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Computationally efficient reinforcement learning: targeted exploration leveraging simple rules
Di Natale, L., Svetozarevic, B., Heer, P., & Jones, C. N. (2024). Computationally efficient reinforcement learning: targeted exploration leveraging simple rules. In Proceedings of the IEEE conference on decision and control (CDC) (pp. 2334-2339). https://doi.org/10.1109/CDC49753.2023.10384283
Data-driven adaptive building thermal controller tuning with constraints: a primal–dual contextual Bayesian optimization approach
Xu, W., Svetozarevic, B., Di Natale, L., Heer, P., & Jones, C. N. (2024). Data-driven adaptive building thermal controller tuning with constraints: a primal–dual contextual Bayesian optimization approach. Applied Energy, 358, 122493 (13 pp.). https://doi.org/10.1016/j.apenergy.2023.122493
Data-driven predictive control for demand side management: theoretical and experimental results
Yin, M., Cai, H., Gattiglio, A., Khayatian, F., Smith, R. S., & Heer, P. (2024). Data-driven predictive control for demand side management: theoretical and experimental results. Applied Energy, 353, 122101 (12 pp.). https://doi.org/10.1016/j.apenergy.2023.122101
Performance gaps between energy system planning and operation: a study exploring the impacts of model fidelity and dispatch strategy
Beaud, M., Cai, H., Perera, A. T. D., & Heer, P. (2023). Performance gaps between energy system planning and operation: a study exploring the impacts of model fidelity and dispatch strategy. In Journal of physics: conference series: Vol. 2600. Energy performance modelling (p. 032016 (6 pp.). https://doi.org/10.1088/1742-6596/2600/3/032016
Degradation-aware data-enabled predictive control of energy hubs
Behrunani, V., Zagorowska, M., Hudoba de Badyn, M., Ricca, F., Heer, P., & Lygeros, J. (2023). Degradation-aware data-enabled predictive control of energy hubs. In Journal of physics: conference series: Vol. 2600. Predictive & adaptive control (p. 072006 (6 pp.). https://doi.org/10.1088/1742-6596/2600/7/072006
Designing fairness in autonomous peer-to-peer energy trading
Behrunani, V. N., Irvine, A., Belgioioso, G., Heer, P., Lygeros, J., & Dörfler, F. (2023). Designing fairness in autonomous peer-to-peer energy trading. In H. Ishii, Y. Ebihara, Jichi Imura, & M. Yamakita (Eds.), IFAC-PapersOnLine: Vol. 56. IFAC world congress (pp. 3751-3756). https://doi.org/10.1016/j.ifacol.2023.10.1544
Experimental validation for distributed control of energy hubs
Behrunani, V., Heer, P., & Lygeros, J. (2023). Experimental validation for distributed control of energy hubs. In Journal of physics: conference series: Vol. 2600. Predictive & adaptive control (p. 072004 (7 pp.). https://doi.org/10.1088/1742-6596/2600/7/072004
Data-driven modeling of heat pumps and thermal storage units for MPC
Brandes, M., Cai, H., Vivian, J., Croci, L., Heer, P., & Smith, R. (2023). Data-driven modeling of heat pumps and thermal storage units for MPC. In Journal of physics: conference series: Vol. 2600. Energy performance modelling (p. 032008 (6 pp.). https://doi.org/10.1088/1742-6596/2600/3/032008
Increasing electrical reserve provision in districts by exploiting energy flexibility of buildings with robust model predictive control
Bünning, F., Heer, P., Smith, R. S., & Lygeros, J. (2023). Increasing electrical reserve provision in districts by exploiting energy flexibility of buildings with robust model predictive control. Advances in Applied Energy, 10, 100130 (12 pp.). https://doi.org/10.1016/j.adapen.2023.100130
Computationally efficient reinforcement learning: targeted exploration leveraging simple rules
Di Natale, L., Svetozarevic, B., Heer, P., & Jones, C. N. (2023). Computationally efficient reinforcement learning: targeted exploration leveraging simple rules. In Proceedings of the IEEE conference on decision and control. IEEE conference on decision and control (pp. 2334-2339). https://doi.org/10.1109/CDC49753.2023.10383956
