# Study on the Development of an Optimal Heat Supply Control Algorithm for Group Energy Apartment Buildings According to the Variation of Outdoor Air Temperature

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## Abstract

**:**

## 1. Introduction

_{2}emissions and economical group energy heating system usage through simultaneous heat consumption in industrial estates.

## 2. Analysis of Group Energy Apartment Building Heat Loss

Item | Specifications |
---|---|

Object building | Apartment building |

Number of households | 1473 |

Period | 2008.01.01~2008.12.31 |

Location | Hwaseong city, Gyeonggi-do, Korea |

Heating source | District heating |

#### Experimental Data for Numerical Analysis

**Figure 2.**Annual variation of supply and return water temperatures of group energy primary side (supplier side) of the model apartment.

**Figure 3.**Annual variation of supply and return water temperatures of group energy secondary side (consumer side) of the model apartment.

**Figure 4.**Annual variations of mass flow rates in the transmission and distribution lines of group energy supply system at the model group energy apartment.

_{air}). Consumer side heat loss rate is the rate of heat loss as hot water is supplied from the heat exchanger to individual homes and is returned from the individual homes to the heat exchanger.

**Figure 6.**Annual variation of heat loss rate of distribution line of the model apartment and annual variation of outdoor air temperature.

**Figure 7.**Heat loss rate variation of distribution line at the model apartment with respect to outdoor air temperature.

- Constraint: Supply heat needed in individual homes according to outdoor temperature variation.
- Objective function: Determine supply water temperature and return water temperature that yield the lowest heat loss rate on the consumer side distribution line.

_{s}denotes the supply water temperature, T

_{air}the outdoor temperature, (${\dot{m}}_{S}$) the supply water flow rate, and T

_{R}the return water temperature:

_{s}and (${\dot{m}}_{S}$) that yields the minimal (${\dot{Q}}_{loss}$) in Equation (3) will be demonstrated.

## 3. Analysis of Heat Loss in Heat Distribution Line of Target Group Energy Apartment Building

**Figure 8.**Schematic diagram of optimal heat supply control algorithm that varies the supply water temperature and mass flow rate according to outdoor air temperature.

_{air}is the outdoor temperature. In this study, the indoor temperature is assumed as 22 °C from January to August and 23 °C from September to December. Heat load is a function of the outdoor temperature, as shown in Figure 9.

**Figure 9.**Variation of heating load of the model group energy apartment building according to outdoor air temperature.

_{S}

_{2}

_{i}is the outlet supply water temperature of the heat exchanger in the secondary loop. T

_{S}

_{2}

_{o}is the apartment building entrance supply water temperature, T

_{R}

_{2}

_{i}is apartment building exit return water temperature, and T

_{R}

_{2}

_{o}is heat exchanger entrance return water temperature. The heat loss rate in the heat distribution line the secondary loop is expressed as ${\dot{Q}}_{loss}^{S}$ and the heat loss rate in return water line is expressed as ${\dot{Q}}_{loss}^{R}$.

## 4. Development of Optimal Heat Supply Control Algorithm for Group Energy Secondary Loop

#### 4.1. Heat Exchange Model of Traditional Korean Floor Heating

_{S}

_{2}

_{o}, the mass flow rate as ${\dot{m}}_{h2}$, and the heat capacity of the supply water as C

_{p}. The heat energy of the supply water is transferred indoor through the mortar in the Ondol floor, and then transferred to outdoor through the window, wall, and ceiling. By modeling the Ondol floor as a heat exchanger, T

_{R}

_{2}

_{o}is the inlet temperature of the Ondol heat exchanger, T

_{R}

_{2}

_{i}is the outlet temperature of the Ondol heat exchanger, A

_{Room}is the total heating area of the Ondol hot water line, U

_{Room}is the equivalent heat transfer coefficient between the Ondol pipeline and room air. Based on the heat exchanger theorem, the outlet temperature of the Ondol heat exchanger T

_{R}

_{2}

_{i}is determined from T

_{Room}, T

_{S}

_{2}

_{o}and (U

_{Room}A

_{Room})/( ${\dot{m}}_{h}{C}_{p}$) as shown in the following Equation.

