SCOTT HARDEN Yes, and this is a great question because it addresses the growing need for bidirectional controls in the power systems, and we believe that data and AI are going to be at the heart of the solution. I’ll give you an example of working with another customer. And I think these real-world examples really try to help… They help set the context. This one is another story from the Nordics actually. A Norwegian DSO, Agder Energi, they had a substation that was running over its capacity just by a couple of megawatts for a few days or a few weeks during the winter months. So, by design or by typical asset cycle, they would have to actually replace that, but the cost was going to be $5 million to replace the substation.
So, as an alternative, they partnered with Microsoft to connect demand side flexibility to dispatch load or increase supply when forecasting an overload situation. We provided the capabilities to forecast the substation load based on historical data, smart metre information and weather data, as you asked. Our capabilities in Azure, our machine learning capabilities, were used to deliver this forecast in advance. And then we built an optimization service in Azure to select and dispatch the most beneficial load or distributed resource based on the asset profile, current or future state. And we leveraged price signals from the market and other properties. The end customer that Agder Energi is serving was given a price to make those assets available, and a higher price if their flexibility was actually leveraged. The reporting back to Agder Energi was provided by way of Power BI reports, and that would show assets, load, customer and price and dispatch situations. The retailers, they had the end customer relationship, a contract. And so, the DSO made a bid to the retailer in overload situations. And the DSO has the visibility into what demand-side flexibility the retailer has within its portfolio. The next phase of the project is to create what we see as a decentralized energy flexibility marketplace where DSOs can bid for demand-side flexibility and the retailer and the energy service company and aggregators can offer demand to this market.
A great partner to engage in this was the existing market operator for 15 of the European countries, called Nord Pool. And so, Agder Energi and Nord Pool created an organization called NODES, a joint venture. And this marketplace is actually in place today, and it’s running on Azure, and it’s matching bids and offers. And we’re running pilots in ten countries in Europe, across 15 different project areas. In these projects, the DSOs, TSOs and aggregators are all collaborating. And the market design for Europe is also integrated with these wholesale markets, capacity markets, and day-ahead and intraday markets. And we see this as a model because in the United States, there was a recent FERC Order, FERC Order 2222, that essentially will allow aggregated resources to be bid into the wholesale energy markets in the United States. And there is the potential, and FERC’s guidance on this projects that this could have an impact of up to 360 gigawatts of power that is generated at the edge of the grid by 2025. And that’s astounding. And so, this marketplace model we see as a model that will be emerging here in North America as well as in many other regions around the globe. And we really see the need for software to play a central role for that, to provide the capabilities to aggregate those resources and bid them back into the market.