intEMT® is a modular and flexible software-toolbox for intelligent energy management designed to model, simulate and optimize complex energy systems. Its five core libraries can be used standalone or in combination, enabling tailored solutions from component-level modelling to full-scale intelligent energy management.
The overall goal of intEMT® is to support the analysis and optimization of energy systems and components. For this purpose, intEMT® provides various modules that assist and simplify the different phases of optimization. The focus is on the simulation-based investigation of the energy system in order to enable non-invasive optimizations and studies.
The "optimization-cycle" start with the data acquisition and analysis. In this stage, all input data is prepared for the further steps and a systematic evaluation is performed.
Based on the data analyis, operational strategies will be developed in the next step. The purpose of these strategies is to calculate and provide setpoints for the components, while taking into account various optimization goals. There are two different levels of strategies:
In the step simulation and optimization, a digital twin of the energy system is developed. The model is used for scenario-based investigations (e.g., energy supply scenarios) and for optimal dimensioning of the components. Note the feedback to the operating strategies: these are also consolidated with the help of the digital twin and adapted as necessary.
The last step, the implementation phase, involves developing the automation functions and implementing them in the real system. Here, too, there is feedback: on the one hand, back to the simulation, and on the other, back to the start, true to the motto “after optimization is before optimization.”
The strategies are classified into different levels, which differ primarily in terms of the time basis on which the cyclical calculation is performed and the type of methods used.
In principle, intEMT®’s energy management and operational strategies consider three different levels:
The local operational strategy provides an initial, fully operational strategy for a component or a combination of components. However, as only local data (e.g. measured values from the plant itself) can be taken into account, the component is not necessarily operated at the operating point that is optimal for the overall system. This is where the higher-level energy management system comes into play, providing the local operating strategy with recommendations for setpoints and thus enabling optimisation targets to be met.
One of the advantages of this approach is that, in the event of communication problems or setpoints from the energy management system that cannot be implemented, the components still continue to fulfil their function (e.g. heat supply), although they may not be operating at the most efficient operating point.
intEMT® | intelligent Energy Management Toolbox