Grid Analysis

MCCS Grid Analysis: Handling all issues with Congestion, Stability & Voltage 

Grid Analysis provides an easy-to-maintain and highly scalable grid analysis and optimisation suite for system operators. By utilising traditional as well as AI/ML algorithms, it assesses the grid state, performs load-flow calculations, and contingency as well as stability analyses. Furthermore the Grid Analysis Suite optimizes grid operation, assets, and topology – across real-time and planning horizons.

There are two ways to use our algorithms. On the one hand, as tools to simulate, analyse, and create operator recommendations. On the other hand, you can integrate them into closed-loop systems.

The MCCS Grid Analysis Suite enables operators to steer the grid in the most efficient and safe way possible.

Use case

Covering the entire workflow, the Grid Analysis Suite supports network data preparation, state estimation, security analysis and optimization. This works equally during real-time operation as well as for simulations, forecasts and planning.

Benefit 

The Suite creates transparency about the grid status through real time predictive calculations and thereby identifies optimization potential, optimizes asset utilization and automates control measures. All with the goal of ensuring safe and economical grid operation despite growing complexity.

The technology behind it 

Grid Analysis is a modular, scalable software system within MCCS, based on open interfaces and container technology.

It uses various calculation engines (e.g., PandaPower, PowSyBl, and PowerFactory) for different types of grid calculations and optimizations.

How does it work? 

With standardized interfaces (e.g., CIM/CGMES, MCCS schema) used to import network models and measurement of data, various analysis, security, and optimization algorithms are applied – all resulting in output for operational use (this can be automated, as well).

Visual 

Our innovative grid analysis process can be seen in the graphic below. MCCS Grid Analysis Suite takes a step away from the conventional linear sequentially running processes. Our new modular approach allows multiple processes to run in parallel and transfer data, allowing both open- and closed-source calculation frameworks to run interchangeably and thereby being highly adaptable.

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