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About

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.

Interest
Topics
Details

Details

  • Name

    João Tomé Saraiva
  • Role

    Research Coordinator
  • Since

    15th July 1985
042
Publications

2023

Improved hybridization of CEVESA MIBEL market model based on real market data

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

Publication
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
This paper presents a new hybridization approach to improve CEVESA, a multi-zonal hydro-thermal equilibrium model for the joint dispatch of energy and secondary reserve capacity for the Iberian Electricity Market (MIBEL). Like similar fundamental models, CEVESA provides market prices that typically show an average systematic bias compared to real market prices. This is because these models do not always capture the true variable production costs of the generation units or the additional markups that generation companies may include in their pricing strategy. Based on real market outcomes, this paper proposes a new methodology built on a previous hybridization approach that estimated a constant monthly markup per thermal offering unit [1]. This new methodology is based on a functional estimation of the offering unit cost (or bidding price), using as input the initial CEVESA production costs based on the fuel and emissions commodities' prices, correcting the power plants' markup.

2023

Simulating a real time Walrasian local electricity market design: assessing auctioneer algorithm and price behavior

Authors
Mello, J; Retorta, F; Silva, R; Villar, J; Saraiva, JT;

Publication
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
In Walrasian markets, an auctioneer proposes a price to the market participants, who react by revealing the quantities they are willing to buy or sell at this price. The auctioneer then proposes new prices to improve the demand and supply match until the equilibrium is reached. This market, common for stock exchanges, has also been proposed for electricity markets like power electricity exchanges, where iterations among auctioneer and market participants take place before the interval settlement period (ISP) until supply and demand match and a stable price is reached. We propose a Walrasian design for local electricity markets where the iterations between auctioneer and market participants happen in real time, so previous imbalances are used to correct the proposed price for the next ISP. The designs are simulated to test convergence and their capability of achieving efficient dynamic prices.

2023

Decentralized and Centralized Storage Architectures in Local Energy Markets (LEM) and their interaction with the Wholesale Market (WSM)

Authors
dos Santos, AF; Saraiva, JT;

Publication
2023 IEEE BELGRADE POWERTECH

Abstract
Energy storage systems, integrated in Renewable Energy Communities (REC), are enabling the development of operation strategies together with Photovoltaic (PV) systems. Additionally, Local Energy Markets (LEM) are emerging mechanisms to enable local energy trading in RECs, the integration of storage systems can increase the community energy savings and profits. In this context, a market environment was modelled as a Markov Decision Process (MDP). In this scope, an Agent Based Model (ABM) using the Q-Learning mechanism was used to implement and to simulate a LEM and its interaction with the Wholesale Market (WSM), also considering an architecture with storage systems. The developed model was tested considering real data regarding energy consumption and PV generation. The paper describes and discusses the obtained market strategy and the profits that can be obtained with this approach.

2023

Simulation of the Operation of Renewable Energy Communities Considering Storage Units and Different Levels of Access Tariffs Exemptions

Authors
dos Santos, AF; Saraiva, JT;

Publication
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
Power systems are evolving very rapidly namely in what concerns the technologies used to generate electricity, the diversification of commercial relationships involving different agents and more specifically the empowerment of consumers. In this scope, several countries passed new legislation to induce the installation of Renewable Energy Communities, RECs, to induce new investments at a local level, to empower end consumers and to increase their self-sufficiency. However, the way Local Energy Markets, LEMs, will be integrated into Wholesale Markets, WSM, is not yet fully established. To this end, this paper proposes a design and an optimization model to increase the mentioned self-sufficiency level, to better manage the energy produced locally, also admitting the installation of battery storage units, and to profit as much as possible of them. LEM interaction with WSM, is based on an Agent Based Model architecture equipped with a Q-learning strategy. An economic assessment is also included, in order to get insights if some level of exemption, for instance associated with some components of the Access Tariffs, have to be considered in order to induce the massification of RECs.

2023

Estimate of the Impact of Special Regime Generation in the Electricity Generation Cost in Portugal

Authors
Saraiva, JT; Vasconcelos, M;

Publication
2023 19TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM

Abstract
This paper describes the work developed to estimate the impact of the Special Regime Generation, SRG, in the generation cost in Portugal. Till the beginning of 2021 the values of the feed in tariffs paid to SRG were much larger than the market price paid to Normal Regime Generation, NRG, and this gap was often considered as a burden subsidized by consumers. In order to bring rational arguments to this discussion, several MSc Thesis were developed in recent years at the Engineering Faculty of Porto University to estimate the global generation cost in the country considering the current feed in regime and also admitting that generation paid feed in tariffs was reduced. This implied the calculation of the new market price if SRG was reduced and conversely NRG was increased. The results of the simulations developed for 2017, 2018, 2019 and 2020 indicate that the impact of SRG very much depends on the market price along the year. If the market price is reduced (for instance in good hydrological years as 2020) the elimination of SRG reduces the generation cost. Conversely, if the market price is high, the elimination of SRG tends to increase the generation cost.

Supervised
thesis

2022

Cancer diagnosis in digital pathology: learning from label scarcity

Author
Sara Isabel Pires de Oliveira

Institution
UP-FEUP

2022

AI for the next-generation manufacturing: applications in scheduling and process control

Author
Nuno André Azevedo Marques

Institution
UP-FEUP

2022

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

Author
André Rodrigues de Oliveira

Institution
UP-FEUP

2022

Local Electricity Market design:P2P Trade, Pool Based and Real Time Walrasian Auctions for energy and flexibility services provision

Author
João Moreira Schneider de Mello

Institution
UP-FEUP

2022

Prototype of a mandibular advancement device with microsensors for sleep apnea syndrome and snoring

Author
Helena Patrícia Campos da Silva

Institution
UP-FEUP