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About

J. T. Saraiva was born in Porto, Portugal, in 1962 and got his MSc, PhD, and Agregado degrees in Electrical and Computer Engineering from FEUP in 1987, 1993 and 2002, where he is currently Professor. In 1985 he joined INESC Porto where he is head researcher and collaborated in several EU financed projects, in national funded projects and in several consultancy contracts with the Portuguese Electricity Regulatory Agency, with EDP Distribuição, EDP Produção, REN, Empresa de Electricidade da Madeira, Empresa de Electricidade dos Açores and with the Greek and the Brasilean Transmission System Operators. Along his Academic career he supervized more than 50 MSc Thesis and 10 PhD Thesis, co authored 3 books, more than 30 papers in international journals and more than 120 papers in International Conferences.

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Details

Details

  • Name

    João Tomé Saraiva
  • Cluster

    Power and Energy
  • Role

    Research Coordinator
  • Since

    15th July 1985
023
Publications

2021

A two-stage constructive heuristic algorithm to handle integer investment variables in transmission network expansion planning

Authors
Oliveira, ED; Junior, ICS; de Oliveira, LW; de Mendonca, IM; Vilaca, P; Saraiva, JT;

Publication
ELECTRIC POWER SYSTEMS RESEARCH

Abstract
Due to the complexity and great relevance of the transmission network expansion planning (TNEP) for electrical systems, this topic remains on the focus of the academic and industry communities. Therefore, this paper proposes a new approach to deal efficiently with the basic formulation of this problem, combining low computational effort and good quality of the obtained solutions. In this approach four factors contribute to solve TNEP problem more efficiently: (i) the investment decisions are selected using a new Constructive Heuristic Algorithm (CHA); (ii) the proposed CHA includes two stages, using the relaxation of the decision integers variables through the hyperbolic tangent function and the setting of its function's slope; (iii) the performance index that was adopted was modified regarding what was reported in the literature; (iv) the use of the primal-dual interior point optimization technique allows the representation of the nonlinearities in the problem: transmission power losses and the hyperbolic tangent function (investment decision). The quality and effectiveness of the proposed algorithm is verified using two real power systems, where the proposed CHA is able to lead to better quality solutions than the ones reported in the literature.

2021

Electricity Cost of Green Hydrogen Generation in the Iberian Electricity Market

Authors
de Oliveira, AR; Collado, JV; Saraiva, JT; Domenech, S; Campos, FA;

Publication
2021 IEEE Madrid PowerTech

Abstract

2021

Estimation of the Global Amount of Mandatory Investments for Distribution Network Expansion Planning

Authors
MacEdo P.M.; Fidalgo J.N.; Saraiva J.T.;

Publication
2021 IEEE Madrid PowerTech

Abstract

2021

Designing modern heuristic algorithms to solve the Transmission Expansion Planning problem

Authors
Vilaca P.; Colmenar J.M.; Duarte A.; Saraiva J.T.;

Publication
2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings

Abstract
Transmission Expansion Planning (TEP) aims at identifying a list of new assets to be installed on the transmission grid to meet the long-term forecasted demand while ensuring a safe supply over the entire planning horizon. As TEP is a Mixed Integer Non-Linear Problem (MINLP) with a huge search space, in the last years several modern heuristic algorithms were proposed to deal with its challenging characteristics. In this way, this paper describes and evaluates the impact and implementation of four operators that can be easily incorporated in any evolutionary algorithm, namely: Neighborhood Search for Local Improvement (NSLI), Diversity Control (DC), Elitist Reproduction (ER) and Boundary Local Search (BLS). The impact of these operators is assessed and discussed over a hundred simulations using a traditional Genetic Algorithm (GA) and a well-known test system, the RTS 24-bus. Regarding the results, the NSLI and the BLS operator considerably improved the GA performance in solving the TEP problem regarding both the final value of the objective function and the diversity of solutions.

2020

A two-stage strategy for security-constrained AC dynamic transmission expansion planning

Authors
Gomes, PV; Saraiva, JT;

Publication
Electric Power Systems Research

Abstract
This paper presents a new and promising strategy organized in two stages to solve the dynamic multiyear transmission expansion planning, TEP, problem. Specifically, the first stage is related to the reduction of the search space size and it is conducted by a novel constructive heuristic algorithm (CHA). The second one is responsible for the refinement of the optimal solution plan and it uses a novel evolutionary algorithm based on the best features of particle swarm optimization (PSO) and genetic algorithm (GA). The planning problem is modelled as a dynamic and multiyear approach to ensure that it keeps a holistic view over the entire planning horizon and it aims at minimizing the total system costs comprising the investment and operation costs. Additionally, the N-1 contingency criterion is also considered in the problem. The developed approach was tested using the IEEE 118-Bus test system and the obtained results demonstrate its advantages in terms of efficiency and required computational time. Furthermore, the results demonstrated that the novel strategy can enable the utilization of the AC optimal power flow (OPF) in a faster and reliable way when compared to the standard and widespread DC-OPF model. © 2019 Elsevier B.V.

Supervised
thesis

2021

Multi-Objective Long-Term Transmission Expansion Planning

Author
Luiz Eduardo de Oliveira

Institution
UP-FEUP

2021

Economic and Regulatory Schemes to Maximize the Social Benefit of Energy Communities

Author
Rogério Rui Dias da Rocha

Institution
UP-FEUP

2021

Previsão de preços de mercado baseada em Deep Learning

Author
Ana Rita Martins Cruz e Silva

Institution
UP-FEUP

2021

Multi-zonal energy and reserve equilibrium market model with interconnections allocation

Author
André Rodrigues de Oliveira

Institution
UP-FEUP

2021

Simulation of Hydro Power Plants in Electricity Markets Using an Agent-Based Model

Author
José Carlos Vieira Sousa

Institution
UP-FEUP