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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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Topics
Details

Details

  • Name

    João Tomé Saraiva
  • Cluster

    Power and Energy
  • Role

    Research Coordinator
  • Since

    15th July 1985
018
Publications

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.

2019

State-of-the-art of transmission expansion planning: A survey from restructuring to renewable and distributed electricity markets

Authors
Gomes, PV; Saraiva, JT;

Publication
International Journal of Electrical Power and Energy Systems

Abstract
Transmission Expansion Planning (TEP) problem aims at identifying when and where new equipment as transmission lines, cables and transformers should be inserted on the grid. The transmission upgrade capacity is motivated by several factors as meeting the increasing electricity demand, increasing the reliability of the system and providing non-discriminatory access to cheap generation for consumers. However, TEP problems have been changing over the years as the electrical system evolves. In this way, this paper provides a detailed historical analysis of the evolution of the TEP over the years and the prospects for this challenging task. Furthermore, this study presents an outline review of more than 140 recent articles about TEP problems, literature insights and identified gaps as a critical thinking in how new tools and approaches on TEP can contribute for the new era of renewable and distributed electricity markets. © 2019 Elsevier Ltd

2019

Impact of decision-making models in Transmission Expansion Planning considering large shares of renewable energy sources

Authors
Gomes, PV; Saraiva, JT; Carvalho, L; Dias, B; Oliveira, LW;

Publication
Electric Power Systems Research

Abstract

2019

On the use of causality inference in designing tariffs to implement more effective behavioral demand response programs

Authors
Ganesan, K; Saraiva, JT; Bessa, RJ;

Publication
Energies

Abstract
Providing a price tariff that matches the randomized behavior of residential consumers is one of the major barriers to demand response (DR) implementation. The current trend of DR products provided by aggregators or retailers are not consumer-specific, which poses additional barriers for the engagement of consumers in these programs. In order to address this issue, this paper describes a methodology based on causality inference between DR tariffs and observed residential electricity consumption to estimate consumers’ consumption elasticity. It determines the flexibility of each client under the considered DR program and identifies whether the tariffs offered by the DR program affect the consumers’ usual consumption or not. The aim of this approach is to aid aggregators and retailers to better tune DR offers to consumer needs and so to enlarge the response rate to their DR programs. We identify a set of critical clients who actively participate in DR events along with the most responsive and least responsive clients for the considered DR program. We find that the percentage of DR consumers who actively participate seem to be much less than expected by retailers, indicating that not all consumers’ elasticity is effectively utilized. © 2019 by the authors.

2019

A three-stage multi-year transmission expansion planning using heuristic, metaheuristic and decomposition techniques

Authors
De Oliveira, LE; Saraiva, JT; Gomes, PV; Freitas, FD;

Publication
2019 IEEE Milan PowerTech, PowerTech 2019

Abstract
Security and quality of supply continue to be major concern of power system operators. Thus, the expansion of transmission grids is certainly one of the major drivers to achieve this goal. In this scope, this paper presents a three-stage approach to solve the multi-year Transmission Expansion Planning (TEP) problem. This approach uses heuristic algorithms coupled with the Harmony Search (HS) metaheuristic and the Branch Bound (B&B) algorithm. This hybrid method (HS-B&B) aims at finding the optimal multi-stage investment plan avoiding load shedding over the planning horizon. In this work, the AC-Optimal Power Flow (AC-OPF) is used to model the network as a way to consider the real operation conditions of the system. The method was validated using the Garver and the IEEE RTS 24 bus systems. Results demonstrate the reduction of computational effort without compromising the quality of the TEP. © 2019 IEEE.

Supervised
thesis

2019

Renewable Integration in Balancing and Ancilliary Services Market in the EU Markets

Author
João Almeida de Sousa Costeira

Institution
UP-FEUP

2019

Estimativa da Valia Económica da PRE no Ano de 2017

Author
Manuel Maria de Sousa Dias Alves da Silva

Institution
UP-FEUP

2019

Residential Consumer Behavioural Analysis on the participation in Demand Response Strategies including distributed generation and electric vehicles

Author
Kamalanathan Ganesan

Institution
UP-FEUP

2019

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

Author
Rogério Rui Dias da Rocha

Institution
UP-FEUP

2019

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

Author
José Carlos Vieira Sousa

Institution
UP-FEUP