The Intelligent Grid Planning Tool (iGPT) project will assess the feasibility of using assured artificial intelligence to support transmission network planning within DIgSILENT PowerFactory. As the energy transition accelerates, planners face increasing volumes of reinforcement, generation connection and system development studies that are labour-intensive and dependent on specialist expertise.

The project will develop and evaluate a proof-of-concept platform combining conversational AI, engineering verification and auditable decision support. It will assess whether AI can reduce study times, improve consistency, strengthen knowledge retention and increase productivity while maintaining governance, transparency and human oversight.

The project will also generate learning on AI governance, assurance, auditability, cybersecurity and the use of large language models in regulated transmission planning, with findings shared across network licensees.

Benefits

NGET currently relies on specialist transmission planning engineers, established engineering procedures, guidance documentation and manual PowerFactory-based workflows to undertake network planning studies. A significant proportion of engineering effort is spent on routine activities such as study preparation, model configuration, execution, validation, reporting and documentation. The project is expected to deliver benefits through improved efficiency, consistency and scalability of transmission planning activities. Potential benefits include reducing the effort associated with repetitive planning tasks, improving the consistency and repeatability of study execution, enhancing traceability of engineering activities and supporting more effective knowledge transfer across engineering teams. The project may also reduce dependency on individual expertise for routine workflows, improve accessibility of planning knowledge and increase the capacity of engineering teams to respond to growing study volumes. Additional benefits include improved reproducibility of studies, reduced rework associated with workflow inconsistencies and stronger engineering governance through more standardised planning processes. As this is an innovation project, a key objective is to validate and quantify these benefits in a controlled environment and establish the evidence base required for future deployment decisions.