Abstract
| Original language | English |
|---|---|
| Publication date | 2017 |
| Publication status | Published - 2017 |
| Event | Building Simulation 2017: The 15th International Conference of IBPSA - San Francisco, United States Duration: 7 Aug 2017 → 9 Aug 2017 Conference number: 15 |
Conference
| Conference | Building Simulation 2017 |
|---|---|
| Number | 15 |
| Country | United States |
| City | San Francisco |
| Period | 07/08/2017 → 09/08/2017 |
Cite this
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Intelligent Scheduling of a Grid-Connected Heat Pump in a Danish Detached House. / Gianniou, Panagiota; Foteinaki, Kyriaki; Heller, Alfred; Rode, Carsten.
2017. Paper presented at Building Simulation 2017, San Francisco, United States.Research output: Contribution to conference › Paper › Research › peer-review
TY - CONF
T1 - Intelligent Scheduling of a Grid-Connected Heat Pump in a Danish Detached House
AU - Gianniou, Panagiota
AU - Foteinaki, Kyriaki
AU - Heller, Alfred
AU - Rode, Carsten
PY - 2017
Y1 - 2017
N2 - This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished grid-connected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation of the system is based on a price-signal considering a three-day period for different weather cases. The results show that the optimal scheduling of the system is successful in terms of reducing the peak load during times when electricity prices are high, thus achieving cost savings as well as maintaining good thermal comfort conditions. The proposed methodology bridges dynamic building modelling with optimization of real-time operation of HVAC systems offering a detailed model for building physics, especially regarding thermal mass and a stochastic price-based control.
AB - This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished grid-connected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation of the system is based on a price-signal considering a three-day period for different weather cases. The results show that the optimal scheduling of the system is successful in terms of reducing the peak load during times when electricity prices are high, thus achieving cost savings as well as maintaining good thermal comfort conditions. The proposed methodology bridges dynamic building modelling with optimization of real-time operation of HVAC systems offering a detailed model for building physics, especially regarding thermal mass and a stochastic price-based control.
M3 - Paper
ER -