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About

About

Filipe Joel Soares received the Physics degree (five-year course) from the Faculty of Sciences and an Electrical Engineering (Renewable Energies) Postgrad from Porto University, Porto, Portugal, in 2004 and 2007, respectively. He also received the Ph.D. degree in Sustainable Energy Systems, in the MIT|Portugal Program, from Porto University, Porto, Portugal, in 2012.

Currently he is a Senior Researcher in the Centre for Power and Energy Systems of INESC Porto and Assistant Professor in the Lusophone University of Porto. His research activity is directed towards the integration of distributed energy resources (i.e. controllable loads, electric vehicles, renewable energy sources and stationary storage) in distribution grids, as well as to the development of advanced algorithms and functionalities for their management and participation in electricity markets.

He is author of more than 50 papers in international journals and conferences.

Interest
Topics
Details

Details

  • Name

    Filipe Joel Soares
  • Cluster

    Power and Energy
  • Role

    Area Manager
  • Since

    01st April 2008
011
Publications

2019

Optimal bidding strategy for an aggregator of prosumers in energy and secondary reserve markets

Authors
Iria, J; Soares, F; Matos, M;

Publication
Applied Energy

Abstract

2019

A cluster-based optimization approach to support the participation of an aggregator of a larger number of prosumers in the day-ahead energy market

Authors
Iria, J; Soares, F;

Publication
Electric Power Systems Research

Abstract

2019

Distribution network planning considering technology diffusion dynamics and spatial net-load behavior

Authors
Heymann, F; Silva, J; Miranda, V; Melo, J; Soares, FJ; Padilha Feltrin, A;

Publication
International Journal of Electrical Power and Energy Systems

Abstract
This paper presents a data-driven spatial net-load forecasting model that is applied to the distribution network expansion problem. The model uses population census data with Information Theory-based Feature Selection to predict spatial adoption patterns of residential electric vehicle chargers and photovoltaic modules. Results are high-resolution maps (0.02 km2) that allow distribution network planners to forecast asymmetric changes in load patterns and assess resulting impacts on installed HV/MV substation transformers in distribution systems. A risk analysis routine identifies the investment that minimizes the maximum regret function for a 15-year planning horizon. One of the outcomes from this study shows that traditional approaches to allocate distributed energy resources in distribution networks underestimate the impact of adopting EV and PV on the grid. The comparison of different allocation methods with the presented diffusion model suggests that using conventional approaches might result in strong underinvestment in capacity expansion during early uptake and overinvestment in later diffusion stages. © 2018

2018

Trading Small Prosumers Flexibility in the Energy and Tertiary Reserve Markets

Authors
Iria, JP; Soares, FJ; Matos, MA;

Publication
IEEE Transactions on Smart Grid

Abstract

2018

Optimal supply and demand bidding strategy for an aggregator of small prosumers

Authors
Iria, J; Soares, F; Matos, M;

Publication
Applied Energy

Abstract
This paper addresses the problem faced by an aggregator of small prosumers, when participating in the energy market. The aggregator exploits the flexibility of prosumers' appliances, in order to reduce its market net costs. Two optimization procedures are proposed. A two-stage stochastic optimization model to support the aggregator in the definition of demand and supply bids. The aim is to minimize the net cost of the aggregator buying and selling energy at day-ahead and real-time market stages. Scenario-based stochastic programing is used to deal with the uncertainty of electricity demand, end-users' behavior, outdoor temperature and renewable generation. The second optimization is a model predictive control method to set the operation of flexible loads in real-time. A case study of 1000. small prosumers from the Iberian market is used to compare four day-ahead bidding strategies and two real-time control strategies, as well as the performance of combined day-ahead and real-time strategies. The numerical results show that the proposed strategies allow the aggregator to reduce the net cost by 14% compared to a benchmark typically used by retailers (inflexible strategy). © 2017 Elsevier Ltd.

Supervised
thesis

2016

Synergies between Electric Vehicles and Dispersed Renewable generation in a GIS Environment under Information Theory Criteria

Author
Fabian Heymann

Institution
UP-FEUP

2015

Enabling Active Demanding Response in Smart Grids

Author
José Pedro Barreira iria

Institution
UP-FEUP