Dr José Barreira Iria

PhD in Sustainable Energy Systems | MSc in Electrical and Computer Engineering
Research Fellow
College of Engineering & Computer Science

Areas of expertise

  • Power And Energy Systems Engineering (Excl. Renewable Power) 090607
  • Renewable Power And Energy Systems Engineering (Excl. Solar Cells) 090608
  • Optimisation 010303
  • Operations Research 010206

Research interests

  • Electricity markets
  • Optimization modeling
  • Demand response
  • Energy storage 
  • Electric vehicles
  • Energy forecasting
  • Uncertainty modeling in the context of power systems 
  • Distribution network planning and operation

Biography

Dr José Iria is a highly motivated academic and research engineer with extensive experience and knowledge in power and energy systems modeling, optimization, and control. In these areas, he has actively participated in more than 20 European, Australian and U.S. R&D projects, and consultancy activities for distribution and transmission system operators, utilities, and smart grid companies. He is the author of 25 peer-reviewed papers in top international journals (9) and conferences (16). He was also co-responsible for raising more than 10 M€ in R&D funds in the areas of energy and power systems.

He obtained a PhD degree in Sustainable Energy Systems, under the MIT|Portugal Program, from the University of Porto in 2019, and an MSc degree in Electrical and Computer Engineering from the same university in 2011. His PhD work was funded by a fellowship awarded by the Portuguese Foundation for Science and Technology to the best 0.8% of the applicants. In 2020, his PhD thesis was recognized by APREN (Portuguese Renewable Energy Association) as one of the best dissertations in the area of renewable energy.

Currently, he is a research fellow at the Australian National University. He held research positions at INESC TEC (Portugal) between 2012 and 2019 and Berkeley Lab (U.S.) between 2017 and 2018. Today, he still holds an affiliate research position at INESC TEC.

Specialties: power and energy systems; electricity markets; distributed energy resources; renewable energy; modeling; optimization; control; decision-making.

 

 

Researcher's projects

Title: Optimal Distributed Energy Resources Scheduling for Frequency Stability 

Objective: The project will develop and test software to coordinate fleets of distributed energy resources on electricity networks, enabling them to provide frequency reserve services.

Funding agency: Australian Renewable Energy Agency (ARENA)

Link: https://arena.gov.au/projects/optimal-der-scheduling-for-frequency-stability-study/

Published papers: 

  1. J. Iria, P. Scott, A. Attarha, Network-constrained bidding optimization strategy for aggregators of prosumers, Energy. 207 (2020) 118266. doi:10.1016/j.energy.2020.118266.

Available student projects

Title: Optimization of distributed energy resources


Motivation and context:

Distributed energy resources (DER) are changing the way how electricity is generated and managed. Traditionally, electricity has been generated by big power plants. Today, it is also starting to come from DER located in millions of homes and businesses. Common examples of DER include photovoltaic systems, battery energy storage systems, electric vehicles, and home energy management technologies.

The demand for DER in Australia is expected to grow in the next years. Energy Networks Australia estimates that by 2050, DER may contribute up to 45% of Australia’s electricity generation capacity. Such high numbers of DER may significantly impact the operation of the Australian power system. For instance, the DER operation may generate voltage and congestion problems in the distribution networks, if not well managed.

Objective:

The objective of this project is to develop computational tools to plan, upkeep, or operate a power system characterized by a high integration of DER. The computational tools may address technical, economic, or environmental aspects, depending on the interest and motivation of the student. Examples of computational tools are:

  • Bidding optimization models for aggregators of DER;
  • Portfolio optimization models for aggregators of DER;
  • Distributed optimization approaches for power system problems;
  • Planning optimization models for distribution networks.

Requirements:

  • Solid understanding of convex and non-convex optimization.
  • Knowledge of optimization modeling.
  • Programming skills, such as python or Julia.

Outputs:

This project should produce an optimization tool to support energy stakeholders to plan, upkeep, or operate the future power system. The work will be very interesting to many forums, so a productive project may well lead to a publication.

ANU students can contact me via email for more details. 

 

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Updated:  06 December 2020 / Responsible Officer:  Director (Research Services Division) / Page Contact:  Researchers