The increasing penetration of renewable energy sources, particularly wind and solar

power plants, has significantly intensified grid compliance requirements across modern

power systems. Consequently, developers and consultants are required to perform a

growing number of detailed electromagnetic transient (EMT) simulations to validate

compliance with grid codes. This work addresses the challenge of long simulation times

associated with PSCAD-based studies by exploring the application of parallel computing

techniques to optimise execution efficiency.

The methodology is based on distributing independent simulation cases across multiple

CPU cores, enabling concurrent execution. Using a PSCAD environment configured for

parallel processing, simulation batches were executed sequentially and then compared

against parallel runs utilising 8-core and 16-core configurations. The case study is based

on a grid compliance project completed for a solar plant in Finland, representing typical

European grid code requirements.

Results demonstrate a substantial reduction in total simulation time when parallel

computing is applied. While sequential execution leads to prolonged processing

durations, parallel executions allow multiple cases to be executed simultaneously,

significantly improving time. The performance gains scale with the number of available

cores.

The relevance of this work lies in its direct applicability to ongoing grid integration studies,

where project timelines are often constrained, and simulation workloads continue to

increase. By using computational resources more effectively, organisations can increase

productivity without compromising the quality of compliance studies.

The study concludes that parallel computing is a practical and scalable solution for

optimising PSCAD-based grid compliance studies. It enables faster project delivery and

better utilisation of hardware resources, supporting the growing demand for efficient

validation of renewable energy systems in increasingly complex power grids.