# Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions

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## Abstract

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## 1. Introduction

## 2. System Simulation Model

#### 2.1. Target System

#### 2.2. Control Mode Simulation Model

## 3. Control Simulation Results

#### 3.1. Comparison of Simulation and Experiment

#### 3.2. Winter Simulation Results

## 4. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## Nomenclature

${A}_{p}$ | Heat transfer area of PCM (m^{2}) |

${C}_{p,w}$ | Specific heat of water (kJ/kg·K) |

${C}_{p,p}$ | Specific heat of PCM (kJ/kg·K) |

${C}_{pc,l}$ | Liquid state cooling PCM specific heat (kJ/kg·K) |

${C}_{ph,l}$ | Liquid state heating PCM specific heat (kJ/kg·K) |

${C}_{ph,s}$ | Solid state heating PCM specific heat (kJ/kg·K) |

$COP$ | Coefficient of performance (-) |

$CO{P}_{n}$ | Normalized coefficient of performance (-) |

$Cos{t}_{tot}$ | Total electricity cost (₩) |

$Cos{t}_{d}$ | Daytime electricity cost (₩) |

$Cos{t}_{m}$ | Nighttime electricity cost (₩) |

$D$ | PCM pack interval inside the thermal storage tank (m) |

${F}_{PLR}$ | Correction factor for part load power consumption (-) |

${h}_{fg}$ | Enthalpy of water for latent processes (kJ/kg) |

${h}_{SPF}$ | Convection heat transfer coefficient according to SPF (kW/m^{2}·K) |

${h}_{w}$ | Convection heat transfer coefficient of water (-) |

$i$ | Time step index (-) |

$j$ | Position step index (-) |

$k$ | Position step index (-) |

${k}_{w}$ | Conduction heat transfer coefficient of water (-) |

$L$ | Distance from the top to the control volume in the height direction (m) |

${M}_{pc}$ | Mass of cooling PCM (kg) |

${M}_{ph}$ | Mass of heating PCM (kg) |

${\dot{m}}_{w}$ | Mass flow rate of water (kg/s) |

${M}_{w}$ | Mass of water (kg) |

${M}_{SPF}$ | Weight of solidified PCM (kg) |

$\mu $ | Viscosity coefficient of water (N·s/m^{2}) |

$Nu$ | Nusselt number, $Nu={h}_{w}D/{k}_{w}$ (-) |

$PLR$ | Part load ratio (-) |

$Pr$ | Prandtl number, $Pr={C}_{p,w}\mu /{k}_{w}$ (-) |

$\dot{Q}$ | Heat capacity (kW) |

${Q}_{p,lat}$ | Total latent heat capacity of PCM (kJ) |

${Q}_{p,sen}$ | Total sensible heat capacity of PCM (kJ) |

$\dot{{Q}_{R}}$ | Reference load capacity (kW) |

$\dot{{Q}_{F}}$ | Full-load capacity (kW) |

${\dot{Q}}_{ht}$ | Capacity of heat pump (kW) |

${\dot{Q}}_{ht,ful}$ | Full-load capacity of heat pump (kW) |

${\dot{Q}}_{ht,opt}$ | Optimum capacity of heat pump (kW) |

${\dot{Q}}_{load}$ | Load of the building (kW) |

${Q}_{load}$ | Total load of the building (kJ) |

${\dot{Q}}_{st}$ | Capacity of thermal storage (kW) |

${Q}_{st}$ | Total accumulated Capacity of thermal storage (kJ) |

${\dot{Q}}_{st,ref}$ | Reference capacity of thermal storage (kW) |

${Q}_{w,sen}$ | Total sensible heat capacity of water (kJ) |

${Q}_{p,sen}$ | Total sensible heat capacity of PCM (kJ) |

${Q}_{p,lat}$ | Total latent heat capacity of PCM (kJ) |

$R$ | Variable of minimum cost (₩) |

$Re$ | Reynolds number, $Re=VD/v$ (-) |

$SPF$ | Solid packing factor (%) |

${T}_{c}$ | Outlet temperature of water for heat pump model (°C) |

${T}_{e}$ | Outdoor temperature for heat pump model (°C) |

${T}_{w}$ | Water temperature at control volume (°C) |

${T}_{p}$ | PCM temperature at control volume (°C) |

${T}_{pc}$ | Cooling PCM temperature at control volume (°C) |

${T}_{pc,l}$ | Liquid state Cooling PCM temperature (°C) |

${T}_{ph}$ | Heating PCM temperature at control volume (°C) |

${T}_{in}$ | Inlet water temperature at control volume (°C) |

${T}_{out}$ | Outlet water temperature at control volume (°C) |

${T}_{ht,i}$ | Inlet water temperature of heat pump (°C) |

${T}_{ht,o}$ | Outlet water temperature of heat pump (°C) |

$\xb7{T}_{st}$ | Temperature change of thermal storage tank during discharging process (°C) |

