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When you name your company after a German phrase that translates to “sunny weather,” it’s an indication of an optimistic outlook. That forward-looking approach is what drives innovation at Kaiserwetter Energy Asset Management, a global renewable energy company that delivers specialized services to help investment firms, banks, and governments have visibility into their investments in solar parks and wind farms around the world.

SAP Leonardo Intelligence Inspires ARISTOTELES

As it was building its cloud-based Internet of Things (IoT) platforms, Kaiserwetter turned to SAP intelligent technologies for the framework it uses to support its core product, known as ARISTOTELES. Rather than creating these innovations from scratch, Kaiserwetter opted to combine smart data analytics, predictive analytics, and machine learning from SAP into what it describes as a data-analytics-as-a-service product (DAaaS).

We had the opportunity to speak with Kaiserwetter CEO and Founder, Hanno Schoklitsch, to hear about how the ARISTOTELES platform interconnects technologies such as artificial intelligence (AI), machine learning, IoT, and predictive analytics to help its customers maximize their investment returns while minimizing risk.

Ann Marie: Could you tell us a bit about what Kaiserwetter does? Who are your typical customers and who are the end users of your dashboards?

Hanno: Our end users are investors and investment funds. We’ve been doing this work to catalyze investment into renewable energy. As we all know, there’s a need for a lot of capital to support putting more renewable energy production in place so that we can achieve a zero-emission future.

On the other side, we also are talking to lending banks about unlocking the capital for financing renewable energy. The idea is to understand how we can really maximize returns of the cash flow from these investments while minimizing risk and offering transparency to our stakeholders. This is exactly what we are bringing together from all the data and analytics in our products and what we provide to our clients through our dashboards.

Ann Marie: What types of projects are these banks funding?

Hanno: We are funding wind parks and solar parks. And we are now working on integrating our first hydropower station into our ARISTOTELES platform—of course, using all the great services that SAP is providing us to get our data in the right place and run our analytics.

Ann Marie: Tell me a little bit more about what your ARISTOTELES platform does and how it’s different from anything else on the market.

Hanno: One of the essential differences is that we have data as a service as our business angle. We are not talking about software as a service. We are gathering the data for our clients, adding analytics, and giving it back to them in a format they can use to make decisions.

Everybody knows that there’s a lot of data flying around. It’s not about just collecting the data but getting the right support in place to draw the intelligence out. This is exactly what we are offering to our clients. Our clients achieve data transparency. Using SAP Data Intelligence, we are finding insights and delivering financials to our dashboards.

For the investors who are our clients, we must reinforce how their capital is performing and whether any issues may arise from a particular site that could affect their capital.

Ann Marie: How does the platform help your customers make decisions? You mentioned that it provides information to help them decide not only to make the investment in the first place, but also to manage risk once they do.

Hanno: When we are analyzing specific machines, we use modeling. For example, each of the wind turbines at the wind farm has a barcode, which is delivered by the manufacturer. In some cases, we model what this wind turbine will do—even though it is not data coming from the actual turbine.

So, it’s not just data collection or something like business intelligence. It’s getting the data from the asset, and that data speaks to the modeling data. Then we get the data into a bar curve and watch for where any deviation is coming from. That gives us the right baseline in a smart data analytics approach.

Ann Marie: How does SAP technology come into the picture?

Hanno: We are applying AI and SAP Data Intelligence to put machine learning algorithms in place while using the capabilities of computing power from SAP to run our models.

This gives our clients the ability to see if there is a potential trend happening and to identify this at an early stage, which is a big, big advantage for them. We put our machine learning in the front end of our product. Our clients are opening their notebooks or desktops in the morning and they can see—What is the machine learning algorithm telling me? What is the forecast of my energy production?

They can see the standard deviation between the analytics and the real production. If this deviation is increasing, then you potentially have already identified an issue coming up. They can monitor the first stage to understand the performance of their assets and whether there are any problems with the performance.

This is a great step to not just have data and make nice and shiny charts out of it. In the end, what we are offering is much more than a reporting setup.

Ann Marie: You are using SAP Leonardo for AI, data intelligence, and IoT services. What devices are you connecting and monitoring through IoT?

Hanno: We are using an IoT setup and putting the connectors into the SAP Cloud Platform using Docker containers, which are then retrieving the data from each of the assets. This is one of the points where we are connecting directly with the assets at wind farms and solar parks all around the world. We are collecting the data that is coming out of each operation and using software on-site to gather the data, which is stored for 10 minutes and sent to us. This is sufficient for our analytics to do the right correlations between the data.

Ann Marie: How do you integrate predictive analytics into the process?

