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About

About

Tiago Pinto got his PhD in 2016 from the Universidade de Trás-os-Montes e Alto Douro (UTAD) Escola de Ciências e Tecnologia, his MSC in Computer Science - Knowledge and Decision Support (2011) and BSc in Computer Science (2008) from the Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto (ISEP/IPP). Tiago is an Assistant Professor at UTAD (Universidade de Trás-os-Montes e Alto Douro) and a senior researcher at INESC-TEC. He is also the Chair of IEEE PES Working Group on Multi-Agent Systems and Vice-Chair of IEEE PES Task Force on Open Data Sets. He has participated or participates in more than 45 national and international research projects, 7 of them as Project Coordinator, 1 as Co - Principal Investigator, 5 as Country coordinator. Tiago has published more than 70 papers in international journals, 16 book chapters and 8 edited books. He has also published more than 200 papers in international conferences. He has supervised/co-supervised multiple students (11 PhD, 3 concluded, 41 MSc, 21 concluded, 56 BSc, 51 concluded; and several international students from exchange programs such as EASMUS and PROPICIE). Tiago has a long experience in the organization of conferences, workshops, special sessions, tutorials and panel sessions in multiple relevant international congresses, such as IEEE PES-GM, IEEE SSCI, AAMAS, IJCAI, ECAI; and of special issues edition in international SCI journals. Tiago has received 19 prizes and awards. The main research interests are Artificial Intelligence (multiagent systems, machine learning, game theory, automated negotiation, metaheuristic optimization) in the domains of Power and Energy Systems (manly electricity markets, smart grid and building energy management) and Industry and mobility (including the development of intelligent solutions for enhanced productivity, management and operation of factories, and the development of innovative solutions for electrical vehicles).

Interest
Topics
Details

Details

  • Name

    Tiago Manuel Campelos
  • Role

    Senior Researcher
  • Since

    01st March 2022
Publications

2024

Contextual Rule-Based System for Brightness Energy Management in Buildings

Authors
Ferreira, V; Pinto, T; Baptista, J;

Publication
ELECTRONICS

Abstract
The increase in renewable generation of a distributed nature has brought significant new challenges to power and energy system management and operation. Self-consumption in buildings is widespread, and with it rises the need for novel, adaptive and intelligent building energy management systems. Although there is already extensive research and development work regarding building energy management solutions, the capabilities for adaptation and contextualization of decisions are still limited. Consequently, this paper proposes a novel contextual rule-based system for energy management in buildings, which incorporates a contextual dimension that enables the adaptability of the system according to diverse contextual situations and the presence of multiple users with different preferences. Results of a case study based on real data show that the contextualization of the energy management process can maintain energy costs as low as possible, while respecting user preferences and guaranteeing their comfort.

2024

Local electricity markets: A review on benefits, barriers, current trends and future perspectives

Authors
Faia, R; Lezama, F; Soares, J; Pinto, T; Vale, Z;

Publication
RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Abstract
Local electricity markets are emerging as a viable solution to overcome the challenges brought by the large penetration of distributed renewable generation and the need to put consumers as central players in the system, with an active and dynamic role. Although there is significant literature addressing the topic of local electricity markets, this is still a rather new and emerging topic. Hence, this study provides an overall view of this domain and a perspective on future needs and challenges that must be addressed. This review introduces the most important concepts in the local electricity market domain, provides an analysis on the different policy and regulatory framework, exposes the most relevant worldwide initiatives related to the field implementation, and scrutinizes the alternative local market models proposed in the literature. The discussion puts forth the main benefits and barriers of the currently proposed local market models, and the expected impact of their widespread implementation. The review is concluded with the wrap-up and discussion on the most relevant paths for future research and development in this field of study.

