Research on the Performance of Air Source Heat Pump Auxiliary
Heating Solar Drying System
Dong Huang and Qihang Zheng
Shantou Polytechnic, Shantou, Guangdong Province, 515041, China
Keywords: Energy-Saving Theory, Big Data Algorithms, Drying System, Solar Energy, Eco-Friendly.
Abstract: Solar drying system is an energy-saving and environmentally friendly drying system, but a single solar drying
system cannot solve the defect problem that is easily affected by climatic factors during drying operations,
and the evaluation is unreasonable. Therefore, this paper proposes a big data algorithm, combined with an air-
source heat pump to assist a solar drying system, and conducts innovative performance evaluation and analysis
of the system. First of all, the energy-saving theory is used to evaluate the drying operation, and the indicators
are divided according to the performance evaluation requirements to reduce the performance evaluation in the
interfering factor. Then, the performance evaluation of the innovative solar drying system is formed by the
energy-saving theory, and the performance evaluation results are carried out Comprehensive analysis.
MATLAB simulation shows that under the condition of certain evaluation criteria, the thermal performance,
drying energy efficiency and energy saving of the air-source heat pump assisted heating solar drying system
of big data algorithm are better than those of conventional drying system .
1 INTRODUCTION
Solar drying technology is an effective grain
preservation and drying technology (Bai, Jia, et al.
2023), which has the advantages of low cost, easy
installation and operation, and environmental
protection, and is widely used in rural and agricultural
production. However, traditional solar drying
systems have seasonal and weather limitations
(Ballerini, Di et al. 2023) in order to solve this
problem, this paper will discuss the design and
analysis of auxiliary heating solar drying systems
based on air source heat pump technology.
1.1 Basis of Air Source Heat Pump
Technology
Air source heat pump technology is a new type of
clean energy technology, the principle of which is to
generate high-grade heat through the low-grade heat
in the air (Bellos, Tsimpoukis, et al. 2023), which is
converted through the compression and expansion
process. Specifically, the air-source heat pump
system passes low-temperature air through an
evaporator to obtain low-grade heat; Then through the
compressor, the low-temperature, low-pressure
refrigerant is compressed into high-temperature,
high-pressure gas; The high-temperature gas is then
passed through the condenser to release high-grade
heat, and finally the refrigerant is returned to the
evaporator through the expansion valve to complete a
cycle (Buday, and Buday-Bodi, 2023).
Air-source heat pump technology offers a variety
of advantages, including high energy efficiency,
environmental protection, safety, and ease of
operation. At the same time, it is suitable for many
different application scenarios, including heating, air
conditioning, hot water, etc (Capone, Guelpa, et al.
2023).
1.2 Solar Drying System Design Based
on Air Source Heat Pump
1.2.1 System Structure
Based on air source heat pump technology, the
designed auxiliary heating solar drying system
includes the following main parts:
(1) Solar collector panel: Solar collector panel is
the core component of the solar drying system, and its
function is to convert solar energy into heat energy
and supply the drying system for use [(Chen, Li, et al.
2023).
188
Huang, D. and Zheng, Q.
Research on the Performance of Air Source Heat Pump Auxiliary Heating Solar Drying System.
DOI: 10.5220/0013538100004664
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 1, pages 188-193
ISBN: 978-989-758-763-4
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