${t}_{1}$ | Daytime operating time (-) |

${t}_{2}$ | Nighttime operating time (-) |

${U}_{s}$ | Overall heat transfer coefficient of the sensible process (kW/m^{2}·K) |

${U}_{l}$ | Overall heat transfer coefficient of the latent process (kW/m^{2}·K) |

$v$ | Kinematic viscosity of water in the control volume (m/s) |

$V$ | Flow rate of water in the control volume (m/s) |

${V}_{w,cv}$ | Volume of water at control volume (m^{3}) |

${V}_{p,cv}$ | Volume of PCM at control volume (m^{3}) |

$\dot{W}$ | Power consumption (kW) |

$\dot{{W}_{R}}$ | Reference power consumption (kW) |

$\dot{{W}_{F}}$ | Full-load power consumption (kW) |

${W}_{p}$ | Predicted power consumption (-) |

${x}_{st}$ | Normalized accumulated heat capacity (-) |

${\rho}_{w}$ | Density of water (kg/m^{3}) |

${\rho}_{p}$ | Density of PCM (kg/m^{3}) |

## References

- Kim, M.-H.; Lee, D.-W.; Yun, R.; Heo, J. Operational Energy Saving Potential of Thermal Effluent Source Heat Pump System for Greenhouse Heating in Jeju. Int. J. Air-Cond. Refrig.
**2017**, 25, 1750018. [Google Scholar] [CrossRef] - Amoabeng, K.O.; Choi, J.M. Review on Cooling System Energy Consumption in Internet Data Centers. Int. J. Air-Cond. Refrig.
**2016**, 24, 1630008. [Google Scholar] [CrossRef] - Baeten, B.; Rogiers, F.; Helsen, L. Reduction of heat pump induced peak electricity use and required generation capacity through thermal energy storage and demand response. Appl. Energy
**2017**, 195, 184–195. [Google Scholar] [CrossRef] - Miara, M.; Günther, D.; Langner, R.; Helmling, S. The outcomes and lessons learned from the wide-scale monitoring campaign of heat pumps in family dwellings in Germany. In Proceedings of the 11th IEA Heat Pump Conference, Montreal, QC, Canada, 12–16 May 2014. [Google Scholar]
- Air Conditioning and Heating Facility with Thermal Energy Storage, Midnight-Electricity Equipment Technical Specifications, Korea Electric Power Corporation. Available online: https://home.kepco.co.kr/kepco/cmmn/fms/FileDown.do?atchFileId=FILE_000000021208041&fileSn=0 (accessed on 29 November 2017).
- Mavrigiannaki, A.; Ampatzib, E. Latent heat storage in building elements: A systematic review on properties and contextual performance factors. Renew. Sustain. Energy Rev.
**2016**, 60, 852–866. [Google Scholar] [CrossRef] - Kim, K.-H.; Yoon, Y.-H.; Kim, Y.-K. Experiment on the charging and discharging processes of a closed ice-thermal-energy-storage system. J. Energy Eng.
**2007**, 16, 164–169. [Google Scholar] - Yang, L.; Zhang, X.-S. Performance of a new packed bed using stratified phase change capsules. Int. J. Low-Carbon Technol.
**2012**, 7, 208–214. [Google Scholar] [CrossRef] - Lee, Y.T.; Chung, J.D.; Park, H.J. A numerical study on the discharging performance of a packing module in a thermal storage tank. Trans. Korean Soc. Mech. Eng. B
**2015**, 39, 625–631. [Google Scholar] [CrossRef] - Miara, M.; Günther, D.; Langner, R.; Helmling, S.; Wapler, J. 10 years of heat pumps monitoring in Germany. Outcomes of several monitoring campaigns. From low-energy houses to un-retrofitted single-family dwellings. In Proceedings of the 12th IEA Heat Pump Conference, Rotterdam, The Netherlands, 15–18 May 2017. [Google Scholar]
- Carey, C.W.; Mitchell, J.W.; Beckman, W.A. The Control of Ice-Storage Systems. ASHRAE Trans.
