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Environmental and Climate Technologies
2021, vol. 25, no. 1, pp. 1284–1292
https://doi.org/10.2478/rtuect-2021-0097
https://content.sciendo.com
1284
©2021 Roberts Kaķis, Ilze Poļikarpova, Ieva Pakere, Dagnija Blumberga.
This is an open access article licensed under the Creative Commons Attribution License (http://creativecommons. org/
license s/by/4.0).
Is It Possible to Obtain More Energy from Solar DH
Field? Interpretation of Solar DH System Data
Roberts KAĶIS1 *, Ilze POĻIKARPOVA2, Ieva PAKERE3, Dagnija BLUMBERGA4
1–4 Riga Technical University, Institute of Energy Systems and Environment, Azenes iela 12/1, Riga,
LV-1050, Latvia
Abstract – Europe has a course to zero emissions by 2050, with a strong emphasis on energy
sector. Due to climatic conditions in Latvia, district heating (DH) plays an important role in
the energy sector. One of the solutions to achieve the set goals in DH is to introduce
emission-free technology. Therefore, the popularity of installation of large-scale solar
collector plants continues to increase in DH in Europe. The first large-scale solar collector
field in the Baltic States was installed in 2019. Solar collector active area is 21 672 m2 with
heat storage water tank 8000 m3. The article shows the first operation results of this system
and evaluates influencing factors. The results of the analysis show that system productivity is
mainly demanded by solar radiation, and the strongest correlation between these parameters
were established in May. The highest correlation between ambient air temperature and
produced thermal energy is reached when ambient air temperature is between 7 °C to 15 °C
and production process has not been externally regulated. The temperature difference
between flow and return temperatures of the heat carrier affect solar collector performance
minimally and strong correlation was not observed.
Keywords – District heating; large scale solar collector field; regression analyses
1. INTRODUCTION
A Green New Deal target is zero emission by 2050, as well as not to exceed global warming
under 1.5 °C. One of the main steps in this resolution is to decarbonise the energy sector. The
Green New Deal will promote decarbonisation of the economy in the energy sector and ensure
longer investment periods [1].
In recent years, use of sustainable heat sources in district heating (DH) has been growing,
heating network losses are reduced and digitalization is taking place to achieve the targets. A
variety of sustainable energy sources are used in DH in the EU – solar energy, heat pumps,
waste heat [2]. The system is moving to the 4th generation by implementing low potential heat
sources, lowering network temperature, integrating smart grid technology, different storage
technologies and promoting interaction with prosumers. When the operation of DH systems
becomes more complex, it is important to plan long-term development of heat production,
transmission and energy efficiency measures at the consumer’s side [3], [4].
Solar energy is a high potential for use in district heating [5]–[7]. Solar collectors are
emission-free technology and an appropriate solution to reduce CO2 in the DH system.
Implementation of solar collector systems is increasing, because it uses unlimited solar energy
and have low maintenance costs [8]. Denmark is the world leader in the use of large-scale
solar collectors in DH, where approximately 160 000 m2 of solar collector active area have
* Corresponding author.
E-mail address: roberts.kakis@rtu.lv
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been installed [9]. In Denmark, 70 % of all large-scale solar collector are installed by
Arcon-Sunmark. The high solar collectors’ efficiency and long warranty decrease the payback
time [10].
Climatic conditions are one of the main influencing factors in the operation of solar
collectors [11], [12]. Yearly, the global radiation in Denmark is approximately 1000–
1150 kWh/m2, but total radiation on collector surfaces is around 1100–1200 kWh/m2. The
total radiation to the collector area is affected by the installation angle, which in Denmark is
in average 30 to 40 degrees, depending on the goal – to get the maximum capacity in the
summer or the maximum produced energy [13]. In Latvia, yearly global radiation is
approximately 1000–1200 kWh/m2 [14].
Fig 1. Global irradiation in Latvia [14].
As can be seen in Fig. 1, Latvia is divided into zones – in the north-west of Latvia radiation
is higher. However, radiation levels in Denmark and Latvia can be considered equivalent.
The main aim of the article is to evaluate the performance of the first large scale solar
system in Baltic States after one-year operation period by determining the potential solar yield
under different impact factors.
2. METHODOLOGY
Several solar collector systems influencing factors and their importance have been
evaluated in this research. Influencing indicators also show how effectively the overall system
works.
