Celebrating the 1-year anniversary of Trade Optimization

The last few years have seen a dramatic increase in renewable energy production worldwide and in Europe in particular. This increase is good news for the transition towards a low-carbon economy but also brings challenges.

Over and underproduction on a nationwide level caused by inaccuracies in the forecasts of renewable energy are mainly compensated with gas-powered plants that can rapidly respond when an imbalance occurs. Renewable energy producers pay so-called balancing costs when their actual production deviates from what they agreed to produce (position on the day-ahead market).

These costs have grown tremendously in the last two years. And, the expectation is that they will continue growing just as fast going forward.

Today, we’re excited to celebrate the 1-year anniversary of Trade Optimization, one of the key AI products that Dexter Energy offers its customers.

Trade Optimization is an automated trading strategy that helps big renewable power producers reduce balancing costs by including market surplus/ shortage predictions to optimize their positions on the day-ahead market.

It has been a great journey to develop this product. We first went live in the Netherlands in January; we expanded the product to Belgium in August and to Germany in November. In just one year, Trade Optimization helped save millions of euros of balancing costs for our customers. Furthermore, our trading strategies are helping to stabilize the grid, reducing reliance on gas-powered flexibility and preventing renewables curtailment, avoiding the emission of tens of thousands of tons of CO2. We could not be prouder of this fantastic achievement!

The product is the result of the smart work of a dedicated team and a supportive organization. We’ve continuously researched price forecasting in various countries as well as investigated optimization techniques. Furthermore, we’ve built scalable software with a high focus on code quality. The competencies that we needed to build, continuously improve and expand the product are a mix of machine learning, stochastic operations research, software engineering, and energy trading expertise.

I have been very fortunate to collaborate with Alessandro Gentile, Inge van den Ende, Lennart Heinemeier, and Zoltan Konarzewski on this product and to be supported by all other teams inside Dexter Energy. Looking forward to another year of helping renewable energy producers reduce balancing costs in even more countries and more markets through continuous research and development on this great product.