Forecasting plays a vital role in maintaining an efficient and stable power grid. Generators need to be able to predict demand and generate power accordingly based on weather forecasts, historical data, and other key factors.
The power generated from renewable sources is intermittent, especially wind and solar energy. This means that power cannot be generated round-the-clock like in the cases of thermal or nuclear sources. Given that wind and solar power contribute to a significant chunk of the country’s power mix, forecasting and scheduling play vital roles in power generation and distribution.
April will mark the first quarter of AleaSoft’s collaboration with India’s central transmission utility (CTU). The company will provide PGCIL with generation forecasting for wind and power stations in the short term, including hour-ahead, day-ahead, and week-ahead forecasts with several granularities.
Granular data is detailed data, or the lowest level that data can be in a target set. It refers to the size that data fields are divided into, in short how detail-oriented a single field is.
It currently obtains forecasts from stations in Tamil Nadu, Karnataka, Andhra Pradesh, Gujarat, Maharashtra, and Madhya Pradesh.
Accurate forecasting of renewable generation has been a tough task for developers. The Central Electricity Regulatory Commission (CERC) had established a fee for errors based on a 15-minute time block and charges for deviation payable or receivable to/from regional deviation settlement mechanism (DSM) pools by renewable generators.
If the error is more than 15%, then additional charges for deviation will be levied along with the fixed rate.
Reference- Mercom India, AleaSoft PR, Economic Times, PGCIL website