Localizing weather forecasts for enhanced heat load forecast accuracy in urban district heating systems

ABSTRACT

Weather forecasts are essential for district heating (DH) utility operations as they prepare the utility for future consumption, thus ensuring optimal operation by supplying sufficient heat while keeping costs low. Weather forecasts are usually converted into heat demand forecasts, which are used for production planning and control of the temperatures in the network. Hence, increasing the accuracy of weather forecasts will lead to improvements in the system's operational performance. However, numerical weather predictions (NWPs) are computed over the earth as grid values, and NWPs are designed for rural areas, not urban areas. Therefore, we propose to localise the weather forecasts to the urban environment by calibrating them using Model Output Statistics. We show that localising weather forecasts (removing the bias) leads to enhanced accuracy in the heat demand forecasts. In our case study, localised weather forecasts lead to an error reduction between 1.5% and 2.5% when compared to forecasts using uncalibrated NWPs.

KEYWORDS:

• Forecast calibration
• recursive estimation
• heat demand
• localised weather forecast
• urban heat island

Acknowledgments

The authors would like to thank HOFOR for making their data available and for their support.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Figure created using Google Maps.

2 European Centre for Medium-Range Weather Forecasts (ECMWF), HRES – High-Resolution Forecast.

Additional information

Funding

This work is funded by the Innovation Fund Denmark through the project HEAT 4.0 (8090-00046B), TOP-UP (9045-00017B), FED (8090-00069B), and SEM4Cities (0143-00032B). The project 'IEA HTP Annex – IoT Annex – Digitalization and IoT for Heat Pumps' (EUDP – 64020-2071) and the IDASC (18012745) project funded by the Region Hovedstaden and the IEA TS4 annex on Digitalisation of District Heating: Optimised Operation (and Maintenance) of District heating and Cooling Schemes via Digital Processes Management funded by the EUDP Denmark, have also supported this work.