Function of a Multi-Parameter Study
The Parameter study varies several (main) Parameters (Parameters that are varied / Variable parameters) independently of each other and determines the resulting Output variables. Additionally, it examines the dependency of the Output variables on Additional coupled parameters that each depend on one Variable parameter.
The Parameter study repeatedly performs a series of Actions, varying one Parameter in each run to examine the dependence of the results on that Parameter. Typically, the Actions Simulation, Variant analysis, and Variant comparison are performed repeatedly, whereby, for example, a plant size in the energy system is varied in order to calculate the dependence of an economic parameter, such as the payback period, on the plant size. A Parameter study provides a broader overview of the solution space compared to Structural optimization, which also allows the determination of plant sizes. Because several parameters can be varied, the Parameter study is optionally a multiparameter study. It carries out not only one simple Simulation, but several, with which a parameter space is strategically searched using the given parameters. The sensitivity analysis, which belongs to the Parameter study, executes simulations for the Variable parameter and the Additional coupled parameters together step by step: firstly, with the first value of each parameter, then with the second interpolation point, and so on. In addition, all parameters are varied individually, while the other Parameters remain constant. In this way, a multi-dimensional parameter space is created.
Via a button, you can visualize, save, and print the Results of the Parameter study in variant-rich 3D and 2D plots with a combined web tool.
Application Areas
A Parameter study enables to find answers on the following questions:
- How sensitively does the energy system behave under other boundary conditions, such as rising gas and electricity prices?
- Which plant sizes provide the best trade-off between costs and CO2 emissions?
- How does the interaction of energy conversion plants and storage systems affect the self-consumption rate or the self-sufficiency rate?
- At what angle of inclination does the photovoltaic system have the shortest payback period?
The Parameter study serves the following use cases, among others:
- Optimal orientation and installation angle of multiple photovoltaic systems for maximized self-supply
- Effects of gas and electricity prices on the overall economic efficiency of a system
- Dimensioning of synergetic systems (e.g., photovoltaic, heat pump, battery storage) to maximize net present value, self-consumption rate, etc.
Coupled parameters can be, for example,
- operating costs coupled to the parameter system size (nominal capacity) and
- maximum loading capacity of a storage coupled to the parameter storage size (capacity).
For the energy system shown in the following scheme, for example, the system peak power of the photovoltaic system and the nominal thermal power of the heat pump are to be varied in order to determine the optimal sizes.
Tutorials
The following tutorials demonstrate how the Parameter study works:
Adding a Parameter Study to the Project
Add the Parameter study to the project using the Home ribbon (see following figure) or the context menu in the Project explorer.
The Parameter study node is inserted in the project tree at the bottom, and the form for the Specifications of the Parameters (Input requirements) is shown.
