By Navigating the Future of Energy through Trading, Forecasting, and Modelling
The global energy sector is experiencing an unprecedented transformation as the world focuses more on decarbonisation and sustainability. The integration of renewable energy sources such as wind, solar, and hydrogen is becoming more and more important in reshaping traditional energy systems, leading to an increased focus on energy trading, forecasting, and modelling. This is no longer just a question of transitioning to a more efficient and sustainable world but to develop tools and strategies that help balancing supply and demand.
Global renewable electricity capacity is expected to increase by over 60% between 2020 and 2026, reaching a remarkable 4,800 GW. Solar and wind power will account for nearly 95% of this growth1. While this rapid shift towards renewable energy is essential to combat climate change, it also creates a critical need for integrated approaches in trading, forecasting, and modelling to maintain system stability and efficiency.
Are We Really Ready to Leave Traditional Energy Systems in the Past?
Unlike traditional fuel-based power plants, which can be dispatched on demand, renewable energy sources are inherently variable and decentralised. As renewable energy sources are fully dependent on natural factors such as sunlight or wind, fluctuations in energy generation become harder to predict and manage. Take the example of a cloudy day, lack of sunlight is enough to cause a drastic reduction in the solar power output; or just consider a calm weather day, such has an immediate impact on wind energy production. This is where accurate forecasting is essential; the creation of advanced weather prediction models, integrated with energy forecasting tools not only allow grid operators and utilities to anticipate fluctuations but also know when and where renewable energy production will vary; this results in a better and more accurate plan for alternative energy sources or storage solutions to meet demand.
The fact that renewable energy systems are often decentralised, with power generation occurring at multiple points across the grid rather than at a few large power plants is actually a positive development. The democratisation of energy production at the source can certainly improve energy security although, on the negative side, it also complicates grid management as energy flows are no longer centralised and predictable. This is where sophisticated modelling comes into action, having energy systems account for numerous distributed energy resources including rooftop solar panels, wind farms and even energy storage systems (batteries) ensuring that energy is efficiently routed where it’s needed without overloading the system.
As the world shifts toward a digital and carbon-free future, intelligent technologies are crucial for integrating decentralised energy sources. However, their true value lies in helping utilities and traders predict market conditions and optimise trading strategies through detailed simulations of various scenarios. Direct impacts go towards more informed and accurate decisions on balancing supply and demand, reduction of levelised cost of energy (LCoE) and increased efficiency across the energy chain value.
How is Precision Energy Trading Powering the Growth of Dynamic Energy Markets?
In a world progressing towards decentralised and variable energy supplies, energy markets must become more dynamic and responsive. Global energy trading and risk management (ETRM) market size was valued at $1.382 billion in 2023, projected to reach $2166.9 million by 2032, exhibiting a compound annual growth rate (CAGR) of 4.2% during the forecast period2. In simpler terms, the ETRM market is expected to expand gradually each year as more companies and utilities invest in technologies that help them manage and trade energy more efficiently and handle the risks associated with energy market fluctuations.
Over and above that, traditional energy trading mechanisms, which often rely on long-term contracts and fixed schedules, are ill-suited to a grid dominated by renewables. For instance, in markets with a high penetration of renewable energy, surplus generation during periods of high solar or wind output can lead to negative electricity prices, while shortages can drive prices up. The positive of real-time trading platforms, enabled by blockchain or AI technology, is exactly what allows energy to be traded on a much shorter time scale, reflecting real-time supply and demand conditions. To a further conclusion, this kind of flexibility is what helps stabilising prices and ensuring that renewable energy can be efficiently utilised.
Still on the same topic, the growing emphasis on carbon trading as part of global climate action underscores the need for more robust trading systems. Estimates show that carbon pricing initiatives now cover more than 20% of global GHG emissions. By 2021, the value of global carbon markets had grown by 164%, reaching $861 billion3. Enough is to conclude that effective energy trading systems can clearly play a substantial role not only for trading electricity but also for carbon credits, resulting in incentivised businesses designing clear targets to reduce their carbon footprints and invest in cleaner and more efficient technologies.
On the same level, it is important to reinforce the importance of collaboration between technology innovators, utilities and policymakers. Startups and companies focusing on energy trading, forecasting and modelling are already making significant progress in addressing the challenges posed by the transition to renewables. However, success in this endeavour requires continuous innovation and adaptation. As renewable energy capacity continues to grow, energy systems will need to become even more sophisticated, going further on the use of AI, machine learning, and big data analytics to manage the increasing complexity of systems. Enough is to say that this statement could summarise Free Electrons’ mission to support the growth and implementation of cutting-edge energy technologies by connecting energy companies with innovative startups, hence marching towards the adoption of sustainable energy solutions in an ever-accelerating future.
