References of "Rafii-Tabrizi, Sasan 50022330"
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See detailOptimal Operation of Nearly Zero Energy Buildings using Mixed Integer Linear Programming
Rafii-Tabrizi, Sasan UL; Hadji-Minaglou, Jean-Régis UL; Scholzen, Frank UL et al

Scientific Conference (2019, September 10)

This paper proposes a deterministic mixed integer linear programming model for the optimal operation of an energy system providing thermal and electrical energy for a residential and commercial nearly ... [more ▼]

This paper proposes a deterministic mixed integer linear programming model for the optimal operation of an energy system providing thermal and electrical energy for a residential and commercial nearly zero energy building. The space heating and space cooling demand of the buildings is simulated using a resistive-capacitive model within a quadratic program respectively. Thermal energy for space heating, space cooling and domestic hot water is buffered in thermal energy storage systems. A dual source heat pump provides thermal energy for space heating and domestic hot water, whereas space cooling is covered by an underground ice storage. The environmental energy sources of the heat pump are ice storage or wind infrared sensitive collectors. The collectors are further used to regenerate the ice storage. Further space heating demands are covered by a combined heat and power unit, which also produces electricity. Photovoltaic panels produce electrical energy which can be stored in a battery storage system. The electrical energy system is capable of selling and buying electricity from the public power grid. A mixed integer linear programming model is developed to minimise the operation cost of the combined commercial and residential nearly zero energy building over a scheduling horizon of 24h. The developed model is tested on two typical days, which are representative for the summer and winter season. Furthermore, it is investigated how external incentives such as varying electricity prices impact the optimal scheduling of the energy system. [less ▲]

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See detailDemand-Side-Management Potentials for Heat-Pumps in Residential Buildings
Bechtel, Steffen UL; Rafii-Tabrizi, Sasan UL; Scholzen, Frank UL et al

Scientific Conference (2019, September 02)

The rollout of volatile renewable energies, within the European Union creates a need for flexibility, which in turn can be solved with Demand-Side-Management. Heat pumps in single-family houses can ... [more ▼]

The rollout of volatile renewable energies, within the European Union creates a need for flexibility, which in turn can be solved with Demand-Side-Management. Heat pumps in single-family houses can contribute by adapting their consumption towards price signals, boosting the integration of renewable energies at the same time. Studies so far only focus on Nearly-Zero-Energy-Buildings neglecting the potential of buildings with lower energy standard. This paper illustrates the load shifting potential of two reference-building types by the means of thermal simulation. Therefore, a designed control unit adapts the operation times of the heat pump according to spot market price signals while simultaneously sustaining indoor comfort. The results show remarkable cost reductions achieved by load shifting for both cases. In addition, the approach of this study facilitates the projection of Demand-Side-Management potentials of whole regions. [less ▲]

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See detailMixed Integer Linear Programming Model for the Optimal Operation of a Dual Source Heat Pump
Rafii-Tabrizi, Sasan UL; Hadji-Minaglou, Jean-Régis UL; Scholzen, Frank UL

Scientific Conference (2019, April 24)

This paper presents a mixed integer linear programming (MILP) model to optimally operate a dual source heat pump (DSHP). The DSHP draws environmental energy from an underground ice storage tank (IST) or ... [more ▼]

This paper presents a mixed integer linear programming (MILP) model to optimally operate a dual source heat pump (DSHP). The DSHP draws environmental energy from an underground ice storage tank (IST) or wind infrared sensitive collectors (WISC). WISC is further used to regenerate the IST. The thermal output of the DSHP is stored in a thermal energy storage (TES). A single-objective optimization approach is applied to minimize the operational cost of the DSHP over a scheduling horizon of 24h. The developed framework is tested on various days, which are representative for each season of the year. Furthermore, it is investigated how variable electricity price market data influence the dynamic behaviour of the DSHP. [less ▲]

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See detailMethodology for Optimally Sizing a Green Electric and Thermal Eco-Village
Rafii-Tabrizi, Sasan UL; Hadji-Minaglou, Jean-Régis UL; Scholzen, Frank UL et al

in Rafii-Tabrizi, Sasan; Hadji-Minaglou, Jean-Régis; Scholzen, Frank (Eds.) et al From Science to Society-New Trends in Environmental Informatics (2017)

This paper presents an energy system for a future eco-village, situated in Luxembourg’s city center, whose thermal and electrical energy needs are covered by renewable resources. Specifically, electrical ... [more ▼]

This paper presents an energy system for a future eco-village, situated in Luxembourg’s city center, whose thermal and electrical energy needs are covered by renewable resources. Specifically, electrical energy is provided by a biogas driven combined heat and power plant, and photovoltaic panels. Lithium-ion accumulators are used for storing the surplus of electrical energy production. Thermal energy needs are mainly covered by a dual source heat pump which draws environmental energy from an ice tank or solar air absorbers. A heat buffer stores heat produced by the combined heat and power plant, a power to heat module and the heat pump. This work focuses on optimally sizing, in terms of power rating, capacity or volume, the energy system components. To this end, a combinatorial simulation-based optimization approach has been developed using MATLAB. The optimal set-up is determined by minimizing the overall cost of the energy system with additional constraints to be respected. Annual needs in thermal and electrical energy, photovoltaic electricity production and the corresponding weather data are based on real data. [less ▲]

Detailed reference viewed: 133 (11 UL)