SMOOTH-MOEA

Simulation Model for Optimized Operation and Topology of Hybrid energy systems – Multi-Objective Evolutionary Algorithm

What does SMOOTH-MOEA help with?

SMOOTH-MOEA was developed by RLI scientists to model and optimize energy systems.

Who is the tool suitable for?

SMOOTH-MOEA is suitable for actors from the research and consulting field who want to solve complex optimization problems in the field of hybrid energy systems.

How does SMOOTH-MOEA work?

In SMOOTH, an energy system is abstracted to its various technical components, which allows detailed modeling (including non-linear and state-dependent behaviors as well as the tracking of arbitrary states of the components). SMOOTH uses the OEMOF framework with mixed-integer optimization and has been used in the past for the simulation of hydrogen energy systems, among others.

Using the Multi-Objective Evolutionary Algorithm (MOEA), the energy system can be optimized for costs and emissions, as well as to determine suitable trade-offs from various optimization goals. For this purpose, NSGA-II is used to determine the so-called pareto-optimal front by gradually changing components (design optimization).

What examples of use are there?

MOEA was developed as part of a master’s thesis entitled “Multi-Objective Optimization of Micro Grids using Evolutionary Algorithms (Wanitschke 2014)” at RLI. Due to the large library of components of the hydrogen economy, SMOOTH-MOEA is used in many hydrogen projects, such as the HyStarter and HyExpert projects.

How can SMOOTH-MOEA be used?

The program code is written in the Python programming language and is freely available on the online service Github.