Use case
Optimal coordinated operation of distributed static series compensators for network congestion relief
Researchers in the energy sector are using Artelys Knitro to meet the challenges of integrating renewable energy sources and ensuring power grid security. The results of their efforts include reduced computing time and the implementation of near-optimal control actions.

The electricity sector is shifting towards an increasing integration of renewable energy sources. Despite their advantages in reducing emissions, they give rise to problems associated with power grid security. Distributed Static Series Compensators (DSSC) may play an important role in improving the security of the operations of transmission systems, through corrective control actions aimed at relieving network congestions in real-time.

The resulting Optimal Power Flow model (OPF) is a complex mixed-integer non-linear optimization problem (MINLP) combining different objective functions. The problem needs to be solved in real-time to determine the corrective actions within an acceptable timeframe.

A hybrid methodology combining Artelys Knitro for solving non-linear programming problems (NLP) and a k-means clustering algorithm allows to generate close-to-optimal control actions in a reasonable computational time for realistically large systems.

Start with a tutorial!

 

You’re not familiar with nonlinear optimization? This tutorial will present some examples of nonlinear problems for various applications. You will discover nonlinear programming methods using the Artelys Knitro solver in a Python notebook, through different examples.

Free trial

 

Get your trial license to test Artelys Knitro’s performances on your own mathematical optimization problem. The trial package includes free support and maintenance. You can have access to Artelys Knitro for free with a 1-month unlimited version or a 6-month limited version.

Artelys Knitro has unmatched performance

Best Nonlinear Solver

Artelys Knitro has been ranked every year by public benchmarks consistently showing Artelys Knitro finds both feasible and proven optimal solutions faster than competing solvers.

Technical support

The Artelys technical support team comprises Artelys’consultants (PhD-level) who are used to solving the most difficult problems and deploying enterprise-wide optimization solutions. They can advise on algorithmic or software features that may result in enhanced performance in your usage of Artelys Knitro.

Updates and new features

The development team works continuously to provide two releases of Artelys Knitro every year. Based on feedback, we always improve our solver to meet users’ requirements and need to solve larger models faster.

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