{"id":48,"date":"2022-02-03T11:18:20","date_gmt":"2022-02-03T11:18:20","guid":{"rendered":"https:\/\/www.gecad.isep.ipp.pt\/precise\/?page_id=48"},"modified":"2025-05-14T15:00:13","modified_gmt":"2025-05-14T15:00:13","slug":"dissemination","status":"publish","type":"page","link":"http:\/\/www.gecad.isep.ipp.pt\/precise\/dissemination\/","title":{"rendered":"Dissemination"},"content":{"rendered":"\n

Scientific Publications<\/h2>\n\n\n\n
Scientific Journals<\/th><\/tr><\/thead>
Bruno Mota, Pedro Faria and Zita Vale, “Residential load shifting in demand response events for bill reduction using a genetic algorithm,” Energy, vol. 260, 124978, 2022, doi: 10.1016\/j.energy.2022.124978<\/a><\/td><\/tr>
Helder Pereira, Luis Gomes and Zita Vale, “Peer-to-peer energy trading optimization in energy communities using multi-agent deep reinforcement learning,” Energy Inform., vol. 5 (Suppl 4), 44, 2022, doi: 10.1186\/s42162-022-00235-2<\/a><\/td><\/tr>
C\u00e1tia Silva, Pedro Faria, and Zita Vale, \u201cRating and Remunerating the Load Shifting by Consumers Participating in Demand Response Programs,\u201d IEEE transactions on industry applications, vol. 59, no. 2, pp. 2288\u20132295, Mar. 2023, doi: 10.1109\/tia.2022.3224414<\/a><\/td><\/tr>
C\u00e1tia Silva, Pedro Faria, and Zita Vale, \u201cDemand Response Implementation: Overview of Europe and United States Status,\u201d Energies, vol. 16, no. 10, pp. 4043\u20134043, May 2023, doi: 10.3390\/en16104043<\/a><\/td><\/tr>
Gabriel Santos, Hugo Morais, Tiago Pinto, Juan M. Corchado, and Zita Vale, \u201cIntelligent Energy Systems Ontology to support markets and power systems co-simulation interoperability,\u201d Energy Conversion and Management: X, vol. 20, pp. 100495\u2013100495, Oct. 2023, doi: 10.1016\/j.ecmx.2023.100495<\/a><\/td><\/tr>
Br\u00edgida Teixeira, Tiago Pinto and Zita Vale, \u201cIntelligent Retraining for Dynamic Forecasting Environments: A Case Study in Short-Term Energy Consumption\u201d, Advanced Engineering Informatics, Elsevier, 2025 (Submitted<\/strong>)<\/td><\/tr>
Br\u00edgida Teixeira, Tiago Pinto and Zita Vale, \u201cContextual Automated Learning for Short-Term Power Consumption Forecasting in Building Energy Management\u201d, Energy Management and Conversion, Elsevier, 2025 (Submitted<\/strong>)<\/td><\/tr>
Br\u00edgida Teixeira, Leonor Carvalhais, Tiago Pinto and Zita Vale, \u201cExplainable AI Framework for Reliable and Transparent Automated Energy Management in Buildings\u201d, Energy and Buildings, Elsevier, 2025 (Submitted<\/strong>)<\/td><\/tr>
Br\u00edgida Teixeira, Gabriel Santos, David Ara\u00fajo, Let\u00edcia Gomes, Tiago Pinto, Zita Vale, \u201cSemantic Rule-Based Approach for Automated Energy Resource Management in Buildings.\u201d, Applied Energy, Elsevier, 2025 (Submitted<\/strong>)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
Conference Proceedings<\/th><\/tr><\/thead>
C\u00e1tia Silva, Pedro Faria and Zita Vale, “Using Supervised Learning to Assign New Consumers to Demand Response Programs According to the Context,” 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC \/ I&CPS Europe)<\/em>, 2022, pp. 1-6, doi: 10.1109\/EEEIC\/ICPSEurope54979.2022.9854646<\/a>.<\/td><\/tr>
Daniel Ramos, Pedro Faria, Lu\u00eds Gomes and Zita Vale, “Energy Forecast in Buildings Addressing Computation Consumption in a Green Computing Approach,” 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC \/ I&CPS Europe)<\/em>, 2022, pp. 1-6, doi: 10.1109\/EEEIC\/ICPSEurope54979.2022.9854723<\/a>.<\/td><\/tr>
