Masoume Mahmoodi

Date: Wednesday 1 June, 2022

Time: 10am, followed by morning tea at 11am.

Forum: PhD presentation

Speaker: Masoume Mahmoodi, PhD candidate, Australian National University

Location: Room S316, Battery Storage and Grid Integration Offices, Level 3, CSIT Building, 108 North Road, ANU campus and Zoom.

Contact: Sarah Wilson, Communications Manager, Battery Storage and Grid Integration Program

To meet the global decarbonisation targets, our electricity system is undergoing a massive transition from fossil fuel-based centralised generation to renewable-based distributed generation (DG). Although technological advancements and governments support policies in favour of achieving such ambitious targets, in practice however, it is challenging to integrate a significant amount of DG units into the electricity system without violating its physical limits. To this end, during my PhD program, I studied DG capacity assessment of electricity distribution systems.

In my talk, I discuss 1) effectiveness of the response from available control devices in improving networks’ DG capacity; 2) different techniques that
we employed for decision making under uncertainty. These methods are useful to account for uncertainties around solar and demand which in turn lead to a
more accurate DG installation capacity for the distribution networks; and 3) exploring two different distributed techniques, one based on alternating direction method of multipliers (ADMM) and another based on dynamic operating envelopes (DOEs) to improve the consumers’ privacy requirement, freedom in
decision making, and computation performance of the problem.

About the speaker

Masoume Mahmoodi received her BSc and MSc degrees in electrical engineering from the Amirkabir University of Technology, Tehran, Iran. She is currently a PhD candidate at the College of Engineering and Computer Science, The Australian National University. Her research interests include power systems modelling and optimisation, decision-making under uncertainty, and data-driven operation/planning of power systems.