Dissemination – PRECISE

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 (Suppl 4), 44, 2022, doi: 10.1186/s42162-022-00235-2
Cátia Silva, Pedro Faria, and Zita Vale, “Rating and Remunerating the Load Shifting by Consumers Participating in Demand Response Programs,” IEEE transactions on industry applications, vol. 59, no. 2, pp. 2288–2295, Mar. 2023, doi: 10.1109/tia.2022.3224414
Cátia Silva, Pedro Faria, and Zita Vale, “Demand Response Implementation: Overview of Europe and United States Status,” Energies, vol. 16, no. 10, pp. 4043–4043, May 2023, doi: 10.3390/en16104043
Gabriel Santos, Hugo Morais, Tiago Pinto, Juan M. Corchado, and Zita Vale, “Intelligent Energy Systems Ontology to support markets and power systems co-simulation interoperability,” Energy Conversion and Management: X, vol. 20, pp. 100495–100495, Oct. 2023, doi: 10.1016/j.ecmx.2023.100495
Brígida Teixeira, Tiago Pinto and Zita Vale, “Intelligent Retraining for Dynamic Forecasting Environments: A Case Study in Short-Term Energy Consumption”, Advanced Engineering Informatics, Elsevier, 2025 (Submitted)
Brígida Teixeira, Tiago Pinto and Zita Vale, “Contextual Automated Learning for Short-Term Power Consumption Forecasting in Building Energy Management”, Energy Management and Conversion, Elsevier, 2025 (Submitted)
Brígida Teixeira, Leonor Carvalhais, Tiago Pinto and Zita Vale, “Explainable AI Framework for Reliable and Transparent Automated Energy Management in Buildings”, Energy and Buildings, Elsevier, 2025 (Submitted)
Brígida Teixeira, Gabriel Santos, David Araújo, Letícia Gomes, Tiago Pinto, Zita Vale, “Semantic Rule-Based Approach for Automated Energy Resource Management in Buildings.”, Applied Energy, Elsevier, 2025 (Submitted)

Conference Proceedings
Cátia 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), 2022, pp. 1-6, doi: 10.1109/EEEIC/ICPSEurope54979.2022.9854646.
Daniel Ramos, Pedro Faria, Luís 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), 2022, pp. 1-6, doi: 10.1109/EEEIC/ICPSEurope54979.2022.9854723.
Ubaid ur Rehman, Pedro Faria, Luís 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), 2022, pp. 1-6, doi: 10.1109/EEEIC/ICPSEurope54979.2022.9854613.
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), SOCO 2022, Lecture Notes in Networks and Systems, vol 531. Springer, Cham., doi: 10.1007/978-3-031-18050-7_7.
António Ramos, Brígida 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), 2022, (To be published).
Leonor Carvalhais, Brígida 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), 2022, (To be published).
Cátia Silva, Pedro Faria, and Zita Vale, “Demand Response Event Participants Selection Using Classification Methods,” IFAC-PapersOnLine, vol. 56, no. 2, pp. 10917–10922, Jan. 2023, doi: 10.1016/j.ifacol.2023.10.776
Cátia Silva, Pedro Faria, and Zita Vale, “Enhance Demand Response Participants Performance Using a Personalized Recommendation Method,” 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. 1–6. doi: 10.1109/EEEIC/ICPSEurope57605.2023.1019465
Gabriel Santos, Brígida Teixeira, Tiago Pinto, and Zita Vale, “Automated energy management and learning,” in 2023 IEEE Conference on Artificial Intelligence (CAI), Jun. 2023, pp. 69–70. doi: 10.1109/CAI54212.2023.00037
Brígida Teixeira, Leonor Carvalhais, Tiago Pinto, and Zita Vale, “Application of XAI-based framework for PV Energy Generation Forecasting,” in 2023 IEEE Conference on Artificial Intelligence (CAI), Jun. 2023, pp. 67–68. doi: 10.1109/CAI54212.2023.00036
João Carvalho, Tiago Pinto, Juan M. Home-Ortiz, Brígida Teixeira, Zita Vale, and Ruben Romero, “Dynamic Parameterization of Metaheuristics Using a Multi-agent System for the Optimization of Electricity Market Participation,” in Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, R. Mehmood, V. Alves, I. Praça, J. Wikarek, J. Parra-Domínguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes, and M. Ricca, Eds., Cham: Springer Nature Switzerland, 2023, pp. 245–255. doi: 10.1007/978-3-031-38318-2_25
Brígida Teixeira, Ricardo Faia, Tiago Pinto, and Zita Vale, “Study of Forecasting Methods’ Impact in Wholesale Electricity Market Participation,” in Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference, R. Mehmood, V. Alves, I. Praça, J. Wikarek, J. Parra-Domínguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes, and M. Ricca, Eds., Cham: Springer Nature Switzerland, 2023, pp. 267–276. doi: 10.1007/978-3-031-38318-2_27
Cátia Silva, Pedro Faria, and Zita Vale, “Local Energy Market Competition Approach for Demand Response Events,” in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Oct. 2023, pp. 1–5. doi: 10.1109/ISGTEUROPE56780.2023.10407496
Ruben Barreto, Luis Gomes, Pedro Faria, and Zita Vale, “Demand Response-based Energy Management Model for Energy Communities considering Data Privacy of the Members,” in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Oct. 2023, pp. 1–5. doi: 10.1109/ISGTEUROPE56780.2023.10407921
Daniel Ramos, Pedro Faria, and Zita Vale, “Explainable Artificial Intelligence for Definition of Inputs in Neural Networks and K-nearest Neighbors Forecasting of Electricity Consumption,” in 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Oct. 2023, pp. 1–5. doi: 10.1109/ISGTEUROPE56780.2023.10408289
Débora de São José, Pedro Faria and Zita Vale, “Second-Life Batteries: European Market and Shortcomings in Policy Making”, 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
Teixeira, Brígida, Tiago Pinto, e Zita Vale. «Enhancing Power Forecasting Through Contextual Awareness with C-Means and K-Means Approaches». Em Distributed Computing and Artificial Intelligence, 21st International Conference, editado por Ravikumar Chinthaginjala, Pawel Sitek, Nasro Min-Allah, Kenji Matsui, Sascha Ossowski, e Sara Rodríguez, 31–42. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82073-1_4
Brígida Teixeira, Gabriel Santos, Letícia Gomes, David Araújo and Zita Vale, “Smart Building Platform for Energy Resource Management”, IEEE Conference on Artificial Intelligence (IEEE CAI) 2025, May 5-7, Santa Clara, California, USA, 2025 (Presented)
Brígida Teixeira, Gabriel Santos, Tiago Pinto and Zita Vale, “Leveraging Ontologies and Semantic Web Technologies to enhance XAI in Smart Building Energy Systems”, The European Conference on Artificial Intelligence (ECAI) 2025, October 25-30, Bologna, Italy, 2025 (Submitted)
Brígida Teixeira, Tiago Pinto and Zita Vale, “Leveraging XAI Techniques for Context-Aware Energy Consumption Forecasting”, 3rd World Conference on XAI, Istanbul, 2025 (Submitted)
Brígida Teixeira, Tiago Pinto and Zita Vale, “Detecting Concept Drift with SHapley Additive exPlanations for Intelligent Model Retraining in Energy Generation Forecasting”, 3rd World Conference on XAI, Istanbul, 2025 (Submitted)