#### 4.2. Heat Loss Rate at the Supply Water Line

_{s}, and U

_{s}is equivalent heat coefficient between the supply water and the wall surrounding the water line. The supply water line is not exposed to air, but is buried underground. Defining T

_{g}as the equivalent temperature of the underground near the supply water line, the supply water line outlet temperature becomes the Ondol inlet temperature T

_{S}

_{2o}and based on the heat exchanger theorem:

#### 4.3. Heat Loss Rate at the Return Water Line

_{R}

_{2i}is the return water line inlet temperature, T

_{R}

_{2o}is the return water line heat exchanger outlet temperature, A

_{R}is the total heating area of return water line, and U

_{R}is the equivalent heating coefficient between the return water line and ground. Based on Equation (10), the heat loss rate at the return water line can be expressed by the following Equation:

_{S}

_{2i}yields:

_{S}A

_{S}, U

_{R}A

_{R}, U

_{Room}A

_{Room}are known, T

_{S}

_{2i}and ${\dot{m}}_{h}$, which supply ${\dot{Q}}_{h}$ while minimizing ${\dot{Q}}_{loss}$, can be found from Equations (12) and (14) by computational simulation. Then, the optimal heat supply control algorithm can be utilized.

## 5. Results and Discussion

_{Room}, as shown in Figure 6, by solving the annual energy consumption with the thermal resistance-capacitance method [21,22] as T

_{Room}is varied. Figure 14 shows the comparison of heat load determined by the thermal resistance-capacitance method and the heat consumption of the target apartment. The two results agree well from March to November, but the heat consumption of the target apartment is slightly higher from the 1st of January to the 28th of February. The result suggests that the room temperature is higher than 22 °C during January and February.

_{S}

_{2i}is changed simultaneously with what, resulting in lower supply water temperature. Thus, the heat loss of in the pipeline is reduced.

_{R}

_{2o}is lower during Spring, Summer, and Autumn compared to that in the original system.

_{S}

_{2i}. Also, the variations of ${\dot{m}}_{h}$ of T

_{S}

_{2i}according to outdoor temperature were obtained.

**Figure 15.**Comparison of experimental and optimized simulation data of supply water temperatures at group energy apartment building during a day for a year.

**Figure 16.**Comparison of experimental and optimized simulation data of temperatures of heat exchanger of group energy apartment building during a day for a year.

**Figure 17.**Comparison of mass flow rate of group energy apartment building with original heating system and that with the optimal heating system for a year.

## 6. Conclusions

- (1)
- This study was based on the apartment building heat consumption data collected in year 2008. Thus, if an accurate database on heat supply and consumption pattern can be obtained, the developed system can accurately predict heat load variations according to outdoor temperature.
- (2)
- Heat load was predicted for group energy apartment buildings. The predictions were compared with experimental data for validation. The results of the heat load prediction method for group energy apartment buildings agreed well with experimental data.
- (3)
- In this study, energy loss was decreased by 10.4% compared to the supply heat by applying the lowest supply water temperature and return water temperature in the optimal heat supply control system.
- (4)
- Heat supply control can be achieved by variable supply mass flow rate control and variation supply water temperature control. To meet consumer heat capacity needs, mass flow rate is varied according to supply water temperature. Low mass flow rate is applied for high supply water temperature, while mass flow rate is increased when the supply water temperature is low.
- (5)
- Primary return water temperature without affecting the indoor temperature. Thus a better utilization of the heat generated from heat generation facility is achievable. The optimal primary side supply water temperature is found when the return water temperature reaches its minimum under the heat control algorithm.
- (6)
- Analysis results of this study can be used to evaluate heat consumption patterns according to outdoor temperature. The analysis results suggest that further research in this area could lead to substantial energy savings in apartment buildings.

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**MDPI and ACS Style**

Byun, J.-K.; Choi, Y.-D.; Shin, J.-K.; Park, M.-H.; Kwak, D.-K.
Study on the Development of an Optimal Heat Supply Control Algorithm for Group Energy Apartment Buildings According to the Variation of Outdoor Air Temperature. *Energies* **2012**, *5*, 1686-1704.
https://doi.org/10.3390/en5051686

**AMA Style**

Byun J-K, Choi Y-D, Shin J-K, Park M-H, Kwak D-K.
Study on the Development of an Optimal Heat Supply Control Algorithm for Group Energy Apartment Buildings According to the Variation of Outdoor Air Temperature. *Energies*. 2012; 5(5):1686-1704.
https://doi.org/10.3390/en5051686

**Chicago/Turabian Style**

Byun, Jae-Ki, Young-Don Choi, Jong-Keun Shin, Myung-Ho Park, and Dong-Kurl Kwak.
2012. "Study on the Development of an Optimal Heat Supply Control Algorithm for Group Energy Apartment Buildings According to the Variation of Outdoor Air Temperature" *Energies* 5, no. 5: 1686-1704.
https://doi.org/10.3390/en5051686