(2) Air source heat pump system: The air source
heat pump system includes compressors, evaporators,
condensers, expansion valves and other main
components, which are converted into high-grade
heat through low-grade heat in the air to provide
auxiliary heating for the drying system (Cui, Geng, et
al. 2023).
(3) Thermal energy storage device: The thermal
energy storage device is used to store the heat energy
generated by the air source heat pump so that the
drying system can be used when needed (Duc, Kien,
et al. 2023).
(4) Fan and duct system: The fan and duct system
are used to circulate and transmit the air in the drying
system to ensure the normal operation and effect of
the drying system.
1.2.2 System Performance
The auxiliary heating solar drying system based on air
source heat pump has the following main properties:
(1) High energy efficiency: Air source heat pump
technology has the characteristics of high energy
efficiency, which provides auxiliary heating for the
drying system by converting low-grade heat in the air
into high-grade heat, and greatly improves the energy
efficiency of the system (Fan, Jiang, et al. 2023.
(2) All-weather: The auxiliary heating solar
drying system based on the air source heat pump has
all-weather and can operate under various climatic
conditions, regardless of the season and weather.
(3) Environmental protection: Air source heat
pump technology belongs to clean energy technology,
which has the characteristics of environmental
protection and will not cause pollution to the
environment (Fu, Shi, et al. 2023).
(4) Easy to operate: Air source heat pump
technology has the characteristics of simple operation
and easy maintenance, which can reduce the
operating cost and operation difficulty of the system
(Hasrat, Jensen, et al. 2023).
1.2.3 System Optimization
In order to further improve the performance and
effect of the auxiliary heating solar drying system
based on air source heat pump, the following
optimization measures can be taken:
(1) Optimize the system structure: The energy
efficiency and performance of the system can be
further improved by improving the material and
structure of the solar collector panel, improving the
compressor and refrigerant of the air source heat
pump system (Hou, Zheng, et al. 2023).
(2) Adjust system parameters: Parameters such as
temperature, humidity and air flow of the system can
be adjusted according to the characteristics of dry
materials and climatic conditions to better meet the
drying needs (Hou, Quan, Kim, 2023).
(3) Application of intelligent control technology:
through the application of intelligent control
technology, the system operation process can be
finely controlled and optimized, and the automation
degree and efficiency of the system can be improved
(Hou, Guo, et al. 2023).
The auxiliary heating solar drying system based
on air source heat pump technology has broad
application prospects and market demand, which can
meet the needs of drying technology in rural and
agricultural production fields. Through continuous
optimization and innovation, it is hoped that the
system can be more widely used and promoted, and
contribute to the construction of a resource-saving
society and sustainable development.
Conventional drying operations of heat sources
mainly based on coal and electricity have high energy
consumption and environmental pollution problems.
In order to reduce the energy consumption of drying
operations, clean and efficient drying technology and
equipment are sought. Based on this, some scholars
believe that the big data algorithm combined with the
air-source heat pump auxiliary heat supply is applied
to the analysis of solar drying system. It can
effectively analyze the performance evaluation
scheme and provide corresponding support for
performance evaluation. On this basis, this paper
proposes a big data algorithm to optimize the
performance evaluation scheme and verify the
effectiveness of the model.
2 RELATED CONCEPTS
2.1 Mathematical Description of Big
Data Algorithms
The big data algorithm uses data theory to
optimize the performance evaluation scheme is
i
x
,
and finds the unqualified values in the solar drying
system according to the index parameters in the
performance evaluation In order to and integrate the
performance evaluation scheme is
i
y
, the parameters
is finally judged to the feasibility of the solar drying
system is
() ()
ii
Tx Fd+ , and the calculation is
shown in Equation (1).
Research on the Performance of Air Source Heat Pump Auxiliary Heating Solar Drying System
189

1
() () (, )
n
ii ijii
i
Tx Fd x y τ
=
+= +

(1)
Among them, the judgment of outliers is shown in
Equation (2).
() ()(1 )
i
x
p
xpxp
∈ℵ
=−

(2
)
Big data algorithms combine the advantages of
data theory and use solar drying systems for
quantification, which can improve the performance of
solar drying systems.
Suppose I. The performance evaluation
requirements is
i
x
, the performance evaluation
scheme is
F
, the satisfaction of the performance
evaluation scheme is
γ
, and the performance
evaluation scheme judgment function is
()
i
p
d ,As
shown in Equation (3).
()
ii
p
dxF τ
γ
→
=
 
(3
)
2.2 Selection of Solar Drying System
Scheme
Hypothesis II The solar drying system function is
(, )
ii
Gx y ,and the weight coefficient is
i
d , then, the
performance evaluation requires an unqualified solar
drying system as shown in Equation (4).
1
(, )=w ()
n
ii i i
i
Gx y d u τ
=
−

(4
)
Using assumptions, I and II, a comprehensive
function of system performance can be obtained, as
shown in Equation (5).
1
() (,) (,)
n
iii ijii
i
p
d Gxy xy τ
=
+≤+

(5)
In order to improve the effectiveness of
performance evaluation, all data needs to be
standardized and the results are shown in Equation
(6).
() (,) ()(1 )
iii
x
p
dGxy px p
∈ℵ
+↔ −

