Massie Mahmoodi
Contacts
I am a Postdoctoral Research Fellow at The Australian National University (ANU), College of Engineering, Computing and Cybernetics, specialising in optimising distributed energy resources (DER) participation in energy and services markets. I am involved with Project Edith, a collaborative demonstration project between Battery Storage and Grid Integration Program (BSGIP) at ANU, Ausgrid, Reposit and ZepBen. My roles in this project include:
1) Develop innovative algorithms to enable DER to actively participate in energy and services markets. Key responsibilities include creating models for optimal power flow, designing behind-the-meter customers' energy management systems, analysing customer price elasticity, and formulating pricing strategies to optimise DER participation.
2) Implement and deploy the developed algorithms by building Python packages. Conduct comprehensive testing and verification to ensure accurate and reliable functionality.
3) Engage in regular meetings with project stakeholders to provide progress updates, discuss research findings, and gather feedback.
I am also involved in the Neighbourhood Battery Project, where we assess the impact of neighbourhood batteries on network hosting capacity and households' PV curtailments in Yackandandah, Victoria. My role in this project is to model neighbourhood batteries, households equipped with PV panels and different settings for inverters (e.g., volt-var, volt-watt, etc) in low-voltage distribution systems.
I have a PhD in Engineering and Computer Science from ANU. During my PhD, I have developed innovative data-driven optimisation-based models and methodologies to address the technical challenges posed by increasing DER in electricity distribution systems. Specifically, my research focused on assessing and maximising the DER capacity while mitigating issues such as over-voltage, line/transformer overloading, and data uncertainty, ultimately contributing to the effective integration of renewable energy sources and the decarbonisation of the electricity sector.
I have a proven track record of implementing and deploying Python packages and collaborating with stakeholders to deliver research outcomes. I am passionate about data-driven power systems planning, decision-making under uncertainty, and renewable energy integration. I possess strong programming skills in Python, and SQL, along with expertise in tools such as Pandas, NumPy, Scikit-learn, and Docker. I hold patents and have received academic scholarships and awards, further reflecting my dedication to excellence.
Groups
- Student, Energy storage and recovery
- Student, Smart grid