2024

Sustainable Irrigation Systems in Vineyards: A Literature Review on the Contribution of Renewable Energy Generation and Intelligent Resource Management Models

Authors
Branquinho, R; Briga-Sá, A; Ramos, S; Serôdio, C; Pinto, T;

Publication
ELECTRONICS

Abstract
Agriculture being an essential activity sector for the survival and prosperity of humanity, it is fundamental to use sustainable technologies in this field. With this in mind, some statistical data are analyzed regarding the food price rise and sustainable development indicators, with a special focus on the Portugal region. It is determined that one of the main factors that influences agriculture's success is the soil's characteristics, namely in terms of moisture and nutrients. In this regard, irrigation processes have become indispensable, and their technological management brings countless economic advantages. Like other branches of agriculture, the wine sector needs an adequate concentration of nutrients and moisture in the soil to provide the most efficient results, considering the appropriate and intelligent use of available water and energy resources. Given these facts, the use of renewable energies is a very important aspect of this study, which also synthesizes the main irrigation methods and examines the importance of evaluating the evapotranspiration of crops. Furthermore, the control of irrigation processes and the implementation of optimization and resource management models are of utmost importance to allow maximum efficiency and sustainability in this field.

2023

Design of Context-Aware Information Systems in Manufacturing Industries: Overview and Challenges

Authors
Santos, A; Lima, C; Reis, A; Pinto, T; Nogueira, P; Barroso, J;

Publication
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, Guimaraes, Portugal, 12-14 July 2023.

Abstract
In the last 30 years, several academic and commercial projects have explored the context-awareness concept in multiple domains. Ubiquitous computing and ambient intelligence are features associated with the 4th generation industry empowering space to interact and respond appropriately according to context. In the scope of Industry 4.0, context-aware systems aim to improve productivity in smart factories and offer assistance to workers through services, applications, and devices, delivering functionalities and contextualised content. This article, through descriptive research, discusses the concepts related to context, presents and analyses projects related to ubiquitous computing and associated with Industry 4.0, and discusses the main challenges in systems and applications development to support intelligent environments for increased productivity, supporting informed decision-making in the factories of the future. The study results indicate that many research questions regarding the analysed projects remain the same, leading the research in the context-aware systems area to minimise issues related to context-aware features, improving the incorporation of Industry 4.0 paradigm concepts. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

2023

Study of Forecasting Methods’ Impact in Wholesale Electricity Market Participation

Authors
Teixeira, B; Faia, R; Pinto, T; Vale, Z;

Publication
Lecture Notes in Networks and Systems

Abstract
Renewable energy sources have transformed the electricity market, allowing virtual power players or aggregators to participate and benefit from selling surplus energy. However, meeting demand and ensuring energy production stability can be challenging due to the intermittent nature of renewable sources. Accurate forecasting of energy consumption, generation, and electricity prices is critical to address these issues. Moreover, the selection of the best algorithm for forecasting is usually based on the predictions’ accuracy, neglecting other factors such as the impact of errors on the real context. This paper presents a study on the economic risk of price forecasting errors on the electricity market’s trading. For this, a simulation model is proposed to analyze the deviations between actual and predicted prices and how these deviations can affect trading in the electricity market, where the main purpose is to maximize profit, depending on whether the player is buying or selling electricity. The economic risk analysis and the predictions scores are used to improve the forecasts, using an approach based on reinforcement learning to evaluating and selecting which models demonstrated better performance in past transactions. The study involved simulating an aggregator’s transactions in the Iberian electricity market for two consecutive days in October 2021. Real data from the market operator between 2020 and 2021 and seven forecasting models were used. The findings showed that errors have a significant impact on profit. Including the economic impact analysis and score evaluation of forecasting methods to determine which method can offer better results has proven to be a viable approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Supervised
thesis

2023

Uso de assistentes virtuais no apoio à gestão de produção

Author
Rodrigo Cardoso Pereira

Institution
UTAD

2023

Análise e definição de contextos para a gestão energética em edifícios

Author
Vasco Rafael da Costa Ferreira

Institution
UTAD