A comparison of thermal energy storage models for building energy system optimization

Schütz, Thomas; Streblow, Rita; Müller, Dirk

doi:10.1016/j.enbuild.2015.02.031

Cited by 53 publications

(25 citation statements)

References 24 publications

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“…Implications of this commonly used modeling approach and alternative approaches are discussed in detail in References [2,30]. Nevertheless, this kind of storage model makes it possible to store and restore heat on different temperature levels, since only heat flows are captured.…”

Section: Power To Heatmentioning

confidence: 99%

Integration of Flow Temperatures in Unit Commitment Models of Future District Heating Systems

et al. 2019

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The transformation of heat supply structures towards 4th generation district heating (4GDH) involves lower supply temperatures and a shift in technology. In order to assess the economic viability of the respective systems, adequate unit commitment models are needed. However, maintaining the formal requirements, while reducing the computational efforts of these models, often includes simplifications such as the assumption of constant supply temperatures. This study investigates the effect of introducing varying supply temperatures in mixed-integer linear programming models. Based on a case study of a municipal district heating system, how the temperature integration approach affects unit commitment and technology assessment for different temperature levels and scenarios is analyzed. In particular, three supply temperature levels are investigated with both variable and constant temperatures in two scenarios. Results indicate that lower flow temperature levels in the heating network tend to favor internal combustion engines, combined cycle power plants, and heat pumps; while back pressure steam turbines, peak loads, and electric boilers show declining operating hours. Furthermore, the effect of varying versus constant temperatures at the same temperature level is rather small, at least as long as technical restrictions do not come into play. Finally, it is found that the effect of changing temperature on a technology assessment is comparably small as opposed to adaptions in the regulatory framework.

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Section: Power To Heatmentioning

confidence: 99%

Integration of Flow Temperatures in Unit Commitment Models of Future District Heating Systems

et al. 2019

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“…Another modelling decision that can influence the results is the capacity model implemented for the thermal energy storage. It has been shown that the capacity model can contribute to approximately 7% underestimation of operational cost relative to the stratified model for a case study of monovalent residential heating system with combined heat and power (CHP) [40]. The same study also describes that the increase in accuracy with the stratified model comes with higher computational cost.…”

Section: Study Limitationsmentioning

confidence: 98%

An optimisation framework for thermal energy storage integration in a residential heat pump heating system

2017

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Domestic heating has a large share in the UK total energy consumption and significant contribution to the greenhouse gas emissions since it is mainly fulfilled by fossil fuels. Therefore, decarbonising the heating system is essential and an option to achieve this is by heating system electrification through heat pumps (HP) installation in combination with renewable power generation. Potential increase in performance and flexibility can be achieved by pairing HP with thermal energy storage (TES), which allows the shifting of heat demand to off peak periods or periods with surplus renewable electricity. We present a design and operational optimisation model which is able to assess the performance of HP-TES relative to conventional heating system. The optimisation is performed on a synthetic heat demand model which requires only the annual heat demand, temperature and occupancy profiles. The results show that the equipment and operational cost of a HP system without TES are significantly higher than for a conventional system. However, the integration of TES and time-of-use tariffs reduce the operational cost of the HP systems and in combination with the Renewable Heating Incentive make the HP systems cost competitive with conventional systems. The presented demand model and optimisation procedure will enable the design of low carbon district heating systems which integrate the heating system with the variable renewable electricity supply.

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“…So it is with the energy quality of the recovery heat. In actual fact, the thermal efficiency of micro-cogeneration units is low during start-up period [14]. The outlet water temperature from the unit would violently fluctuate during overheat protection process, which would influence the performance of heat recovery devices.…”

Section: Introductionmentioning

confidence: 99%

Experimental and modeling investigation of an ICE (internal combustion engine) based micro-cogeneration device considering overheat protection controls

Zheng

Zhai

et al. 2016

Energy

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A dynamic simulation model for the micro-cogeneration unit based on internal combustion engine (ICE) is built as a new component on TRNSYS. This model considers dynamic processes including start-up, cool-down, and overheat protection controls. Through an experiment study, the steady and dynamic performances of the unit are presented and analyzed for calibrating the parameters of the dynamic model. Then the model is validated by the experiment data during steady and dynamic processes. The improvement of prediction accuracy of the model by considering dynamic processes is analyzed. The validation results show that the dynamic model can well predict the characteristics of the unit during start-up, cool-down, and overheat protection control processes. The cumulative prediction errors of the dynamic model decrease with the increase of the start-stop interval. By considering the dynamic processes, 5.18% and 3.2% of Qth and ηtotal cumulative prediction errors are decreased respectively when the start-stop interval is 0.5h. The primary energy saving ratio and CO2 emission reduction ratio increases with the increase of the start-stop interval. The start-stop interval for the unit in this paper should be longer than 0.5 h, or the energy consumption of micro-cogeneration unit would be larger than that of conventional system.

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A comparison of thermal energy storage models for building energy system optimization

Cited by 53 publications

References 24 publications

Integration of Flow Temperatures in Unit Commitment Models of Future District Heating Systems

Integration of Flow Temperatures in Unit Commitment Models of Future District Heating Systems

An optimisation framework for thermal energy storage integration in a residential heat pump heating system

Experimental and modeling investigation of an ICE (internal combustion engine) based micro-cogeneration device considering overheat protection controls

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