Journals

1. P. Tzallas, A. Papaioannou, A. Dimara, N. Bezas, I. Moschos, C. N. Anagnostopoulos, S. Krinidis, D. Ioannidis, D. Tzovaras, "MAS-DR: An ML-Based Aggregation and Segmentation Framework for Residential Consumption Users to Assist DR Programs.", Sustainability, vol. 17, no. 4, February 13, 2025.

Conference

1. T. Samaras, A. Dimara, P. Tzallas, A. Papaioannou, N. Bezas, S. Krinidis, C. N. Anagnostopoulos, D. Ioannidis, D. Tzovaras, "Edge-Computing FogFlow Framework For Solar Generation Prediction Exploiting Federated Learning.", in Proceedings of the International Conference on Modeling & E-Information Research, Artificial Learning and Digital Applications (ICMERALDA), November 24, 2023, pp. 149-154.
2. P. Tzallas, A. Papaioannou, A. Dimara, S. Krinidis, G. Pavlidis, C. Anagnostopoulos, D. Ioannidis, D. Tzovaras, "Advanced Contextual-targeted Building Flexibility Based on Signature Labelling for Demand Response.", in Proceedings of the IEEE Electrical Power and Energy Conference (EPEC), December 2022, pp. 380-385. https://ieeexplore.ieee.org/abstract/document/10000249
3. P. Tzallas, N. Bezas, I. Moschos, D. Ioannidis, D. Tzovaras, "Probabilistic Quantile Multi-step Forecasting of Energy Market Prices: A UK Case Study.", in Proceedings of the IFIP International Conference on Artificial Intelligence Applications and Innovations, Springer, Cham, 2022, pp. 301-313.