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  • 1. Bee, Elena
    et al.
    Prada, Alessandro
    Baggio, Paolo
    Psimopoulos, Emmanouil
    Dalarna University, School of Technology and Business Studies, Energy Technology. Uppsala University.
    Air-source heat pump and photovoltaic systems for residential heating and cooling: Potential of self-consumption in different European climates2019In: Building Simulation, ISSN 1996-3599, E-ISSN 1996-8744, Vol. 12, no 3, p. 453-463Article in journal (Refereed)
    Abstract [en]

    Renewable sources will play a key role in meeting the EU targets for 2030. The combined use of an aerothermal source through a heat pump and a solar source with a photovoltaic (PV) system is one feasible and promising technology for the heating and cooling of residential spaces. In this study, a detailed model of a single-family house with an air-source heat pump and a PV system is developed with the TRNSYS simulation software. Yearly simulations are run for two types of buildings and nine European climates, for both heating and cooling (where needed), in order to have an overview of the system behaviour, which is deeply influenced by the climate. The storage system (electrical and thermal) is also investigated, by means of multiple simulation scenarios, with and without the battery and with different water storage sizes. The numerical results provide an overview of the performance of the considered heating and cooling system, as well as the balance of the electrical energy exchange between the grid, the building, and the PV array.

  • 2.
    Luthander, Rasmus
    et al.
    Uppsala universitet, Fasta tillståndets fysik.
    Psimopoulos, Emmanouil
    Dalarna University, School of Technology and Business Studies, Energy Technology. Uppsala universitet, Fasta tillståndets fysik.
    Widén, Joakim
    Uppsala universitet, Fasta tillståndets fysik.
    Demand Side Management Using PV, Heat Pumps and Batteries: Effects on Community and Building Level2017In: Proceedings of the 33rd European Photovoltaic Solar Energy Conference, 2017Conference paper (Refereed)
    Abstract [en]

    This study examines how the energy management optimization on household level affects the maximum power flow in a community of houses and the contribution to load smoothening in the community. A detailed model of a single-family house with exhaust air heat pump and photovoltaic system is used in combination with high-resolution weather, electricity use and hot water use data. All five houses in the community are identical but the occupancy of the residents and their use of electric appliances and hot water differ. Results show no reduction of the maximum power delivered to the grid if the houses are operated to optimize the individual self-consumption and self-sufficiency. The highest aggregated power from the grid for the whole community occurred when the heat pumps were controlled by the PV electricity production but without any battery storage. This case also resulted in least smoothing of the aggregated household loads in the community. The conclusion of the study is that energy optimization for individual households in a community do not have to result in a reduction of the aggregated load and power production.

  • 3.
    Psimopoulos, Emmanouil
    et al.
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Bee, E.
    Luthander, R.
    Bales, Chris
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Smart control strategy for PV and heat pump system utilizing thermal and electrical storage and forecast services2017Conference paper (Refereed)
  • 4.
    Psimopoulos, Emmanouil
    et al.
    Dalarna University, School of Technology and Business Studies, Energy Technology. Uppsala University.
    Bee, Elena
    University of Trento, Trento, Italy.
    Luthander, Rasmus
    Uppsala University.
    Bales, Chris
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Smart control strategy for PV and heat pump system utilizing thermal and electrical storage and forecast services2017Conference paper (Refereed)
    Abstract [en]

    In this study, a detailed model of a single-family house with exhaust air heat pump, PV system and energy hub developed in the simulation software TRNSYS 17 is used to evaluate energy management algorithms that utilize weather and electricity price forecasts. A system with independent PV and heat pump is used as a base case. The proposed control strategy is applied to the base case to optimize the available PV electricity production using short-term weather and electricity price forecasts. The three smart and predictive control algorithms were developed with the scope to minimize final energy by the use of the thermal storage of the building, the hot water tank and electrical storage. The results show reduction of the final energy of 26.4%, increase of the self-consumption to 60% and decrease of the annual cost of 15% when using the forecast services in combination with thermal and electrical storage compared to the base case.

  • 5.
    Psimopoulos, Emmanouil
    et al.
    Dalarna University, School of Technology and Business Studies, Energy Technology. Uppsala University.
    Bee, Elena
    Widén, Joakim
    Bales, Chris
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Techno-economic analysis of control algorithms for an exhaust air heat pump system for detached houses coupled to a photovoltaic system2019In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 249, p. 355-367Article in journal (Refereed)
    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.

  • 6.
    Psimopoulos, Emmanouil
    et al.
    Dalarna University, School of Technology and Business Studies, Energy Technology. Uppsala University.
    Johari, Fatemeh
    Uppsala University.
    Widén, Joakim
    Uppsala University.
    Bales, Chris
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Impact of boundary conditions on the performance enhancement of advanced control strategies for a residential building with a heat pump and PV system with energy storage2019In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118Article in journal (Refereed)
  • 7.
    Psimopoulos, Emmanouil
    et al.
    Dalarna University, School of Technology and Business Studies, Energy Technology. Uppsala universitet.
    Leppin, Lorenz
    Luthander, Rasmus
    Uppsala universitet, Fasta tillståndets fysik.
    Bales, Chris
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Control algorithms for PV and Heat Pump system using thermal and electrical storage2016In: Proceedings of the 11th ISES EuroSun 2016 International Conference on Solar Energy for Buildings and Industry, Palma de Mallorca, Spain, 11-14 October 2016, International Solar Energy Society , 2016Conference paper (Other academic)
    Abstract [en]

    In this study a detailed model of a single-family house with an exhaust air heat pump and photovoltaic system is developed in the simulation software TRNSYS. The model is used to evaluate three control algorithms using thermal and electrical storage in terms of final energy, solar fraction, self-consumption and seasonal performance factor. The algorithms are tested and compared with respect to energetic improvement for 1) use of the heat pump plus storage tank for domestic hot water and space heating, 2) use of the electrical storage in batteries and 3) use of both electrical and thermal storage. Results show the highest increase of self-consumption to 50.5%, solar fraction to 40.6% and final energy decrease to 6923 kWh by implementing the third algorithm in a system with 9.36 kW PV capacity and battery storage of 10.8 kWh. The use of electrical energy storage has higher positive impact compared to the thermal storage with the settings and component sizes used. The combined use of thermal storage and batteries leads to final energy savings that are nearly the same as the combined savings of thermal storage and batteries separately, showing that they are mostly independent of one another for the settings of this study.

  • 8. Sotnikov, A.
    et al.
    Nielsen, C. K.
    Bales, Chris
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Dalenbäck, J. -O
    Andersen, Martin
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Psimopoulos, Emmanouil
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Simulations of a Solar-Assisted Block Heating System2017Conference paper (Refereed)
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