Towards scalable physically consistent neural networks: an application to data-driven multi-zone thermal building models
Di Natale, L., Svetozarevic, B., Heer, P., & Jones, C. N. (2023). Towards scalable physically consistent neural networks: an application to data-driven multi-zone thermal building models. Applied Energy, 340, 121071 (16 pp.). https://doi.org/10.1016/j.apenergy.2023.121071
Design optimization of a district heating and cooling system with a borehole seasonal thermal energy storage
Fiorentini, M., Heer, P., & Baldini, L. (2023). Design optimization of a district heating and cooling system with a borehole seasonal thermal energy storage. Energy, 262, 125464 (15 pp.). https://doi.org/10.1016/j.energy.2022.125464
Modeling and real-time control of a hydrogen refueling station with uncertain demand
Fochesato, M., Laaksonlaita, T., Heer, P., & Lygeros, J. (2023). Modeling and real-time control of a hydrogen refueling station with uncertain demand. In H. Ishii, Y. Ebihara, Jichi Imura, & M. Yamakita (Eds.), IFAC PapersOnLine: Vol. 56. 22nd IFAC world congress, Yokohama, Japan, July 9-14, 2023 (pp. 2695-2700). https://doi.org/10.1016/j.ifacol.2023.10.1363
K3 Handwerkcity. Der Gewerbepark erreicht hohen energetischen Selbstversorgungsgrad
Heer, P., Brandes, M., Cai, H., & Palla, H. (2023). K3 Handwerkcity. Der Gewerbepark erreicht hohen energetischen Selbstversorgungsgrad. Aqua & Gas, 103(6), 20-26.
Data-driven demand-side flexibility quantification: prediction and approximation of flexibility envelopes
Hekmat, N., Cai, H., Zufferey, T., Hug, G., & Heer, P. (2023). Data-driven demand-side flexibility quantification: prediction and approximation of flexibility envelopes. In Power tech conference. 2023 IEEE Belgrade PowerTech (p. (6 pp.). https://doi.org/10.1109/PowerTech55446.2023.10202703
Flexibility assessment of power-hydrogen-power (P2H2P) system in multi-energy districts
Koirala, B. P., Cai, H., de Koning, J., Heer, P., & Orehounig, K. (2023). Flexibility assessment of power-hydrogen-power (P2H2P) system in multi-energy districts. In Journal of physics: conference series: Vol. 2600. Predictive & adaptive control (p. 072007 (6 pp.). https://doi.org/10.1088/1742-6596/2600/7/072007
Flexibility implications of optimal PV design: building vs. community scale
Li, Q., Vulic, N., Cai, H., & Heer, P. (2023). Flexibility implications of optimal PV design: building vs. community scale. In Journal of physics: conference series: Vol. 2600. Optimization at building & urban scale (p. 082002 (7 pp.). https://doi.org/10.1088/1742-6596/2600/8/082002
Stochastic MPC for energy hubs using data driven demand forecasting
Micheli, F., Behrunani, V., Mehr, J., Heer, P., & Lygeros, J. (2023). Stochastic MPC for energy hubs using data driven demand forecasting. In H. Ishii, Y. Ebihara, Jichi Imura, & M. Yamakita (Eds.), IFAC-PapersOnLine: Vol. 56. 22nd IFAC world congress, Yokohama, Japan, July 9-14, 2023 (pp. 11026-11031). https://doi.org/10.1016/j.ifacol.2023.10.803
Uncertainty-aware energy flexibility quantification of a residential building
Rousseau, J., Cai, H., Heer, P., Orehounig, K., & Hug, G. (2023). Uncertainty-aware energy flexibility quantification of a residential building. In IEEE PES Innovative Smart Grid Technologies Conference Europe. Proceedings of 2023 IEEE PES innovative smart grid technologies Europe (ISGT EUROPE 2023). https://doi.org/10.1109/ISGTEUROPE56780.2023.10407489
Impact of forecast uncertainty and electricity markets on the flexibility provision and economic performance of highly-decarbonized multi-energy systems
Srinivasan, A., Wu, R., Heer, P., & Sansavini, G. (2023). Impact of forecast uncertainty and electricity markets on the flexibility provision and economic performance of highly-decarbonized multi-energy systems. Applied Energy, 338, 120825 (16 pp.). https://doi.org/10.1016/j.apenergy.2023.120825