(6
)
2.3 Analysis of Performance
Evaluation Schemes
Before the big data algorithm, the performance
evaluation scheme should be analyzed in multiple
dimensions, and the performance evaluation
requirements should be mapped to the solar drying
system data database, and the unqualified
performance evaluation scheme should be eliminated
is
()
i
TP y
, According to Equation (6), the anomaly
evaluation scheme can be proposed, and the results
are shown in Equation (7).
() (,)
()
()(1 )
iii
i
x
p
dGxy
TP y
p
xp
∈ℵ
+
=
−

(7
)
Among them, the parameter is to explain the
scheme is
() (,)
1
()(1 )
iii
x
pd Gx y
px p
∈ℵ
+
≤
−

,needs to be
proposed, otherwise the scheme needs to be
integrated The parameter is
()
i
Th x
, and the result is
shown in Equation (8).
() () (, )
iiii
Th x p d G x y=+
(8
)
The solar drying system conducts comprehensive
analysis and sets the threshold and index weight of
the performance evaluation scheme to ensure the
accuracy of the big data algorithm. Solar drying
system is a system test performance evaluation
scheme, which needs to be innovatively analyzed. If
the solar drying system is in a non-normal
distribution, its parameters is
()
i
unno j , its
performance evaluation scheme will be affected,
reducing the accuracy of the overall performance
evaluation , whose argument is
ax b
τ
+
, the
calculation result is shown in Equation (9).
INCOFT 2025 - International Conference on Futuristic Technology
190

min[ ( ) ( , )]
100%
() (,)
iii
iii
pd Gx y
ax b
pd Gx y
τ
+
+= ×
+


(9
)
The survey performance evaluation scheme
shows that the solar drying system scheme presents a
multi-dimensional distribution, which is in line with
the objective facts. The solar drying system is not
directional, indicating that the solar drying system
scheme has strong randomness, so it is regarded as a
high analytical study. If the stochastic function of the
solar drying system is
()
i
randon j , then the
calculation of equation (9) can be expressed as
formula (10).
min[ ( ) ( , )]
100% ( )
() (, )
iii
i
iii
pd Gx y
a x b randon j
pd Gx y
τ
+
+= × +
+


(10)
Among them, the solar drying system meets the
normal requirements, mainly because the data theory
adjusts the solar drying system, removes duplicate
and irrelevant schemes, and supplements the default
scheme, so that the dynamic correlation of the whole
performance evaluation scheme is strong.
3 OPTIMIZATION STRATEGY
OF AUXILIARY HEATING
SUPPLY OF AIR SOURCE HEAT
PUMP
The big data algorithm adopts the random
optimization strategy for the auxiliary heating supply
of the air source heat pump and adjusts the drying
operation parameters to realize the optimization of the
auxiliary heating supply of the air source heat pump.
The big data algorithm divides the auxiliary heat
supply of air source heat pump into different
performance evaluation levels, and randomly selects
different schemes. In the iterative process, the
performance evaluation schemes with different
performance evaluation levels are optimized and
analyzed. After the optimization analysis is
completed, the performance evaluation level of
different schemes is compared, and the optimal air
source heat pump auxiliary heating solar drying
system is recorded.
4 PRACTICAL CASE OF
AUXILIARY HEATING SUPPLY
OF AIR SOURCE HEAT PUMP
4.1 Performance Evaluation
Presentation
In order to facilitate performance evaluation, this
paper takes the air-source heat pump auxiliary heating
solar drying system under complex conditions as the
research object, with 12 paths and a test time of 12h,
and the performance evaluation of the specific solar
drying system The scheme is shown in Table 1.
Table 1: System Performance Evaluation Requirements
Scope of
application
grade Energy
saving
effect
Innovative
effect
Air collectors I 90.82 89.00
II 89.63 89.90
Centrifugal
fan
I 90.02 90.75
II 91.24 91.60
Air volume
regulating
valve
I 88.84 89.53
II 89.94 89.15
The performance evaluation process in Table 1 is
shown in Figure 1.
Solar collector
Centrifugal
fan
Drying chamber
Air-cooled
condenser
Main engine of air
heat source pump
Centrifugal
fan
Figure 1: Analysis process of auxiliary heat supply by air
source heat pump
Compared with conventional drying systems, the
performance evaluation scheme of big data algorithm
is closer to the actual performance evaluation
requirements. In terms of the rationality and
fluctuation range of the air-source heat pump
auxiliary heating solar drying system, the big data
algorithm is better than the conventional drying
system. Through the change of performance
evaluation scheme in Figure 2, it can be seen that the
Research on the Performance of Air Source Heat Pump Auxiliary Heating Solar Drying System
191

