C026 — Evaluating the Impacts of Weather Forecast Inaccuracy on Performance of Model Predictive Control for Dynamic Facades
Inaccuracy in weather forecasts and the impacts on predictive control systems are not yet well understood. This study evaluates weather forecast errors for U.S. Department of Energy reference cities and quantifies impacts on predictive control for dynamic facades. A stochastic noise algorithm emulated the forecast errors in simulation. Imperfect forecasts increased average electric cost by 13.3% and glare index by 41.5%, indicating that forecast error significantly decreases performance. However, bias correction largely mitigated the performance impacts to 0.0% for electricity cost and 3.0% for glare index. Future work developing practical bias-correction implementation methods is needed.
Product Details
- Published:
- 2022
- Number of Pages:
- 8
- Units of Measure:
- Dual
- File Size:
- 1 file , 940 KB
- Product Code(s):
- D-BCS22-C026
- Note:
- This product is unavailable in Russia, Belarus
