APUEA Magazine | No.2 / 2018
The Art of Renewable Energy Forecasting By Mikkel Westenholz, Managing Director, ENFOR
Why Forecast Renewables?
BeneďŹ ts
+ Support the transition to renewables and reduce CO2 emissions
+ Enable the ability to
manage large amounts of renewable energy
+ Lowers the cost of
balancing renewable energy (reducing cost of standby capacity)
+ Increase the security of supply
In order to reduce CO2 emissions, the share of renewable power production (especially wind and solar power) increase in many countries around the world. As renewable power production increase, the electricity systems face a new challenge due to the fluctuating and intermittent nature of renewable power production. As wind, solar, wave and hydro power all are highly depending on weather conditions, the ability to forecast the weather and accurately transform it to a power forecast, becomes as key competence. For countries like Denmark, where wind power alone makes up for more than 40% of the annual power consumption and where renewable power can make up for more than 100% of consumption in individual hours, accurate renewable power forecasting becomes system critical. The forecasting solutions provided by ENFOR has been operational since 1994 and have supported the transition of the electricity system both in Denmark and many other countries.
How to Forecast Renewables Operational power forecasting typically has a time horizon of a few minutes ahead and up to approx. 2 weeks, which can thereby be used for short to medium term planning of power production. Such power forecasts are based on weather input from global and regional weather models. The weather forecasts are then combined with local measurements from the renewable power assets. Accurate forecasts can be achieved by feeding off-line production data on a regular basis (once a month or similar) such that machine learning algorithms can automatically adapt to the data and
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