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Accelerating Your R&D with Open Software

May 5, 2026

Accelerating Your R&D with Open Software

A changing grid and the need for collaborative R&D

Power systems are undergoing a structural technical transition. Renewable generation, inverter-based resources, storage, electrification, data centers, distributed energy resources, flexible demand, and increasingly constrained networks are changing both the composition and the behaviour of the grid. These changes affect different parts of the system at different spatial and temporal scales, but their impacts are strongly interdependent.

The response from grid operators shows that these challenges are no longer treated as isolated technical issues. Across the sector, they are coordinating around applied power system R&D that can address shared technical problems. Initiatives such as CRESYM, the TSO Innovation Alliance, G-PST, and the GridWise Alliance reflect this shift, bringing together system operators, researchers, technology providers, and other stakeholders around challenges that no single actor can fully solve alone.

Conducting effective R&D for the modern grid

Several technical challenges introduced by the current transition, most notably the integration of variable inverter-based resources, require the industry to question even basic modelling assumptions. Established workflows now need closer examination of how devices are represented, how system behaviour is interpreted, and how results are validated. In many cases, the research task now includes both defining the methodology and running the study.

Effective R&D therefore requires a software environment that can evolve with the research question while preserving traceability. Engineers need to understand why a result was produced, which means being able to inspect the assumptions, numerical methods, modelling choices, and data structures behind it. When the method needs to change, the environment must allow innovation teams to modify algorithms, connect external methods, and automate non-standard workflows without losing the ability to reproduce and review the work.

That is what allows a method to be benchmarked against alternatives, challenged by other teams, and improved over time.

Commercial software and its limits

Commercial software remains an important part of power system engineering. It is established, familiar to current engineering teams, and already embedded in many technical processes. Where the workflow is mature and the objective is to apply a known method consistently, that is a major advantage.

The limitation appears when the work moves from applying a known method to developing a new one. Even when commercial tools provide scripting interfaces or user-defined models, the underlying architecture still sets the practical boundary of what can be changed. For R&D, that boundary matters. If the technical question requires a different representation, algorithm, or workflow, engineers may need to reshape the question around what the tool can support.

In that situation, the software environment starts to influence the research direction. Effort that should go into developing and validating the method is redirected toward finding acceptable approximations inside the available functionality. That can be useful for incremental work, but it becomes limiting when the innovation objective sits ahead of established commercial implementation.

Developing from scratch and its limits

The opposite approach is to build research code from scratch. This can provide flexibility, especially when a team needs to test an idea that is not yet supported by established tools. For early-stage research, that freedom can be valuable.

The limitation is that each project can end up recreating the same foundations before it reaches the actual research question. Core modelling infrastructure is rebuilt in parallel across teams. This creates disconnected prototypes that are difficult to maintain, review, or reuse once the original project ends. The result is technical fragmentation: useful ideas are developed, but they do not easily become shared engineering capability.

Open source as shared R&D infrastructure

Open-source power system software provides a third path. It creates a common technical foundation that research teams can build on instead of starting from zero or waiting for commercial implementation. Teams can extend the platform for a specific research question while keeping the underlying method accessible to others.

For this to be useful in power systems, open source also needs a certain level of maturity. It must provide enough core functionality to support serious studies, interoperate with standard power-system data formats, and have high ease of use. Otherwise, it risks becoming another isolated prototype.

At that level of maturity, open-source platforms allow R&D methods to be tested directly on realistic power-system cases. The same environment can support experimentation during development and structured case execution once the method is ready to be applied more broadly.

Ownership and transferability

Open source also changes what the organisation retains from an R&D effort. The result should include a method that the team can understand, maintain, and adapt for future studies. Because the implementation remains accessible, the technical knowledge developed during the project stays with the teams doing the work.

This is especially important for collaborative R&D. Power system research increasingly brings together organisations with different responsibilities and expertise. A shared open software base gives these teams a common environment for developing methods, reviewing technical choices, and transferring knowledge. In this context, platforms such as VeraGrid provide an open but practical foundation where new power system methods can be developed.

The objective is to ensure that applied R&D does not end as a disconnected prototype, but becomes part of the organisation's technical base. For this reason, mature open-source platforms have an important role to play in power system innovation: they allow new methods to move from investigation to repeated use without being rebuilt for each project.