It’s what everyone is looking for – the way out of the energy crisis. More energy efficiency, less CO2 and of course cost, cost, cost. But does Smart Energy really provide the decisive answer? What exactly is behind this new solution approach? How do companies benefit from this in concrete terms? We talked about this in an interview with our CTO Thomas Stammeier.
Thomas Stammeier: “The term Smart Energy Solutions refers to a new solution approach in which we combine IoT data on the status of machines and systems with energy data, i.e., values for the generation and consumption of a plant, for the first time. We also incorporate external data sources e.g., forecasts on weather, solar yields and electricity prices. All of this data is then combined in an intelligent planning algorithm to enable companies to plan for a specific time horizon in a cost-optimized way – and also in a way that optimizes emissions in the long term.”
Thomas Stammeier: “Companies can optimize several things with the help of Smart Energy Solutions: For a start, building and infrastructure control – this includes, for example, improved use of self-generated solar or PV power and optimal utilization of battery storage. Which, by the way, can also help to avoid peak loads.
Secondly, the issue of cost. Those who do not purchase a fixed electricity quota and are not bound by a fixed price can save a lot of money. Currently, energy prices can fluctuate by up to 100% in a single day. Electricity should therefore be purchased at the particularly favorable time and used to replenish stored electricity – in an automated manner.
Thirdly, in perspective, it is about the entire planning of production processes. Energy-intensive production should only be ramped up when energy is cheap – and ideally also automatically. The prerequisite, however, is that a company is positioned to be energy-flexible.
Thomas Stammeier: “In general, we want to help companies uncover hidden optimization potential. A classic case is standby mode, in which machines can consume a lot of energy even though they are not producing at all, but – to put it simply – are merely staying warm. This unnecessary consumption can be detected manually. Our goal, however, is to replace manual procedures as far as possible with automated detectors in order to derive recommendations for action algorithmically. Here, we are talking about Energy Optimizer algorithms.”
Thomas Stammeier: “Here, we rely on a combination of established machine learning algorithms for predictions and classical optimizer algorithms for planning such as Mixed Integer Linear Programming (MILP for short). What we do is map physical conditions, such as the power grid or PV systems, but also the machine consumption of a manufacturing plant, and the state of charge of a battery storage system, into a mathematical model. The algorithms can then be applied to this. In other words: We model a piece of reality mathematically in order to be able to optimize on it.”
"Companies that do not limit themselves to the classic energy management view, but want to improve their energy efficiency proactively, should make the move into Smart Energy now. In our eyes, the time is right to bring together the two dimensions of IoT data and energy data."
Thomas Stammeier: “We are currently piloting Smart Energy Solutions at a leading German automotive group. A comprehensive evaluation of the project will be available in early 2023, but the recommendations for action are already very valuable for the customer and can be implemented directly. For example, the Energy Optimizer algorithms provided concrete suggestions that have succeeded in significantly improving the feed-in and utilization of battery storage. Here, recommendations are given as an outlook for the next 48 hours and visualized in a planner output graph.”
Thomas Stammeier: “Companies that do not limit themselves to the classic energy management view, but want to improve their energy efficiency proactively, can approach us at any time. First, we will assess to what extent Smart Energy Solutions are target-oriented for the specific application (production, building, etc.) and if they can also be used effectively. If that’s the case, we start to bring IoT and energy data collection together. We know that this is often difficult in companies, or at least it seems so. But that is precisely where our expertise lies. In our eyes, it is high time to bring both dimensions together – not least in the energy crisis, but also because the energy landscape is becoming increasingly flexible and IoT data is becoming more readily available.”
Find out more about Smart Energy Management in our Solution Paper.
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