2.1. Case Study
In this paper the analysed case study is large scale solar collector system installed in Latvia,
Salaspils. The total active area of collectors is 21 672 m2 with integrated water storage tank
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of 8000 m3. The system is operating since September 2019, and it is the first field of
large-scale solar collectors for district heating in the Baltic States.
In total, 1720 Arcon-Sunmark A/S HT-Heat Boost 35/10 solar collectors have been
installed, size of each collector is 2.0 × 6.3 meters. The collector has high absorber efficiency
~83 %. The solar system is operating with a temperature regime 45/63 ºC, but in the thermal
accumulation system the temperature can be raised to 85 ºC, if necessary, which allows to
increase the total amount of stored heat.
TABLE 1. OVERVIEW OF MAIN SOLAR SYSTEM PARAM ETERS
Parameter Value
Total active area 21 672 m2
Number of installed solar collectors 1720
Operational temperature regime of solar field 45/63 °C
Volume of thermal storage tank 8000 m3
Absorber efficiency 83 %
Gross efficiency 77 %
Heat loss coefficient, a1 2.27 W/km2
Heat loss coefficient, a2 0.0181 W/km2
The operating modes are also important for the solar yield evaluation. Operation is
influenced by two factors: the intensity of solar radiation and the set temperature. When the
solar irradiance is below 250 W/m2, the solar field is preheated, but the heat production starts
when the set temperature is reached. Production is divided into two stages – low temperature
and high temperature. Low temperature production starts when the solar irradiance is from
250 W/m2 to 650 W/m2.When the solar irradiation is above 650 W/m2, high temperature
production starts. The overheating protection of solar field during high solar irradiation
period is done in two different ways. The first option is to cool it through the collector field
at night. The second option is to reduce efficiency by raising the inlet temperature in the
collector field.
The performance of solar collectors is determined according to the produced solar heat
according to Eq. (1) [15]:
2
g c 0 1ma 2ma puo
η ()()PA GaTT aTT fff
=⋅⋅−⋅−−⋅− ⋅⋅⋅
, (1)
where
Pg Guaranteed performance (thermal power output), W;
Ac Collector area corresponding to the collector efficiency parameters, m2;
η0 Optical efficiency;
a1, a2 Heat loss coefficients W/(K·m²);
G Solar irradiance on collector plane W/m²;
Ta Ambient air temperature °C;
Tm Mean temperature of solar collector fluid, °C;
fp Safety factor, considering the pipe heat losses in the collector field and transmission
lines;
fu Safety factor, considering measurement uncertainty;
fo Safety factor for other parameters.
In the particular study the estimated pipe losses are 3 %, therefore the used fp is 0.97. The
value of fu is assumed to be 0.95 for the total measurement uncertainty estimated to be 5 %.
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The used safety factor for other parameters fu is assumed as 0.95, considering non-ideal flow
distribution and unforeseen heat losses.
Mean temperature of solar collector fluid is calculated according to Eq. (2) [15].
c,in c,out
m
()
2
TT
T+
=
, (2)
where
Tc,in Hot side temperature (equal to collector outlet temperature), °C;
Tc,out Cold side temperature (equal to collector inlet temperature), °C.
From the above equations it can be seen that the solar field performance is affected by the
following factors:
− Collector area;
− Collector optical efficiency;
− System losses;
− Ambient air temperature;
− DH return temperature – inlet temperature;
− Collector outlet temperature.
The next step is to understand which factors in a particular system can be affected by the
system operator and which cannot be changed. As this is the first project in the Baltic States
the solar radiation is also analysed in order to identify how the intensity of solar radiation
affects the overall system performance. Therefore, the solar collector yield is evaluated
depending on the solar intensity, DH heat carrier return temperature and the heat carrier flow
rate.
2.2. Solar System Monitoring System and Input Data
The monitoring system is designed to ensure security and to be able to calculate the
efficiency of solar collector field. Data reading points corresponds to solar district heating
guideline is shown in Fig. 2.
Fig. 2. Technical scheme of the measurement points [15].
The particular solar collector field in Salaspils is equipped with four solar radiation meters
installed in opposite quadrants of the collector field. Solar radiation meters are connected to
circulation pumps, which increases or decreases the flow depending on the average
measurement of the two radiation meters. The cloudy weather is the main reasons why two
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measurements are compared. Radiation meters are located far enough away from each other
and, while a shadow from a cloud may have been fallen on the one of the radiation meters, at
the same time other radiation meters receive huge amount of solar radiation. Circulation
pumps and flow is also connected and regulated from temperature meters, which displays the
temperature in the solar collector system.
