Smart Meter penetration across the globe is ever increasing, for example in New Zealand we have close to 72% already. There are several implementations and publications around utilizing Smart meter data for various applications. Alongside, there is also a pick-up of penetration of distributed energy technologies like PV and Storage batteries, which makes the distribution networks bidirectional, influencing changing load profiles named as "California duck curves" and "Indian Giraffe curves" etc.
This project will comprehensively assess and classify all possible applications/implementation potential for Smart Meter Data for Electricity Distribution Network utilities and/or retailers. These will include both real-time, online and time-insensitive applications spanning monitoring, operation, maintenance and trading applications.
For handling the large scale of data, big-data analytics will need to be assessed and for smart grid and self-learning algorithm development all possible Artificial Neural Network (ANN) techniques will need to be investigated.
The Power systems Group (PSG) have close working relationship with the various retailers and distribution utilities of New Zealand. Thus, once the project group identifies a few use-cases, if needed getting data and industry engagement will not be an issue. The PSG PhD researchers working in Smart Grid analytics will be closely working with this project group.
Undergraduate
1) Prototype a couple of new applications using high-penetration Smart Meter data for distribution/retailer operators.
2) Showcase proof-of-concept implementation in the Power systems lab at Newmarket campus.
One of the project group members need to register in Power system elective specialization course track(ELECTENG 309, ELECTENG 731, ELECTENG 703)
Lab allocations have not been finalised