Ubaid ur Rehman, Pedro Faria, Lu\u00eds Gomes and Zita Vale, “Artificial Neural Network Based Efficient Maximum Power Point Tracking for Photovoltaic Systems,” 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC \/ I&CPS Europe)<\/em>, 2022, pp. 1-6, doi: 10.1109\/EEEIC\/ICPSEurope54979.2022.9854613<\/a>.<\/td><\/tr>
Bruno Ribeiro, Helder Pereira, Luis Gomes and Zita Vale, “Python-based Ecosystem for Agent Communities Simulation”, 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)<\/em>, SOCO 2022, Lecture Notes in Networks and Systems, vol 531. Springer, Cham., doi: 10.1007\/978-3-031-18050-7_7<\/a>.<\/td><\/tr>
Ant\u00f3nio Ramos, Br\u00edgida Teixeira, Gabriel Santos, Tiago Pinto and Zita Vale, “Explainable artificial intelligence (XAI) techniques for energy consumption,” The 9th International Conference on Energy and Environment Research (ICEER)<\/em>, 2022, (To be published<\/strong>).<\/td><\/tr>
Leonor Carvalhais, Br\u00edgida Teixeira, Gabriel Santos and Zita Vale, “A framework proposal for explainable AI-based building energy management,” The 9th International Conference on Energy and Environment Research (ICEER)<\/em>, 2022, (To be published<\/strong><\/strong>).<\/td><\/tr>
C\u00e1tia Silva, Pedro Faria, and Zita Vale, \u201cDemand Response Event Participants Selection Using Classification Methods,\u201d IFAC-PapersOnLine, vol. 56, no. 2, pp. 10917\u201310922, Jan. 2023, doi: 10.1016\/j.ifacol.2023.10.776<\/a><\/td><\/tr>
C\u00e1tia Silva, Pedro Faria, and Zita Vale, \u201cEnhance Demand Response Participants Performance Using a Personalized Recommendation Method,\u201d in 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC \/ I&CPS Europe), Jun. 2023, pp. 1\u20136. doi: 10.1109\/EEEIC\/ICPSEurope57605.2023.1019465<\/a><\/td><\/tr>
Gabriel Santos, Br\u00edgida Teixeira, Tiago Pinto, and Zita Vale, \u201cAutomated energy management and learning,\u201d in 2023 IEEE Conference on Artificial Intelligence (CAI), Jun. 2023, pp. 69\u201370. doi: 10.1109\/CAI54212.2023.00037<\/a><\/td><\/tr>
Br\u00edgida Teixeira, Leonor Carvalhais, Tiago Pinto, and Zita Vale, \u201cApplication of XAI-based framework for PV Energy Generation Forecasting,\u201d in 2023 IEEE Conference on Artificial Intelligence (CAI), Jun. 2023, pp. 67\u201368. doi: 10.1109\/CAI54212.2023.00036<\/a><\/td><\/tr>
Jo\u00e3o Carvalho, Tiago Pinto, Juan M. Home-Ortiz, Br\u00edgida Teixeira, Zita Vale, and Ruben Romero, \u201cDynamic Parameterization of Metaheuristics Using a Multi-agent System for the Optimization of Electricity Market Participation,\u201d in Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, R. Mehmood, V. Alves, I. Pra\u00e7a, J. Wikarek, J. Parra-Dom\u00ednguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes, and M. Ricca, Eds., Cham: Springer Nature Switzerland, 2023, pp. 245\u2013255. doi: 10.1007\/978-3-031-38318-2_25<\/a><\/td><\/tr>
Br\u00edgida Teixeira, Ricardo Faia, Tiago Pinto, and Zita Vale, \u201cStudy of Forecasting Methods\u2019 Impact in Wholesale Electricity Market Participation,\u201d in Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, R. Mehmood, V. Alves, I. Pra\u00e7a, J. Wikarek, J. Parra-Dom\u00ednguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes, and M. Ricca, Eds., Cham: Springer Nature Switzerland, 2023, pp. 267\u2013276. doi: 10.1007\/978-3-031-38318-2_27<\/a><\/td><\/tr>