The days’ average radiation measurement is calculated using every measurement above
300 W/m2, because, as experience shows, at this value it is possible to start thermal energy
production and obtain useful temperature, all measurements which are under this value are
not taken into account. During the night production stops. Radiation measurements are
recorded automatically and shall be performed as minimum once every two minutes or even
more frequently. Up to 25 000 measurements are made at the 24-hour period.
The produced thermal energy from solar collectors is also measured and recorded
automatically, in order to evaluate the solar energy yield.
3. RESULTS
In the first year since solar collectors are installed in Salaspils, the annual share of thermal
energy produced by solar collectors is about 20 % of the total produced amount of heat. The
amount produced using solar collectors was 11 088 MWh, whilst the total produced amount
of thermal energy in Salaspils heating plant were about 58 GWh. As it is shown in Fig. 3, the
highest share of solar field production is observed in June, July and August, when the solar
energy share reached 46–49 % comparing to the total production. Although there are two
wood chip boilers installed in Salaspils DH plant, it was concluded, that the best solution to
cover the peaks demands in summer period is by using the natural gas boilers. Natural gas
boilers can be started immediately without the time-consuming boiler starting process, which
would be the case if biomass boilers were used. Natural gas boilers in combination with solar
collectors is used only in the summer months. Biomass boilers continue to operate in April
and June, as they are not sopped after the heating season. Therefore, total annual share of
thermal energy produced with natural gas boilers was only 10 %.
Fig. 3. Share of thermal energy produced by solar collectors and total produced thermal energy in 2019.
During the high solar radiation periods, when the sun reaches its highest intensity for
several days, the installed 8 000 m3 storage tank cannot accumulate all of the produced solar
energy, and the overheating protection of solar field starts. However, there are also moments
0
1000
2000
3000
4000
5000
6000
April May June July August
Produced thermal energy, MWh
Total Produced with solar collectors
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of low solar irradiation and cloudy weather for several days, in which all of stored heat is
consumed and production by solar collectors is insufficient. In these moments, natural gas
boilers are used for heat production, the operation of which is more efficient than biomass
boilers when switched on for a shorter time.
Another operational parameter that can be regulated by the operator is the solar field set
point. Set point is a manually adjusted temperature mark at which the solar collector field
circulation pumps start their operation and move the heat carrier towards the heat exchanger,
where heat is removed. In summer months the ambient air temperature and solar radiation is
much higher than in spring. This results in higher solar thermal energy production, but the
demand of thermal energy at the consumer’s side is lower compared to May and April. In
such cases, the set point should be increased, thus reducing the amount of energy produced
and adjust it with the heat consumption. The opposite situation is observed in spring, when
demand for thermal energy is high enough and all solar energy is either consumed, or stored.
Consequently, the set point is adjusted lower, sometimes even under the network flow
temperature to reduce the load from the biomass boilers and decrease the fuel consumption.
The obtained monitoring data are analysed by using regression analysis method by
determining the correlation between different parameters. This method reflects the
relationship between two factors, which means that when one value changes, the
corresponding one also changes. The maximum value of correlation coefficients is one.
The data presented have been collected throughout the sunny season, which in Latvia’s case
is from April until August. Fig. 3 shows that solar radiation is the main impacting factor of
produced solar thermal energy.
Fig. 4. Produced solar energy dependency of solar radiation.
Of all the parameters studied, which may affect the performance of solar collectors directly,
solar radiation has the highest correlation coefficient with average value reaching 0.6112.
Similar results have been observed in the studies carried out in large-scale solar DH systems
in Denmark [12]. The largest data distribution has been observed in July, which is due to the
regulation of already mentioned set point. At high productivity over several days and
insufficient heat demand, the set point was raised reducing produced thermal energy.
R² = 0.521
R² = 0.8249
R² = 0.5189
R² = 0.5799
0
10
20
30
40
50
60
70
80
90
100
300 400 500 600 700 800 900
Produced thermal energy, MWh
Solar radiation, W/m2
April May July August
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However, the highest correlation is observed in May because solar collectors are placed in
such a position that they produce heat energy with the highest efficiency and productivity in
May. This analysis proves it. If this correlation between solar radiation and solar collector
productivity is the strongest in May, the most appropriate conditions have therefore been
created to make production the most efficient at this time.
