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Toni Mancini, Federico Mari, Annalisa Massini, Igor Melatti, and Enrico Tronci. "Simulator Semantics for System Level Formal Verification." In Proceedings Sixth International Symposium on Games, Automata, Logics and Formal Verification (GandALF 2015),., 2015. DOI: 10.4204/EPTCS.193.7.
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V. Alimguzhin, F. Mari, I. Melatti, E. Tronci, E. Ebeid, S. A. Mikkelsen, R. H. Jacobsen, J. K. Gruber, B. Hayes, F. Huerta et al. "A Glimpse of SmartHG Project Test-bed and Communication Infrastructure." In Digital System Design (DSD), 2015 Euromicro Conference on, 225–232., 2015. DOI: 10.1109/DSD.2015.106.
Keywords: Batteries; Control systems; Databases; Production; Sensors; Servers; Smart grids; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis
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T. Mancini, F. Mari, I. Melatti, I. Salvo, and E. Tronci. "An Efficient Algorithm for Network Vulnerability Analysis Under Malicious Attacks." In Foundations of Intelligent Systems – 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29-31, 2018, Proceedings, 302–312., 2018. Notes: Best Paper. DOI: 10.1007/978-3-030-01851-1_29.
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T. Mancini, F. Mari, I. Melatti, I. Salvo, E. Tronci, J. K. Gruber, B. Hayes, M. Prodanovic, and L. Elmegaard. "User Flexibility Aware Price Policy Synthesis for Smart Grids." In Digital System Design (DSD), 2015 Euromicro Conference on, 478–485., 2015. DOI: 10.1109/DSD.2015.35.
Keywords: Contracts; Current measurement; Load management; Power demand; Power measurement; State estimation; Substations; Grid State Estimation; Peak Shaving; Policy Robustness Verification; Price Policy Synthesis
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T. Mancini, F. Mari, A. Massini, I. Melatti, I. Salvo, and E. Tronci. "On minimising the maximum expected verification time." Information Processing Letters (2017). DOI: 10.1016/j.ipl.2017.02.001.
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R. Ehrig, T. Dierkes, S. Schaefer, S. Roeblitz, E. Tronci, T. Mancini, I. Salvo, V. Alimguzhin, F. Mari, I. Melatti et al. "An integrative approach for model driven computation of treatments in reproductive medicine." In Proceedings of the 15th International Symposium on Mathematical and Computational Biology (BIOMAT 2015), Rorkee, India., 2015. DOI: 10.1142/9789813141919_0005.
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T. Mancini, F. Mari, A. Massini, I. Melatti, and E. Tronci. "SyLVaaS: System Level Formal Verification as a Service." Fundamenta Informaticae 149, no. 1-2 (2016): 101–132. DOI: 10.3233/FI-2016-1444.
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T. Mancini, F. Mari, I. Melatti, I. Salvo, E. Tronci, J. Gruber, B. Hayes, M. Prodanovic, and L. Elmegaard. "Parallel Statistical Model Checking for Safety Verification in Smart Grids." In 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 1–6., 2018. DOI: 10.1109/SmartGridComm.2018.8587416.
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T. Mancini, F. Mari, A. Massini, I. Melatti, I. Salvo, S. Sinisi, E. Tronci, R. Ehrig, S. Röblitz, and B. Leeners. "Computing Personalised Treatments through In Silico Clinical Trials. A Case Study on Downregulation in Assisted Reproduction." In 25th RCRA International Workshop on “Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion” (RCRA 2018)., 2018. DOI: 10.29007/g864.
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I. Melatti, F. Mari, T. Mancini, M. Prodanovic, and E. Tronci. "A Two-Layer Near-Optimal Strategy for Substation Constraint Management via Home Batteries." IEEE Transactions on Industrial Electronics (2021): 1. Notes: To appear. DOI: 10.1109/TIE.2021.3102431.
Abstract: Within electrical distribution networks, substation constraints management requires that aggregated power demand from residential users is kept within suitable bounds. Efficiency of substation constraints management can be measured as the reduction of constraints violations w.r.t. unmanaged demand. Home batteries hold the promise of enabling efficient and user-oblivious substation constraints management. Centralized control of home batteries would achieve optimal efficiency. However, it is hardly acceptable by users, since service providers (e.g., utilities or aggregators) would directly control batteries at user premises. Unfortunately, devising efficient hierarchical control strategies, thus overcoming the above problem, is far from easy. We present a novel two-layer control strategy for home batteries that avoids direct control of home devices by the service provider and at the same time yields near-optimal substation constraints management efficiency. Our simulation results on field data from 62 households in Denmark show that the substation constraints management efficiency achieved with our approach is at least 82% of the one obtained with a theoretical optimal centralized strategy.
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