Use case
Robust nonlinear mathematical transmission expansion planning based on German electricity market simulation

Experts use Artelys Knitro to solve the transmission expansion planning and network reinforcements thanks to the development of large scale models and the opitmization of the making-decision process.

Relatively recent developments in power systems, such as the integration of renewable energy resources and the shift from centralized to decentralized energy generation technologies, have made transmission expansion planning problem (TEP) an essential but complex decision-making process.

TEP is a complex optimization problem that consists in determining where, when, and what reinforcements should be placed in the network, in order to guarantee consumers will be able to withdraw the desired quantity of electricity at all times, while making the transmission grid reliable, secure and stable as well as cost efficient.

Such a complex nonlinear optimization problem can be solved using Artelys Knitro which allows methodologies working for large-scale models to be solved in a robust and efficient way.

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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