**1995**, 101, 1345–1352. [Google Scholar] - Ahn, Y.H.; Kang, B.H.; Kim, S.; Lee, D.Y. The operation characteristics and cost analysis of an ice thermal storage system. Korean J. Air-Cond. Refrig. Eng.
**2005**, 17, 156–164. [Google Scholar] - Spethmann, D.H. Application considerations in optimal control of cool storage. ASHRAE Trans.
**1993**, 99, 1009–1015. [Google Scholar] - Braun, J.E. A comparison of chiller-priority, storage priority, and optimal control of an ice-storage system. ASHRAE Trans.
**1992**, 98, 893–902. [Google Scholar] - Kintner-Meyer, M.; Emery, A.F. Cost optimal analysis and load shifting potentials of cold storage equipment. ASHRAE Trans.
**1995**, 101, 539–548. [Google Scholar] - Jung, S.H.; Lee, D.Y.; Kang, B.H.; Kim, W.S. Control strategy for economic operation of an ice-storage system considering cooling load variation. Korean J. Air-Cond. Refrig. Eng.
**1999**, 12, 140–149. [Google Scholar] - Chen, H.-J.; Wang, D.W.P.; Chen, S.L. Optimization of an ice-storage air conditioning system using dynamic programming method. Appl. Therm. Eng.
**2005**, 25, 461–472. [Google Scholar] [CrossRef] - Chang, Y.C. An Outstanding Method for Saving Energy-Optimal Chiller Operation. IEEE Trans. Energy Convers.
**2006**, 21, 527–532. [Google Scholar] [CrossRef] - Henze, G.P.; Biffar, B.; Kohn, D.; Becker, M.P. Optimal design and operation of a thermal storage system for a chilled water plant serving pharmaceutical buildings. Energy Build.
**2008**, 40, 1004–1019. [Google Scholar] [CrossRef] - Kirk, H.D.; Braun, J.E. Development and evaluation of a rule-based control strategy for ice storage system. HVAC&R Res.
**1996**, 2, 312–334. [Google Scholar] - Lee, K.H.; Choi, B.Y.; Lee, S.R. An evaluation of chiller control strategy in ice storage system for cost-saving operation. Korean J. Air-Cond. Refrig. Eng.
**2008**, 20, 97–105. [Google Scholar] - Ice Storage Systems. One of the Systems Series, A Trane Air Conditioning Clinic. TRANE. Available online: http://www.tga-optimierung.de/kaeltetechnik/wp-content/uploads/sites/2/2015/07/Ice-Storage-Systems.pdf (accessed on 24 August 2012).
- Rachedi, K.; Korti, A.I.N. Computational investigation of thermal interaction phenomena between two adjacent spheres filed with different Phase Change Materials (PCMs). Int. J. Air-Cond. Refrig.
**2017**, 25, 1750033. [Google Scholar] [CrossRef] - Felix Regin, A.; Solanki, S.C.; Saini, J.S. An analysis of a packed bed latent heat thermal energy storage system using PCM capsules: Numerical investigation. Renew. Energy
**2009**, 34, 1765–1773. [Google Scholar] [CrossRef] - Lee, C.S. A Study on Optimal Control Methods for Cooling of Heat Pump and Latent Heat Storage System. Ph.D. Thesis, Department of Mechanical Engineering, Kookmin University, Seoul, Korea, 2015. [Google Scholar]
- MATLAB. Mathworks 2016. Available online: https://www.mathworks.com/company/events/conferences.html (accessed on 21 May 2016).
- Kim, D.J.; Jung, W.S.; Chang, Y.S.; Kang, B.H. Heating performance analysis of the region control method for heat pump with thermal storage system. J. Mech. Sci. Technol.
**2017**, 31, 5569–5579. [Google Scholar] [CrossRef] - Arnold, D. Dynamic Simulation of Encapsulated Ice Tanks: Part I—The Model. ASHRAE Trans.
**1990**, 96, 1103–1110. [Google Scholar] - Salvalai, G. Implementation and validation of simplified heat pump model in IDA-ICE energy simulation environment. Energy Build.
**2012**, 49, 132–141. [Google Scholar] [CrossRef] - Cuong, L.N.; Oh, J.-T. The Comparison of Experiment Results and CFD Simulation in the Heat Pump System Using Thermobank and Two-Phase Ejector for Heating Room and Cold Storage. Int. J. Air-Cond. Refrig.
**2016**, 24, 1650004. [Google Scholar] [CrossRef] - Byrne, P.; Miriel, J.; Lenat, Y. Modelling and simulation of a heat pump for simultaneous heating and cooling. Build. Simul.
**2012**, 5, 219–232. [Google Scholar] [CrossRef] [Green Version] - Seok, H.T.; Kim, K.W. Thermal performance evaluation of design parameters and development of load prediction equations of office buildings. Korean J. Air-Cond. Refrig. Eng.
**2001**, 13, 914–921. [Google Scholar] - KSES. Korean Standard Weather Data; The Korean Solar Energy Society: Seoul, Korea, 2013. [Google Scholar]
- Korea Electric Power Corporation. KEPCO Selective Terms of Supply; KEPCO: Naju, Korea, 2013. [Google Scholar]

