Abstract
The increased integration of renewable energy sources, in particular wind and solar power, calls for changes in power system operation. Current market designs that are only efficient to accommodate limited uncertainty are highly challenged
by the partly predictable renewable energy generation. Hence, innovative market structures have been proposed to cope with the uncertainty introduced. Nonetheless, the quality of wind power forecasts may affect the market outcome due to their inaccuracy. For this reason, a framework is proposed to examine market-clearing algorithms, both deterministic and stochastic approaches, under imperfect wind power forecasts in order to quantify their influence on the market outcome. Results show that mean value mismatch between “estimated” and “realized” distributions has the highest impact on total system cost. Finally, it is examined if cost recovery for market players is guaranteed in the presence of inaccurate wind power forecasts.
by the partly predictable renewable energy generation. Hence, innovative market structures have been proposed to cope with the uncertainty introduced. Nonetheless, the quality of wind power forecasts may affect the market outcome due to their inaccuracy. For this reason, a framework is proposed to examine market-clearing algorithms, both deterministic and stochastic approaches, under imperfect wind power forecasts in order to quantify their influence on the market outcome. Results show that mean value mismatch between “estimated” and “realized” distributions has the highest impact on total system cost. Finally, it is examined if cost recovery for market players is guaranteed in the presence of inaccurate wind power forecasts.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of IEEE International Energy Conference 2016 |
| Number of pages | 6 |
| Publisher | IEEE |
| Publication date | 2016 |
| ISBN (Print) | 978-1-4673-8463-6 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | 2016 IEEE International Energy Conference - KU Leuven , Leuven , Belgium Duration: 4 Apr 2016 → 8 Apr 2016 https://ieeexplore.ieee.org/xpl/conhome/7507294/proceeding |
Conference
| Conference | 2016 IEEE International Energy Conference |
|---|---|
| Location | KU Leuven |
| Country/Territory | Belgium |
| City | Leuven |
| Period | 04/04/2016 → 08/04/2016 |
| Internet address |
Keywords
- Bilevel programming
- Electricity markets
- Renewable energy forecasting
- Stochastic programming