stability of the big data algorithm is better, and the
energy-saving effect is better. Therefore, the
performance evaluation scheme of big data algorithm
has better thermal performance, drying energy
efficiency, energy-saving effect, and summation
stability.
4.2 Auxiliary Heating Situation of Air
Source Heat Pump
The performance evaluation scheme of auxiliary
heating of air source heat pump includes non-
structural information, semi-structural information
and structural information. After the pre-selection of
big data algorithm, a preliminary performance
evaluation scheme of auxiliary heating supply of air
source heat pump is obtained, and the auxiliary
heating of air source heat pump is obtained the
feasibility of the performance evaluation scheme is
analyzed. In order to more accurately verify the
innovative effect of the air-source heat pump
auxiliary heating solar drying system, the solar drying
system with different performance evaluation levels
was selected, and the performance evaluation scheme
is shown in Table 2 shown.
Table 2: The overall situation of the solar drying system
solution
Category Drying energy
efficienc
y
Analysis rate
Solar hot air
subs
y
stem
89.92 90.67
Air source heat
p
um
p
subs
y
ste
m
88.93 88.49
Drying roo
m
89.08 89.57
mean 90.39 90.58
X
6
38.62 37.59
P=3.98
4.3 Energy Saving and Stability of
solar Drying System for
Performance Evaluation
In order to verify the accuracy of the big data
algorithm, the performance evaluation scheme is
compared with the conventional drying system, and
the performance evaluation scheme is shown in
Figure 2.
It can be seen from Figure 2 that the solar drying
system of the big data algorithm is higher than that of
the conventional drying system, but the error rate is
lower, indicating that the performance evaluation of
the big data algorithm is relatively stable the
performance evaluation of conventional drying
systems is uneven. The average performance
evaluation scheme of the above two methods is
shown in Table 3.
Figure 2: Solar drying systems of different methods
Table 3: Comparison of performance evaluation accuracy
of different methods
Algorithm Solar
drying
s
y
stem
Magnitude
of change
Error
Big data
algorithms
88.97 90.68 1.69
Conventional
drying syste
m
82.79 86.94 4.15
P 37.06 38.26 36.73
By Table 3, it can be seen that the conventional
drying system has deficiencies in thermal efficiency
and drying temperature in terms of drying energy
efficiency, and the drying system has undergone
significant changes. High error rate. The general
result of the big data algorithm is higher for solar
drying systems, which are better than conventional
drying systems. At the same time, the solar drying
system of the big data algorithm is greater than 88%,
and the accuracy has not changed significantly. In
Figure 3: Solar drying system for performance evaluation
of big data algorithm
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192

order to further verify the superiority and
effectiveness of the big data algorithm, the general
analysis of the big data algorithm is carried out by
different methods, Figure 3 shown.
By Figure 3, it can be seen that the solar drying
system of the big data algorithm is significantly better
than the conventional drying system, and the reason
is that the big data algorithm combines the air source
heat pump to assist the heating and set up the drying
operation thresholds to reject non-compliant
performance evaluation schemes.
5 CONCLUSIONS
Aiming at the problem that a single solar drying
system is not ideal; this paper proposes a big data
algorithm and optimizes the solar drying system by
combining the auxiliary heat supply of air source heat
pump. At the same time, the performance evaluation
innovation and threshold innovation are analyzed in
depth to construct the drying operation set. The
research shows that compared with the traditional
drying system, the air source heat pump auxiliary
heating solar drying system with big data algorithm
has the advantages of energy saving and
environmental protection and has the characteristics
of high thermal efficiency and low drying
temperature.
ACKNOWLEDGEMENTS
This paper was supported by Shantou Polytechnic and
the project of The Optimization Design of Roller
Dryer Assisted with Solar Heating.2018 Guangdong
Provincial College Youth Innovative Talents Project
"Optimization Design of Solar Energy Auxiliary
Heating to Drum Dryer"
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