**Figure 2.**PCM (Phase change material) samples and thermal storage tank schematic for heating system: (

**a**) picture of packed PCMs for cooling and heating (left: cooling; right: heating); and (

**b**) schematic of thermal storage tank.

**Figure 4.**Comparison between the experiment and the simulation results of heat charging process and heat discharging process for 10 h.

**Figure 5.**Comparison between the experiment and the simulation results: (

**a**) comparison of time step in 5 h instant of charging process; and (

**b**) comparison of control volume layers in 5 h instant of charging process.

**Figure 7.**Performance of heat pump according to PLR (Part load ratio): (

**a**) correction factor models for power consumption of heat pump under part load operation; and (

**b**) the normalized COP (Coefficient of performance) of heat pump according to part load ratio.

**Figure 9.**Conceptual diagram of conventional control methods: (

**a**) thermal storage priority method; and (

**b**) heat pump priority method.

**Figure 14.**Analysis of heating load and heating capacity: (

**a**) percentage of winter season and average outdoor temperature by each heating load; and (

**b**) heating capacity rate due to normalized loads with over 80% load.

**Figure 15.**Performance analysis by control method: (

**a**) the normalized COP by control mode according to capacity ratio of heat pump; and (

**b**) the normalized COP by control mode according to heating load rate.

**Figure 16.**Power consumption and electricity cost analysis by control method: (

**a**) normalized power consumption by thermal storage priority method according to load size; and (

**b**) normalized electricity cost by thermal storage priority method according to load size.

Parameter | Specification | |
---|---|---|

Type | Heating | Cooling |

Thermal Conductivity of liquid (W/m·K) | 0.167 | 0.136 |

Thermal Conductivity of solid (W/m·K) | 0.346 | 0.307 |

Average phase change temperature (°C) | 52 | 4 |

Heat of fusion (kJ/kg) | 196.87 | 252.30 |

Specific heat of liquid (kJ/kg·K) | 1.97 | 2.07 |

Specific heat of solid (kJ/kg·K) | 2.30 | 2.32 |

Size (mm) | 17.3 (W) × 250 (L) × 310 (H) | |

Pack weight (kg) | 1 |

Parameter | Specification | |
---|---|---|

Type | Heating | Cooling |

Packed PCM (EA) | 147 | 1197 |

Latent thermal storage energy (kJ) | 28,940 | 302,000 |

Total thermal storage energy (kJ) | 288,000 | 483,000 |

Operating temperature range (°C) | 40–55 | 2–12 |

Size (mm) | 1750 (W) × 2000 (L) × 2000 (H) | |

Volume (m^{3}) | 5.616 |

Coefficient | ${\mathit{a}}_{\mathbf{1}}$ | ${\mathit{a}}_{\mathbf{2}}$ | ${\mathit{a}}_{\mathbf{3}}$ | ${\mathit{a}}_{\mathbf{4}}$ | ${\mathit{a}}_{\mathbf{5}}$ |
---|---|---|---|---|---|

Charging | 51 | 0.5 | −154 | 235 | −121 |

Discharging | 5 | 141 | −300 | 370 | −143 |

Parameter | Condition Range |
---|---|

Tc (°C) | 55, 52, 48, 43, 40 |

Te (°C) | 5, 1, −5, −11, −15 |

Load (kW) | 10, 25, 50 ,75, 100 |

Water flow rate (lpm) | 7 |

Coefficient | Parameter | |||||
---|---|---|---|---|---|---|

Heat capacity | ${b}_{1}$ | ${b}_{2}$ | ${b}_{3}$ | ${b}_{4}$ | ${b}_{5}$ | ${b}_{6}$ |

25.59 | −0.0788 | −0.4708 | −0.0058 | 0.0030 | 0.0029 | |

Power consumption | ${c}_{1}$ | ${c}_{2}$ | ${c}_{3}$ | ${c}_{4}$ | ${c}_{5}$ | ${c}_{6}$ |

1.2850 | −0.0622 | 0.0591 | −0.0003 | −0.0001 | 0.0001 | |

Factor for part load power consumption | ${d}_{1}$ | ${d}_{2}$ | ${d}_{3}$ | |||

0.7558 | −0.2237 | 0.4578 |

**Table 6.**Zone electric rate based on daytime and nighttime electric power rate by KEPCO (Korea Electric Power Corporation).

