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Techno-economic analysis of control algorithms for an exhaust air heat pump system for detached houses coupled to a photovoltaic system
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences. Dalarna Univ, Energy Technol, Borlange, Sweden.
Univ Trento, Dept Civil Environm & Mech Engn, Trento, Italy.
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Applied Mechanics, Byggteknik.ORCID iD: 0000-0003-4887-9547
Dalarna Univ, Energy Technol, Borlange, Sweden.
2019 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 249, p. 355-367Article in journal (Refereed) Published
Abstract [en]

Operational control strategies for the heating system and "smart" utilization of energy storage were developed and analyzed in a simulation based case study of a single-family house with exhaust air heat pump and photovoltaic system. Rule based control algorithms that can easily be implemented into modern heat pump controllers were developed with the aim to minimize final energy and maximize self-consumption by the use of the thermal storage of the building, the hot water tank and electrical storage. Short-term weather and electricity price forecasts are used in some of the algorithms. Heat supply from an exhaust air heat pump is limited by the ventilation flow rate fixed by building codes, and compact systems employ an electric heater as backup for both space heating and hot water. This heater plays an important role in the energy balance of the system. A typical system designed for new detached houses in Sweden was chosen for the study. This system, together with an independent photovoltaic system, was used as a base case and all results are compared to those for this base case system. TRNSYS 17 was used to model the building and system as well as the control algorithms, and special care was taken to model the use of the backup electric heater as this impacts significantly on final energy use. Results show that the developed algorithms can reduce final energy by 5-31% and the annual net cost for the end user by 3-26%, with the larger values being for systems with a battery storage. Moreover, the annual use of the backup electric heater can be decreased by 13-30% using the carefully designed algorithms.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2019. Vol. 249, p. 355-367
Keywords [en]
Photovoltaics, Heat pump, Forecast services, Thermal storage, Electrical storage, Control algorithms
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:uu:diva-390382DOI: 10.1016/j.apenergy.2019.04.080ISI: 000472692200029OAI: oai:DiVA.org:uu-390382DiVA, id: diva2:1341787
Funder
Knowledge Foundation, 20160171Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-11-22Bibliographically approved
In thesis
1. Smart control of PV and exhaust air heat pump systems in single-family buildings
Open this publication in new window or tab >>Smart control of PV and exhaust air heat pump systems in single-family buildings
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Recently, decentralized household photovoltaic (PV) systems have become more affordable and there is a tendency to decrease subsidies for the PV excess electricity fed into the grid. Therefore, there is growing interest in methods to increase the self-consumption (SC), which is the part of the electricity produced by PV and directly consumed on buildings. It has been found that battery storage is an effective way to achieve this. When there is a heat pump system installed, thermal energy storage using the thermal mass of the building or hot water tanks, can also be used to increase the household self-sufficiency and minimize the final energy use. The main aim of this thesis is to develop operational control strategies for the heating system of a single-family house with an exhaust air heat pump, a photovoltaic system and energy storage. In order to accomplish this a detailed system model was developed in TRNSYS 17, which includes a six-zone building model and the heat pump control. Moreover, these control strategies include short-term weather and price forecast services.  Another objective is to evaluate the impact on the benefit of these control strategies in terms of energy use and economic performance for a wide range of boundary conditions (country/climate, electricity prices, occupancy and appliance loads).  Results show that the control using a forecast of dynamic electricity price in most locations leads to greater final energy savings than those due to the control using thermal storage for excess PV production. The exception is Sweden, where the result is the opposite. Moreover, the addition of battery storage leads to greater decreases in final energy than the use of the thermal storage (TH mode), which is limited to the thermal mass of the building and small hot water tank of the compact heat pump. As far as the impact of the advanced control (combined use of TH and PRICE) on cost savings is concerned, savings (up to 175 €) are possible in Spain and in Germany. The design of the TH and PRICE mode show low computational complexity that can be easily implemented in existing heat pump controllers. Additionally, the PRICE mode should have no capital and running cost for the end user while the TH mode might require an external electricity meter. Another yet implication with the TH mode is the need to activate the room thermostatic valve.

Place, publisher, year, edition, pages
Uppsala: , 2019. p. 50
Keywords
photovoltaics, heat pump, forecast services, thermal storage, electrical storage, control algorithms
National Category
Engineering and Technology
Identifiers
urn:nbn:se:uu:diva-397488 (URN)
Opponent
Supervisors
Funder
Knowledge Foundation, 20160171
Available from: 2019-12-17 Created: 2019-11-22 Last updated: 2019-12-17Bibliographically approved

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