Fig. 4 presents a correlation between ambient air and produced thermal energy. The
correlation between these parameters is lower in June, July and August, but higher in April
and May. Average correlation between ambient air temperature and produced thermal energy
is 0.2837, which means that the correlation is low and other conditions impact solar collector
performance more.
Fig. 5. Solar collector efficiency dependency of ambient air temperature.
Another analysed impacting parameters that were examined in this study were flow and
return temperature of heat carrier. Study showed that correlation between these parameters
and produced thermal energy with solar collectors is very low. The data was very distributed
and knowing that the set point value was changed regularly, several times a day, the analysis
of these parameters is very complicated. When the temperature difference changes several
times a day, it is difficult to register and divide data on how much heat energy was produced
with each specific temperature difference between supply and return temperatures.
Fig. 5 shows the comparison of the performance about numerous solar heating plants in
Denmark and the particular solar DH plant in Salaspils. All the heating plants included in this
comparison are using the same solar collector technologies from Arcon-Sunmark A/S,
HTHEATstore 35/10. The data was calculated as average solar performance and solar
radiation results during the period from 2012 to 2016 presenter in [13]. It is clear that the
Salaspils solar heating plant has achieved high solar yield. The specific solar performance
(511 kWh/m2) is high compared to other solar DH systems with similar average solar
radiation.
R² = 0.3123
R² = 0.4989
R² = 0.2032
R² = 0.1972
R² = 0.2071
0
20
40
60
80
100
120
0 5 10 15 20 25 30
Produced thernmal energy, MWh
Ambient air temperature, °C
April May June July August
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Fig. 6. Comparison of solar heating plant performance demanding of solar radiation in Denmark [13] and solar heating
plant installed in Salaspils (2020).
The difference between the results could arise, because the solar heating plant in Salaspils
is actively working only the first year, when the equipment and technologies are the most
effective, although the efficiency of solar collectors does not fall significantly during the
following years. The monitoring of system performance will be continued and more driving
factors will be identified in the future.
Overall, the solar performance of solar collector field installed in Salaspils is high, however,
it would be possible to produce even more thermal energy, if the plant had more storage for
the energy, or if the demand were higher. But the problem is that the weather cannot be
controlled and the demand shrinks at times, when the production (with solar collectors) is the
most productive – warm and sunny days. On the further research authors has planned to
analyse the efficiency of solar collectors by excluding the influence of solar radiation, to
better identify the effects of other factors, which dependency on the efficiency are
significantly lower compared to solar radiation. One of the main tasks will be more detailed
analysis of the set point by dividing several components – temperature limits and flow control,
on the primary (solar collector) and secondary (rest of the system) sides of the system.
4. CONCLUSION
The article presents the operational data analysis of a first large-scale solar collector field
in Latvia, connected to district heating network, and demanding of several factors.
The results of the analysis show that the system’s productivity is mainly demanded by solar
radiation and the strongest correlation between these parameters is identified in May. Solar
collector performance is strongly affected by adjusted set point which sometimes has to be
settled on a seemingly unbeneficial value, but it is done with the long-term aim to keep the
solar collector system safe. Correlation between solar radiation and collector productivity is
linear.
200
250
300
350
400
450
500
550
600
800 850 900 950 1000 1050 1100 1150 1200 1250
Solar performance, kWh/m
2
Solar radiation, kWh/m2
Solar heating plants in Denmark Solar heating plant in Salaspils
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Solar collectors installed in Salaspils are producing with the highest productivity at a time
when it is most beneficial:
− Solar radiation is high and it would be possible to produce a large quantity of heat;
− Placement creates suitable conditions for efficient production;
− The temperature of ambient air is within such limits as the demand for heat has not yet
fallen so low that the volume produced could not be realised.
The highest correlation between ambient air temperature and produced thermal energy is
reached, when ambient air temperature is between 7 to 15 °C and production process has not
been externally regulated. The temperature difference between flow and return temperatures
of the heat carrier affect’s solar collector performance minimally and strong correlation was
not observed.
ACKNOWLEDGEMENT
The research is funded by the Ministry of Economics of the Republic of Latvia, project “Assessment of Latvia’s renewable
energy supply-demand economic potential and policy recommendations”, project No. VPP-EM2018/AER_1_0001.
This research/publication was supported by Riga Technical University's Doctoral Grant programme.
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