Hanno: This is what we use machine learning for. We can predict what energy or power the asset should be creating within the next few hours. And then we have the real data coming from the asset. If this does not match or shows an increase in the deviation, you can already see that there is an issue coming up. Based on these numbers, you can set measures to avoid any potential threat or negative impact.

We have returns of 95–97%, which is great performance that we can show to our clients. This is possible because we are using the machine learning algorithms we have put in place and because of our computing power, which we get from SAP.

Ann Marie: How do you build your data models?

Hanno: We start with prefabricated models from SAP, which, of course, must be customized to meet our needs. We have our own data scientists who adjust these prefabricated models. If we don’t have what we need, we also make our own customized models. I think the prefabricated models are helpful, but you really need your own data scientist team.

Ann Marie: How do you incorporate weather data into your analysis?

Hanno: We have third-party weather data that we are integrating for the wind and solar parks. This is not just a weather model itself—we are actually getting the power forecast based on the weather models. We look at the power the machines are expected to produce for the next 24 hours, and then for three to seven days.

Ann Marie: Why did you choose to rely on the cloud for your solution?

Hanno: I think it’s the only way forward to handle all this big data stuff. We already have so much data that we see no other possibility than using the cloud. We are a smaller company—but even for medium-sized companies—I think the future must be run by the cloud. The cloud was critical to get the high-performance data management we needed, as well as having SAP HANA in place for its in-memory, high-speed data analytics. This was, to us, essential to our operations.

Ann Marie: I would assume that having a cloud-based solution makes your offering more accessible to your customers, as well.

Hanno: Absolutely. We have so many possibilities now. For example, we have customers who do the data analytics with an application on-site and they may be in a location with extra-cloudy weather. They are connecting edge servers to the SAP Cloud Platform to get the data and analytics on our platform.

We are seeing an increasing world of different setups out there, which we have to adopt quickly into our platform. The SAP Cloud Platform allows us to adapt quite fast to these ongoing changes in different data integrations with assets connected by IoT. We are always looking to connect faster and better. Data quality is essential to us, and we are working to improve data integrity. As we bring our technology to different areas in the world, we are thankful to have the use of SAP capabilities.

Ann Marie: What advice would you offer other SAP customers who are looking to use AI and machine learning?

Hanno: I am an entrepreneur. When we transitioned to a digital company, for me it was crucial not to build our own platform completely by ourselves. I’m convinced that it’s much more diligent to use the platforms that technology companies are already providing that can be customized to your own business model.

We are building a business model that relies on a technology platform that SAP is providing using AI, IoT, and SAP Analytics Cloud. The whole product suite of SAP is quite big. And working with SAP is great because you get computing power. If you would like to perform AI on your own, you will ultimately be limited in the end by your computing power. Getting the computing power to do this is a big advantage.

Finally, you need to have data scientists on your side to work with AI and machine learning. It’s not that easy. Even with the prefab models, you need data scientists who understand your business model and who can really focus on how you can support that model using AI.

Ann Marie: Over the long term, how are your solutions helping institutions invest more sustainably?

Hanno: If you’re going, for example, to invest in these kinds of assets in other countries—even in the U.S. or Europe or South America—you are facing a potentially higher risk/return profile. You have to watch what is going on, and that is what we’re doing. The technical part of these investments, we have completely under control. We know exactly what the machine is telling us and what energy it is producing. We have the financials under control. We know where the accounts are, as we are connected with the banks and we know where the cash is. In the end, this is highly efficient risk management. What we have today, we wouldn’t have had the technology to do two or three years ago. Now, you can invest in different markets, even if the risk is higher, because we can control that risk in a different way.

We can also turn the world around on the financing of solar and wind farms, or other similar projects, by talking to the lending banks. How are they currently watching their credit/loan portfolios? I think this must change completely. Currently, banks are looking into the past. They are granting a loan to a customer for a wind farm or solar park. And then the customer has the obligation to send them reports on a monthly basis. All of these reports are looking into the past. We have to change this—we have to look into the future.

And this is exactly what Kaiserwetter already provides. You can look into the future and see if there’s a potential issue coming up. Distressed assets should not suddenly become a problem for banks if they are using data to predict the performance of these assets in the future.

As for the next possibility? Informatics is here. What if you opened your desktop or laptop and it started talking to you? We have identified which of your investments will have potential threats coming in three or four months. This is the future—the machine is talking to you and you can act. This type of data could help drive your decision-making process.

Ann Marie: Hanno, thank you so much for your time today, and for explaining how you support investors in renewable energy.

Hanno: Call me whenever you want to have good weather. You know, Kaiserwetter is known for making good weather.

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