PES was delighted to have the chance to speak with Mahmoud Hamada, PhD, MBA, Managing Director of SAMAWATT, to find out how machine learning algorithms can help reduce grid imbalance penalties. With government subsidies covering these penalties no longer an option, how can small and medium-sized renewable energy farms without the necessary market trading expertise, have other options than PPA to reduce the imbalance risk? Read on to find out more…
PES: Firstly, welcome to PES Wind Mahmoud, I’m looking forward to our conversation. As a business that aims to help wind and solar power producers reduce electric grid imbalance penalties, perhaps we can begin by looking at how the imbalance occurs and just how big a problem it causes?
Mahmoud Hamada: Thank you for the warm welcome. Yes, wind and solar farms have a fundamental problem: their power production is intermittent because it depends on unpredictable weather conditions.
This intermittent production causes instability in the electric grid system, so to incentivise greater accuracy in electricity production forecasts, the grid operator levies grid imbalance penalties on the producers whenever there is a deviation between forecast and actual electricity injection into the grid.