Parameter | Time | Electricity Rate |
---|---|---|

Day time—r(${t}_{1}$) | 08:00–22:00 | 7.69 (¢/kWh) |

Night time—r(${t}_{2}$) | 22:00–08:22 | 5.42 (¢/kWh) |

Region 1 | ${\dot{Q}}_{load}<{\dot{Q}}_{st,ref}$ |

Region 2 | ${\dot{Q}}_{st,ref}<{\dot{Q}}_{load}<{\dot{Q}}_{hp,opt}$ |

Region 3 | ${\dot{Q}}_{hp,opt}<{\dot{Q}}_{load}<{\dot{Q}}_{st,ref}+{\dot{Q}}_{hp,opt}$ |

Region 4 | ${\dot{Q}}_{st,ref}+{\dot{Q}}_{hp,opt}<{\dot{Q}}_{load}<{\dot{Q}}_{st,ref}+{\dot{Q}}_{hp,ful}$ |

Region 5 | ${\dot{Q}}_{st,ref}+{\dot{Q}}_{hp,ful}<{\dot{Q}}_{load}$ |

**Table 8.**Comparison of simulation results with experiments according to control strategies for various load conditions.

Load | Performance | Experiment | Simulation | |||||
---|---|---|---|---|---|---|---|---|

Heat Pump Priority | Thermal Storage Priority | Region Control | Heat Pump Priority | Thermal Storage Priority | Region Control | |||

100% | Heating capacity | Heat pump | 0.65 | 0.61 | 0.62 | 0.62 | 0.60 | 0.61 |

Thermal storage | 0.35 | 0.39 | 0.38 | 0.38 | 0.40 | 0.39 | ||

Heat pump power consumption | Day | 0.6 | 0.57 | 0.57 | 0.56 | 0.57 | 0.57 | |

Night | 0.39 | 0.43 | 0.41 | 0.41 | 0.43 | 0.41 | ||

Total | 0.99 | 1.00 ^{1} | 0.98 | 0.97 | 1.00 ^{1} | 0.98 | ||

80% | Heating capacity | Heat pump | 0.62 | 0.43 | 0.49 | 0.6 | 0.44 | 0.48 |

Thermal storage | 0.19 | 0.38 | 0.32 | 0.21 | 0.37 | 0.33 | ||

Heat pump power consumption | Day | 0.49 | 0.37 | 0.39 | 0.46 | 0.38 | 0.39 | |

Night | 0.15 | 0.36 | 0.30 | 0.16 | 0.35 | 0.30 | ||

Total | 0.64 | 0.73 | 0.69 | 0.62 | 0.73 | 0.69 | ||

60% | Heating capacity | Heat pump | 0.62 | 0.26 | 0.39 | 0.61 | 0.23 | 0.41 |

Thermal storage | 0 | 0.36 | 0.23 | 0 | 0.38 | 0.20 | ||

Heat pump power consumption | Day | 0.45 | 0.25 | 0.32 | 0.48 | 0.24 | 0.33 | |

Night | 0 | 0.32 | 0.16 | 0 | 0.35 | 0.17 | ||

Total | 0.45 | 0.57 | 0.48 | 0.48 | 0.59 | 0.50 |

^{1}Non-dimensional reference; thermal storage priority method when the heating load 100%.

Parameter | Heat Pump Priority | Thermal Storage Priority | Region Control | Optimal Control |
---|---|---|---|---|

Day power consumption | 0.77 | 0.47 | 0.47 | 0.49 |

Night power consumption | 0.19 | 0.53 | 0.43 | 0.39 |

Total power consumption | 0.96 | 1.00 ^{2} | 0.90 | 0.88 |

Electricity cost | 1.08 | 1.00 ^{2} | 0.92 | 0.91 |

^{2}Non-dimensional reference; thermal storage priority method when the winter season.

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Jung, W.; Kim, D.; Kang, B.H.; Chang, Y.S.
Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions. *Energies* **2017**, *10*, 2020.
https://doi.org/10.3390/en10122020

**AMA Style**

Jung W, Kim D, Kang BH, Chang YS.
Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions. *Energies*. 2017; 10(12):2020.
https://doi.org/10.3390/en10122020

**Chicago/Turabian Style**

Jung, Wangsik, Dongjun Kim, Byung Ha Kang, and Young Soo Chang.
2017. "Investigation of Heat Pump Operation Strategies with Thermal Storage in Heating Conditions" *Energies* 10, no. 12: 2020.
https://doi.org/10.3390/en10122020