Optimization Suite

• Python module for the simple definition and robust solution of optimization problems

• Python module for visualizing optimization and fitting results

• ModelFitter for Python analogous to ModelFitter for Excel

• Examples of optimization problems of varying complexity with links to various optimization algorithms

• Optimization add-on for MoBA Automation for automated optimization with many different boundary conditions and targets

• MUSCOD, a particularly efficient optimizer for dynamic optimization, optimal control, and non-linear model predictive control

• Calculation of complex models: By separating the methods for simulation and optimization, complex models can be calculated by suitable simulation solvers

• Robust steady-state and dynamic simulation techniques, especially for thermal systems 

• Integration into other software tools: for automation, visualization, evaluation and parallelization. Integration into the user's own software tools is also possible

• Support of various model formats: FMU (co-simulation and model exchange), Dymola models, TISC interface

• Use of various optimizers: open-source optimizers (e.g. Scipy), TLK's own optimizers (e.g. Nelder-Mead algorithm including globalization), commercial optimizers, and others

• Highly efficient dynamic optimization: the use of TLK Energy's MUSCOD optimizer enables highly efficient dynamic optimization, optimal control and non-linear model predictive control

Figure 1: Dynamic optimization of different refrigeration circuit topologies

• Stationary optimization: parameter optimization, e.g. for design optimization

• Dynamic optimization: parameter optimization for systems that are largely characterized by their dynamic behavior

• Stationary fitting: parameter estimation for the adaptation of models to stationary measurement data

• Dynamic fitting: Parameter estimation for fitting models to dynamic measurement curves

• Optimal control: trajectory optimization for control variables

• Design of energy-optimized heat pumps and refrigeration systems

• Structural optimization of cooling plates for electric vehicles

• Optimal control and regulation of heat pump clothes dryers

• Automated control parameter optimization for various ambient conditions

• Automated parameter estimation of refrigerant compressor models in a database