INTERVIEW - TokWise uses big data, ML to lift power producers' profits

INTERVIEW - TokWise uses big data, ML to lift power producers' profits

TokWise is a technology company that brings data-driven solutions for renewable players, giving them a competitive advantage on the market. “Our proposition is focused on increasing the value of each MWh of green power on the market and maximise profit for our clients,” said Vassil Vassilev, Co-founder and Technical Lead at the company. Tokwise combines big data with proprietary Machine Learning-based algorithms to add an extra intelligence layer on the trading operations of their clients. Fine-tuning and optimisation are based on a wider spectrum of market signals and efficient risk management approach.

Automation” and “big data processing” nowadays are frequently used expressions when it comes to trading platforms but they often remain somewhat of an enigma. Can you de-code for us what’s the essence of TokWise’s solution? What kind of data do you process and how is that plugged in the everyday decision-making process of your clients?

The energy industry is transitioning to a more data-driven business model and the old-fashioned toolsets are no longer capable of efficiently managing the complex market dynamics. To describe the intensity of the change - just imagine 1.6 million records per day representing a rolling forecast for a small green portfolio of just 5-6 solar and wind parks. An impossible task for a digitally-unarmed human.

TokWise Portfolio Management Suite is a solution bringing solid digital tools. The platform connects the assets and the market in a centralised place to easily orchestrate all activities from forecasting, trading and scheduling topped up with advanced analytics.

The automation chain drives higher efficiency and market responsiveness of the energy players. On the side of big data processing, we have embedded artificial intelligence capabilities that support the commercial processes by narrowing down the market and grid complexity into tailored suggestions for improved trading strategies.

It sounds like TokWise’s solutions are perfect for SMEs but would you say that big corporations could also benefit from your services and are there any differences to the challenges that these two types of clients are facing?

The current market situation with these extreme volatile conditions across Europe is challenging for any company regardless of its size. The difference is what technology they are ready to adapt. Larger companies are now interested in exploring and adopting solutions based on machine learning to improve their trading operations. We have designed our Commercial & Forecast Optimization solution to add an extra intelligence layer and optimise their operations. The solution is based on proprietary algorithms that process large amounts of data to encompass market, grid and assets conditions and output optimised trading strategies. Thus, we improve the bidding by arbitraging across various energy markets and increase the EUR per MWh return.

TokWise is a young company but you already have clients in five different markets. What would you say are the differences between Western European markets and Bulgaria? Are there specific challenges that Bulgarian green energy companies are facing?

The market maturity and liquidity in Western Europe are differentiating factors. However, Bulgaria achieved two important milestones – to integrate with the Single Dayahead Coupling with Greece and Romania. This integration provides new opportunities for the energy market players in the SEE region.

The green companies in Western and Southeastern Europe are facing more or less the same challenges: a fade-out of the subsidy and transition to a merchant regime, volatile and unpredictable markets and increasing costs. All of those factors require new capabilities to sustain the business models and this is exactly our mission - to support renewable companies during the transition.

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