Meet the Free Electrons Alumni Revolutionising this Area
Over the past few years, the Free Electrons program has been thriving inside the energy sector, making significant advancements in crucial areas of energy trading, forecasting and modelling. Other than bringing together startups and utilities from all over the world, it is actually contributing to a bigger change by trying and further implementing groundbreaking solutions that will impact on both short- and long-term futures. Below, a few of the most impactful examples that are revolutionising the grid in this area.
Solandeo is a German startup that provides AI as a digital service for energy traders and grid operators, mostly focused on advanced metering and data management solutions on renewable energy sources. Their Measuring Point Operation technology shows already quite a forward-thinking approach, combining real-time data monitoring with advanced predictive analytics hence, enabling for a fully automated forecasting and autonomous trading of energy in the day-ahead and intraday electricity markets.
In 2019, Solandeo partnered with ESB to pilot wind forecast optimisation for energy trading leveraging Solandeo’s advanced predictive analytics and machine learning technologies to maximise the efficiency of renewable energy trading. In further analysis, this collaboration has aimed to create a system that could respond dynamically to market conditions, thereby improving profitability while ensuring stability in the energy supply4.
Gaiascope is an American startup that specialises in providing software solutions that enhance profitability of renewable energy assets and energy storage starting by offering precise electricity market forecasts. Their unique selling proposition lies in their technology, Terra, a software platform that combines machine learning algorithms with physical grid modelling to deliver precise forecasts across multiple timeframes. This platform is particularly valuable in highly volatile energy markets, as it provides detailed, probabilistic forecasts for nodal, hub, and load zone prices, allowing for energy traders and utilities to make informed trading decisions.
One noteworthy collaboration was with Origin Energy back in 2022, where the main focus was on leveraging Gaiascope’s proprietary Terra platform to optimise energy trading strategies. Its advanced capabilities in analysing congestion, outages, and power flow were of great importance in this area, enabling better predictions on price movements and optimisation of bidding strategies inside energy markets, particularly in regions such as in the Electric Reliability Council of Texas (ERCOT)5. If anything, this participation has demonstrated the potential of AI-driven platforms like Terra to enhance performance in the energy sector by enabling better market participation and optimisation of the use of renewable assets.
Still inside American lands, Salient Predictions specialises in long-range, probabilistic weather forecasting using AI and machine learning to deliver accurate sub seasonal-to-seasonal (S2S) forecasts, which range from 2 to 52 weeks in advance. In the face of pressing global warming challenges, their S2S model provides actionable insights to sectors like agriculture, energy, and finance, helping decision-makers to address climate-related risks and vulnerabilities. Based on a comparison of the Continuous Ranked Probability Score (CRPS) to reference models, their accuracy in predicting temperature and precipitation gain can reach up to 50% over industry benchmarks, integrating ocean and land-surface data that could improve the accuracy of their forecasts beyond traditional models like NOAA’s GEFS6.
In a partnership started with Hydro Québec after meeting during the seventh program edition, Salient’s hybrid forecasting tool, combining AI and physics-based weather models was crucial for predicting water inflows to Hydro Québec’s dams and in optimising energy market transactions. This initiative has most certainly shown great accomplishment in project development but, most importantly, it presents great potential to a future progressing towards decentralised and variable supplies.
Education for Change
These collaborations are certainly not enough of a claim to show that the world is fastly adapting and progressing in this sector although, it is enough to conclude the world really needs to start rethinking how we manage and operate energy systems. To progress further, people need to be educated on how to adopt more sustainable measures and, that is exactly what Free Electrons aims when connecting progressivist startups with utilities. Other than piloting and developing impactful solutions, the program is potentiating opportunities for people to discuss current challenges and vulnerabilities in the energy sector and further on, adapt their technologies taking into consideration not one, not two but the various concerns that have led to a decentralised and vulnerable sector.
Energy trading, forecasting and modelling are essential components of a stable and efficient renewable energy future. By embracing these tools and fostering innovation, we can ensure that renewable energy is not only abundant but also reliable, affordable and accessible to a greater number of people. With significant potential for energy security, optimised grid management and better use of renewable energy resources, the path to a more sustainable future becomes clearer.
Gain further insight on the impact of predictive technologies on renewable energy integration at Free Electrons!
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