Research

Current

• Control of Heat Pumps for Energy Flexibility in Distribution Networks, May 2023 to Present
• Power and Energy Systems Research Group, SFU, BC, Canada
• Mitacs project titled “Evaluating Grid Modernization Pathways, Opportunities and Emissions Impacts” in partnership with the company Generac Power Systems Inc.
• Comprehensive Review on the Control of Heat Pumps for Energy Flexibility in Distribution Networks: paper
Decarbonization plans promote the transition to heat pumps, creating new opportunities for their energy flexibility in demand response programs, solar photovoltaic integration and optimization of distribution networks. My current research focuses on developing scheduling-based and real-time optimization methods to control heat pumps for enhanced energy flexibility in distribution networks.

Past Projects

• Assessment of the Impact of Electric Vehicles and Photovoltaic Systems on Distribution Networks, May 2023 to Aug. 2024
• IEEE CCECE 2024
The increasing integration of electric vehicles and solar photovoltaic systems may impose challenges for the operation of power distribution networks. This study assesses the impact of the integration of electric vehicles and solar photovoltaic generation on voltage issues, network loading and power losses in a low-voltage power distribution network.

• Definition of Representative Scenarios of Power Demand, Electric-vehicle Charging, and Photovoltaic Generation, May 2023 to June 2024
• IEEE EEEIC 2024
The definition of representative scenarios can be beneficial to the modelling of power distribution networks, reducing the computational burden of optimization models that require data from several power demand and photovoltaic generation profiles. We proposed a method that cluster net power demand profiles from households connected at the low-voltage distribution network. After a comprehensive study of different clustering algorithms, an agglomerative hierarchical clustering algorithm was employed to generate a dendrogram that facilitates the identification of cluster hierarchy. The results show that the agglomerative hierarchical clustering method merged clusters with lower imbalance while k-means and k-means++ clustering methods led to a high imbalance of time-series profiles within clusters.

• Assessment of Reliability in Expansion Planning of Distribution Networks, Aug. 2020 to Oct. 2022
• Power Systems Modeling and Analysis Group, Federal University of Rio Grande do Sul, Brazil
• R&D Project: Integrated Planning for Definition of Expansion Projects in Distribution Networks Considering Probabilistic Criteria. Funded by CEEE Equatorial power distribution utility in Brazil.
• Paper outlining the proposed framework
• Review paper
• Thesis
• Paper introducing the computational tool that includes the proposed framework as a module
Developed a framework for real-life applications by power distribution companies applied to the problem of power distribution systems expansion planning, considering reliability.