Ground-coupled heat pumps: Part 1 – Literature review and research challenges in modeling and optimal control

Atam, Ercan; Helsen, Lieve

doi:10.1016/j.rser.2015.10.007

Cited by 103 publications

(42 citation statements)

References 38 publications

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“…From these works it has emerged that Model Predictive Control (MPC) algorithms are an effective method to improve building energy efficiency. In particular, the reviews on MPC can be grouped in those focused on optimal-intelligent control methods adopted for a single HVAC component (e.g., ventilation systems [35], ground-coupled heat pumps [36], thermal storages [37], window control [38], etc.) or those that consider the control strategies for the energy management of the entire building.…”

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confidence: 99%

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

et al. 2018

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In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities for enhancing energy efficiency in the operation of Heating Ventilation and Air Conditioning (HVAC) systems because of its ability to consider constraints, prediction of disturbances and multiple conflicting objectives, such as indoor thermal comfort and building energy demand. Despite the application of MPC algorithms in building control has been thoroughly investigated in various works, a unified framework that fully describes and formulates the implementation is still lacking. Firstly, this work introduces a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control. Secondly the main scope of this paper is to define the MPC formulation framework and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management. The potential benefits of the application of MPC in improving energy efficiency in buildings were highlighted.

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confidence: 99%

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

et al. 2018

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“…Some of them can be listed as follows. (i) developing a control-oriented model and using this model to design a nonlinear model predictive control (NMPC) system for frost prevention; (ii) determining the optimal number and distribution of hot air blowers; (iii) development of optimised, rule-based controllers from NMPC-type controllers through machine learning; (iv) consideration of synergistic effects by using hot air blowers and other alternatives, such as water sprayers around the perimeter of the orchard, and mulching or coverage of the fruit trees, which could significantly reduce the required minimum frost prevention energy from the use of hot air blowers; (v) development of different active frost prevention systems, including renewable energy sources and their economic feasibility analyses: for example, photovoltaics systems [25] and ground-coupled heat pumps [26][27][28] to fully or partially heat/warm the hot air to be blown. Funding: The first author would like to thank TÜBİTAK for funding (through the TÜBİTAK 1512 program) his project entitled "Development of tools for solar-energy assisted frost prevention systems in large-scale orchards.…”

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confidence: 99%

Thermofluid Modelling of Large-Scale Orchards for Optimal Design and Control of Active Frost Prevention Systems

2020

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Accurate modelling and simulation of temperature dynamics in large-scale orchards is important in many aspects, including: (i) for the calculation of minimum energy required to be used in optimal design of active frost prevention energy systems (fully renewable or partially renewable) to prevent freezing of fruit flowers, buds, or leaves; (ii) for testing frost prevention control systems before real-implementation which regulate active heating systems inside orchards targeted to prevent frost. To that end, in this study, first, a novel and sophisticated parametric computational thermofluid dynamics (CTFD) model for orchard air thermal dynamics for different orchard parameters (such as fruit type, climate, number of trees, their sizes, and distance between them) and boundary/initial conditions was developed and validated with field data from the literature. Next, the use of the developed parametric CTFD model was demonstrated through a case study to calculate the minimal thermal energy required to prevent frost under different frost levels in a test Prunus armeniaca orchard located in Malatya, Turkey, which is the world capital for dry apricot production.

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“…Some of them can be listed as follows. (i) Developing a control-oriented model and using this model to apply NMPC for frost prevention; (ii) Determining the optimal number and distribution of hot air blowers; (iii) Development of optimized rule-based controllers from NMPC-type controllers through machine learning; (iv) In addition to hot air blowers, inclusion of water sprayers around perimeter of the orchard during frost periods; (v) Partial block of wind via a mobile vertical covering system, (vi) Economic feasibility analysis of alternative energy storage choices instead of batteries (such as energy storage via compressed air) or green energy choices instead of PV (for example, ground-coupled heat pumps [16], [17]). All these approaches have potential in lowering the investment cost and payback time significantly, and they will studied by the authors in the future.…”

Section: Directionsmentioning

confidence: 99%

Solar energy-assisted frost prevention in horticulture applications: integrated framework and parametric CFD modeling

Atam¹,

Hong²

2018

Preprint

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Prevention of frost in horticulture is important, but challenging, and its realization,especially using green-energy sources, will have a huge societal impact.In this paper, first we suggest an integrated solarphotovoltaics (PV)-assisted framework where solar energy will be used as a secondary application for frostprevention (the primary application is electricity production for grid). Optimal design and operation ofthe suggested integrated system require detailed thermal modeling of air dynamics in the orchard,integrated system optimization and control tasks. Second, in this paperwe address the first task above: development of a novel, sophisticated parametric computational fluid dynamics (CFD)model for orchard air thermal dynamics for different orchard parameters (such as fruit type, climate, the number of trees,their sizes, distance between them, etc.) and boundary/initial conditions.Finally, the use of developed parametric CFD model is demonstrated through a case study to calculate the minimal thermalenergy required to prevent frost under different frost levels in a test apricot orchard located in Malatya, Turkey, which isthe world capital for dry apricot production.

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Ground-coupled heat pumps: Part 1 – Literature review and research challenges in modeling and optimal control

Cited by 103 publications

References 38 publications

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

Thermofluid Modelling of Large-Scale Orchards for Optimal Design and Control of Active Frost Prevention Systems

Solar energy-assisted frost prevention in horticulture applications: integrated framework and parametric CFD modeling

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