Calculating the impact of Australian network operators' instructions on a PV portfolio

The sheer complexity involved in assessing the impact of the Australian Energy Market Operator’s (AEMO) power limitation setpoints on production makes it very difficult to ensure accuracy and utilise labour efficiently. These limitations also impede the ability of asset managers to work with site operators on understanding the practical effects of the setpoints and taking action to mitigate losses.

The client in this case owned a portfolio of five PV assets in Australia with an average capacity of 100MW and needed to precisely estimate the daily production losses caused by AEMO setpoints for informed decision-making on the part of the asset management team, working with the on-site operators. Manual data processing was proving frustratingly inadequate to the task.

Quintas Analytics’ automated solution streamlined the work of the asset management team and improved its communications. The work was completed faster and more efficiently, improving the accuracy of the availability assessment, reducing manual effort, and cutting the risk of error in calculations.

THE SOLUTION

Quintas Analytics developed an automated solution to address the above challenges.

1.?????? Data Integration: the new system automatically collected and integrated the separate data from AEMO’s power limitation setpoints and the SCADA.

2.?????? Production Loss Calculation: The solution estimated daily production losses caused by the AEMO setpoints, based on the power limitations and irradiance for each plant.

3.?????? Availability Assessment: Algorithms calculated the assets’ daily technical availability, excluding the effect of AEMO setpoints, to enable communication with on-site operators and better focus on the real operational issues of the assets.

THE BENEFITS

1.?????? Reduced Workload: The daily chore of manually matching SCADA production data with setpoints was eliminated, freeing up working time.

2.?????? Improved Precision: Due to the automated process, the risk of human error throughout was substantially reduced.

3.?????? Up-to-Date Information: The daily assessment allowed for faster and more accurate decision making, improving communications with on-site operators.

4.?????? Optimised Operations: A more detailed understanding of production losses improved operational efficiency and planning.

Process automation, data integration and automated calculations proved to be essential tools for effective management and improved communications with the operator, setting a valuable example for similar projects in the Australian solar PV sector.