C\u00e1tia Silva, Pedro Faria, and Zita Vale, \u201cLocal Energy Market Competition Approach for Demand Response Events,\u201d in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Oct. 2023, pp. 1\u20135. doi: 10.1109\/ISGTEUROPE56780.2023.10407496<\/a><\/td><\/tr>
Ruben Barreto, Luis Gomes, Pedro Faria, and Zita Vale, \u201cDemand Response-based Energy Management Model for Energy Communities considering Data Privacy of the Members,\u201d in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Oct. 2023, pp. 1\u20135. doi: 10.1109\/ISGTEUROPE56780.2023.10407921<\/a><\/td><\/tr>
Daniel Ramos, Pedro Faria, and Zita Vale, \u201cExplainable Artificial Intelligence for Definition of Inputs in Neural Networks and K-nearest Neighbors Forecasting of Electricity Consumption,\u201d in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Oct. 2023, pp. 1\u20135. doi: 10.1109\/ISGTEUROPE56780.2023.10408289<\/a><\/td><\/tr>
D\u00e9bora de S\u00e3o Jos\u00e9, Pedro Faria and Zita Vale, \u201cSecond-Life Batteries: European Market and Shortcomings in Policy Making\u201d, in ICEER 2023 – The 10th International Conference on Energy and Environment Research, October 7-9, 2023, Doi: https:\/\/doi.org\/10.1007\/978-3-031-54394-4_20<\/a><\/td><\/tr>
Teixeira, Br\u00edgida, Tiago Pinto, e Zita Vale. \u00abEnhancing Power Forecasting Through Contextual Awareness with C-Means and K-Means Approaches\u00bb. Em Distributed Computing and Artificial Intelligence, 21st International Conference, editado por Ravikumar Chinthaginjala, Pawel Sitek, Nasro Min-Allah, Kenji Matsui, Sascha Ossowski, e Sara Rodr\u00edguez, 31\u201342. Cham: Springer Nature Switzerland, 2025. https:\/\/doi.org\/10.1007\/978-3-031-82073-1_4<\/a><\/td><\/tr>
Br\u00edgida Teixeira, Gabriel Santos, Let\u00edcia Gomes, David Ara\u00fajo and Zita Vale, \u201cSmart Building Platform for Energy Resource Management\u201d, IEEE Conference on Artificial Intelligence (IEEE CAI) 2025, May 5-7, Santa Clara, California, USA, 2025 (Presented<\/strong>)<\/td><\/tr>
Br\u00edgida Teixeira, Gabriel Santos, Tiago Pinto and Zita Vale, \u201cLeveraging Ontologies and Semantic Web Technologies to enhance XAI in Smart Building Energy Systems\u201d, The European Conference on Artificial Intelligence (ECAI) 2025, October 25-30, Bologna, Italy, 2025 (Submitted<\/strong>)<\/td><\/tr>
Br\u00edgida Teixeira, Tiago Pinto and Zita Vale, \u201cLeveraging XAI Techniques for Context-Aware Energy Consumption Forecasting\u201d, 3rd World Conference on XAI, Istanbul, 2025 (Submitted<\/strong>)<\/td><\/tr>
Br\u00edgida Teixeira, Tiago Pinto and Zita Vale, \u201cDetecting Concept Drift with SHapley Additive exPlanations for Intelligent Model Retraining in Energy Generation Forecasting\u201d, 3rd World Conference on XAI, Istanbul, 2025 (Submitted<\/strong>)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
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Scientific Publications Scientific Journals Bruno Mota, Pedro Faria and Zita Vale, “Residential load shifting in demand response events for bill reduction using a genetic algorithm,” Energy, vol. 260, 124978, 2022, doi: 10.1016\/j.energy.2022.124978 Helder Pereira, Luis Gomes and Zita Vale, “Peer-to-peer energy trading optimization in energy communities using multi-agent deep reinforcement learning,” Energy Inform., vol. 5…
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