias Lange, Corinna Möhrlen, Mayte Garcia Casado, Michael Davidson, Pengwei Du, Jan Dobschinski, Amber Motley, Rui Pestana |
|---|---|
| Přispěvatelé: | Publica |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
grid integration
Electrical load Meteorology business.industry 020209 energy Probabilistic logic Energy Engineering and Power Technology forecasting 02 engineering and technology 021001 nanoscience & nanotechnology Grid probabilistic Unit (housing) Renewable energy Variable (computer science) 0202 electrical engineering electronic engineering information engineering Environmental science Electricity Electrical and Electronic Engineering EPS 0210 nano-technology Energy source business |
| Popis: | Much of the electric system is weather dependent; thus, our ability to forecast the weather contributes to its efficient and economical operation. Climatological forecasts of meteorological variables are used for long-term planning, capturing changing frequencies of extreme events, such as cold and hot periods, and identifying suitable locations for deploying new resources. Planning for fuel delivery and maintenance relies on subseasonal to seasonal forecasts. On shorter timescales of days, the weather affects both energy demand and supply. Electrical load depends critically on weather because electricity is used for heating and cooling. As more renewable energy is deployed, it becomes increasingly important to understand how these energy sources vary with atmospheric conditions; thus, predictions are necessary for planning unit commitments. On the scales of minutes to hours, shortterm nowcasts aid in the real-time grid integration of these variable energy resources (VERs). |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|