What is automated bulk analysis?

There are several steps a Synergi Electric user may have to carry out on a new Synergi Electric model prior to doing any actual engineering work. For example, the model may require Quality Assurance checks, some cleanup tasks, and Load Allocation before running Load Flow or any other analysis. All of these steps can be automated, as well as standard analyses like Load Flow, Fault Analysis and Hosting Capacity Analysis, and DNV can help to design, develop, and implement this as part of the model build process.

How can DNV help with automated bulk analysis?

There are several options for automating analysis in Synergi Electric, from built-in tools like EA Automation to external tools, such as the Python interface. These can be adapted or combined to produce customized analysis process which are capable of running complex analyses. The analysis process can be comprised of multiple steps, with flexibility in the reporting schema and formats so that each step in the process – for example, QA checks with reports followed by Load Allocation where a new model is saved. All of the results can be formatted to suit the needs of the user.

DNV’s process starts with a design stage, where the requirements and requests of the stakeholders are discussed, agreed, and documented. DNV then develops customized scripting which may include several coding languages (e.g., Python, SQL, Batch files). The result is a tool that can execute all of the bulk distribution system analysis and reporting at the push of a button, or from a scheduled task.

Key benefits of Synergi Electric's Automated Bulk Analysis

• Allows system-wide analysis to be updated as often as the model data (or load data) is updated.
• Reduces resource requirements of planning engineers to perform QA checks.
• Can facilitate easy communication of data issues between distribution planners and GIS administrators.
• Ensures automated tasks are completed in a standardized manner.
• Can provide a better starting point for engineers reviewing models or running planning studies.