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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
  • Role

    Area Manager
  • Since

    01st April 2008
032
Publications

2023

Real-time management of distributed multi-energy resources in multi-energy networks

Authors
Coelho, A; Iria, J; Soares, F; Lopes, JP;

Publication
SUSTAINABLE ENERGY GRIDS & NETWORKS

Abstract
The replacement of fossil fuel power plants by variable renewable energy sources is reducing the flexibility of the energy system, which puts at risk its security. Exploiting the flexibility of distributed multi-energy resources through aggregators presents a solution for this problem. In this context, this paper presents a new hierarchical model predictive control framework to assist multi-energy aggregators in the network-secure delivery of multi-energy services traded in electricity, natural gas, green hydrogen, and carbon markets. This work builds upon and complements a previous work from the same authors related to bidding strategies for day-ahead markets - it closes the cycle of aggregators' participation in multi-energy markets, i.e., day-ahead bidding and real-time activation of flexibility services. This new model predictive control framework uses the alternating direction method of multipliers on a rolling horizon to negotiate the network-secure delivery of multi-energy services between aggregators and distribution system operators of electricity, gas, and heat networks. We used the new model predictive control framework to conduct two studies. In the first study, we found that considering multi-energy network constraints at both day-ahead and real-time optimization stages produces the most cost-effective and reliable solution to aggregators, outperforming state-of-the-art approaches in terms of cost and network security. In the second study, we found that the adoption of a green hydrogen policy by multi-energy aggregators can reduce their consumption of natural gas and respective CO2 emissions significantly if carbon and green hydrogen prices are competitive.& COPY; 2023 Elsevier Ltd. All rights reserved.

2023

TSO-DSO Coordinated Operational Planning in the Presence of Shared Resources

Authors
Simões, M; Madureira, G; Soares, F; Lopes, JP;

Publication
2023 IEEE Belgrade PowerTech, PowerTech 2023

Abstract
Electric power systems are currently experiencing a profound change, as increasing amounts of Renewable Energy Sources (RESs) displace conventional forms of generation. This development has gone hand-in-hand with an increasing share of distributed power generation being connected directly to the Distribution Network (DN), and the widespread of other types of Distributed Energy Resources (DERs), such as Energy Storage Sytems (ESSs), Electric Vehicles (EVs), and active (flexible) consumers. As these trends are expected to continue, this will require a profound revision of the way Transmission System Operators (TSOs) and Distribution System Operators (DSOs) interact with each other to fully benefit from the growing flexibility that is available at the DN level. In this work we propose a new tool for the coordinated operational planning of transmission and distribution systems, considering the existence of shared resources that can be simultaneously used by TSO and DSOs for the optimal operation of their networks. The tool uses advanced distributed optimization techniques, namely the Alternating Direction Method of Multipliers (ADMM) in order to maintain data privacy of the several agents involved in the optimization problem, and keep the tractability of the problem. The proposed tool is applied to modified IEEE test systems, and the results obtained highlight the benefits of the proposed coordination mechanism to solve problems occurring simultaneously at the transmission and DN-levels. © 2023 IEEE.

2023

TSO-DSO Coordinated Operational Planning in the Presence of Shared Resources

Authors
Simoes, M; Madureira, AG; Soares, F; Lopes, JP;

Publication
2023 IEEE BELGRADE POWERTECH

Abstract
Electric power systems are currently experiencing a profound change, as increasing amounts of Renewable Energy Sources (RESs) displace conventional forms of generation. This development has gone hand-in-hand with an increasing share of distributed power generation being connected directly to the Distribution Network (DN), and the widespread of other types of Distributed Energy Resources (DERs), such as Energy Storage Sytems (ESSs), Electric Vehicles (EVs), and active (flexible) consumers. As these trends are expected to continue, this will require a profound revision of the way Transmission System Operators (TSOs) and Distribution System Operators (DSOs) interact with each other to fully benefit from the growing flexibility that is available at the DN level. In this work we propose a new tool for the coordinated operational planning of transmission and distribution systems, considering the existence of shared resources that can be simultaneously used by TSO and DSOs for the optimal operation of their networks. The tool uses advanced distributed optimization techniques, namely the Alternating Direction Method of Multipliers (ADMM) in order to maintain data privacy of the several agents involved in the optimization problem, and keep the tractability of the problem. The proposed tool is applied to modified IEEE test systems, and the results obtained highlight the benefits of the proposed coordination mechanism to solve problems occurring simultaneously at the transmission and DN-levels.

2023

Evaluation of the economic, technical, and environmental impacts of multi-energy system frameworks in distribution networks

Authors
Coelho, A; Soares, F; Iria, J; Lopes, JP;

Publication
2023 IEEE BELGRADE POWERTECH

Abstract
This paper presents a general comparison between network-secure and network-free optimization frameworks to manage flexible multi-energy resources. Both frameworks were implemented in a test case that includes electricity, gas, and heat distribution networks. Several potential scenarios for the decarbonization of the multi-energy system were simulated. The economic, technical, and environmental impacts were compiled. The network-secure framework is highly recommended to avoid service disruptions due to network violations, but its implementation comes with a price - overall operational costs increase, sometimes substantially.

2023

An energy-as-a-service business model for aggregators of prosumers

Authors
Iria, J; Soares, F;

Publication
APPLIED ENERGY

Abstract
Traditional retail business models price electricity using volumetric tariffs, which charge customers for the unit of energy consumed. These tariffs were designed for passive consumers with low flexibility. In this paper, we argue that these volumetric tariffs are unsuitable for prosumers with high flexibility since they are unable to adequately value the flexibility of their distributed energy resources in multiple electricity markets. This reduces the interest of prosumers participating in aggregators' business models. To address this issue, we propose a new business model for aggregators of prosumers, based on the concept of energy-as-a-service. In this business model, prosumers pay a monthly fee for aggregators to represent and optimize them in multiple wholesale electricity markets, including in energy and ancillary service markets. The monthly fee is computed by a new technoeconomic simulation framework proposed in this paper, which can also be used to estimate the profitability of the new business model from the perspectives of both the aggregator and prosumers. Our experiments on a portfolio of real prosumers from Australia show that the new business model maximizes the economic benefits of both the aggregator and prosumers by increasing the average profit of the aggregator by 438% and reducing the average electricity cost of prosumers from $583/year to $0 when compared to two of the most common retail business models available in the Australian market. In other words, the economic benefit for prosumers is free electricity. In addition to this benefit, the new business model also provides simplicity and predictability to prosumers, as they are offered a guaranteed outcome before providing the services.

Supervised
thesis

2022

Formação ética em engenharia com recurso a metodologias ativas: caso de estudo em Engenharia Eletrotécnica

Author
Maria de Fátima Coelho Monteiro

Institution
UP-FEUP

2022

Operation Strategies for Energy Communities and Evaluation of their Impacts on Power Systems Using an ABM Model

Author
António José Valente Ferreira dos Santos

Institution
UP-FEUP

2022

Impacts of energy sector - Decarbonization on electrical power systems

Author
Bruna Daniela Costa Tavares

Institution
UP-FEUP

2022

Applied Machine Learning Fairness in Business to Consumer Services Industry

Author
Nuno Filipe Loureiro Paiva

Institution
UP-FEUP

2021

Impacts of energy sector - Decarbonization on electrical power systems

Author
Bruna Daniela Costa Tavares

Institution
UP-FEUP