Expanding the horizons of power-to-heat: Cost assessment for new space heating
concepts with wind powered thermal energy systems
Karl-Kiên Cao1*, Alejandro Nicolás Nitto2, Evelyn Sperber1 and André Thess1,3
1 Institute of Engineering Thermodynamics, German Aerospace Center (DLR), Pfaffenwaldring 38–40, 70569
2 Current affiliation: ABO Wind Energías Renovables S.A., Av. Alicia Moreau de Justo 1050, Piso 4 Oficina 196 –
Dock 7, C1107AAP - Puerto Madero, Ciudad Autónoma de Buenos Aires, Argentina
3 Institute of Energy Storage, University of Stuttgart, Pfaffenwaldring 31, 70569 Stuttgart, Germany
* Corresponding author
Wind Powered Thermal Energy Systems (WTES) are the entirety of all conceivable
combinations that consist of wind energy converters and thermal energy storage facilities.
Although there is still a pressing demand for innovative technological solutions that allow the
decarbonization of power and especially heat supply, comparative costs assessments that
include the direct conversion of wind energy into heat are pending. In this paper, we conduct
such an analysis for the first time. In particular, a techno-economic analysis based on the
calculation of levelized costs of heat supply (LCOE) is presented. The novelty of this study is
the comparison of five specific WTES concepts which either make use of electric boilers,
hydro-dynamic retarders or heat pumps. The spectrum of applications considered ranges
from heat supply for individual buildings to small villages and cities. The results show that
LCOE below 5 c€/kWh can be reached. This indicates already competitiveness compared to
conventional space heating technologies. In this means, we provide a systematic framework
for future studies to evaluate the particular economic potentials of WTES in the energy
Wind powered energy systems, wind energy, space heating, thermal energy storage
Absorption heat pump
Combined heat and power
Concentrated solar power
Electrical heat pump
Levelized cost of energy (heat) supplied
Mechanical heat pump
Organic rankine cycle
Seasonal coefficient of performance
Wind powered energy systems
1.1 Demand-oriented supply of renewable energy
Technologies for renewable energy supply, such as wind converters and photovoltaics, are
not suited for generating power at any desired time. Given the growing demand for
integration of low-carbon technologies into energy systems, the need to balance the variable
availability of renewable energy resources is increasing. Frequently discussed solutions
include, inter alia, power storage systems which, however, cause additional costs for
construction and operation .
Wind turbines are nowadays one of the most cost-effective ways of generating electricity
from renewable energy resources and thus can contribute significantly to low-carbon energy
supply in the future. However, since the majority of wind turbines tends to provide power at
the same time for a local spatial scale, a high supply of electricity is generated
simultaneously  but not necessarily demand-oriented. Furthermore, extreme weather
events pose the challenge to ensure security of supply with dispatchable generators, such as
biomass-fired plants, over time periods in the range of weeks . However, biomass
resources are limited and can therefore only be exploited to a certain extent .
Similar to photovoltaic systems, wind turbines can be extended with energy storage systems
in order to ensure a demand-oriented power generation. Still, commercially available large-
scale storage technologies, such as pumped-hydro storage plants or compressed-air
reservoirs, underlie spatial restrictions and can therefore only be installed if suitable site-
conditions are given . Opposed to that, energy storage technologies independent of
location, such as lithium-ion or redox flow batteries entail relatively high investment costs if
they are used as long-term storage . The combination of both extensive location-
independence and cost-efficiency can be provided by thermal storage systems . However,
so far, these storage facilities are only operated in concentrated solar power plants (CSP) for
balancing the daily variability of solar energy .
1.2 Wind Powered Thermal Energy Systems
In conclusion, there exists a gap in the spectrum of renewable energy technologies for wind
energy converters (WECs) that supplement energy supply at locations with low solar
radiation at reasonable costs and in line with demand in terms of time and space. This gap
can be filled by Wind Powered Thermal Energy Systems (WTES). WTES describes all
combinations of wind turbines with thermal storage facilities for the demand-oriented supply
of electricity or heat. Compared to existing power-to-heat solutions , the novelty of
these concepts relies on the inclusion of on-site conversion of wind energy into heat. In
particular, we define WTES as an innovative composition of state-of-the-art technologies, i.e.
wind energy converters, thermal storage and, depending on the application, a thermal
engine (Figure 1).
Figure 1: Basic concept of WTES
Due to their capability to work with high temperature heat, WTES can be potentially used for
both heat and power supply. This ultimately results in a very broad spectrum of conceivable
WTES implementation concepts. For example, WTES provide the opportunity for retrofit
measures or the development of renewable alternatives to fossil-fired combined heat and
power (CHP) plants. In this setup, WTES combine the systemic advantages of steam power
plants (i.e. rotating mass) with the use of the renewable resource wind.
The central element of WTES is the thermal energy storage. Its purpose is to balance
intermittent heat generation and demand. Available technologies are latent heat storage,
thermochemical storage and systems for storing sensitive heat. Today's commercial systems
store high-temperature heat in bulk materials made of natural materials such as granite or
basalt with air as the heat transport and heat transfer medium. For WTES, the size of the
storage is crucial since it defines possible operation strategies. Therefore, an appropriate
dimensioning includes the consideration of temperature and performance range, the working
medium and the required reaction times. For example, to keep losses for electricity
reconversion with thermal engines low (Carnot efficiency), the thermal energy storage needs
to work with high-temperature heat (>350°C). At this temperature power reconversion with
efficiencies of up to 25% can be achieved by organic rankine cycle (ORC) processes .
Heat generation in WTES can be distinguished into direct and indirect energy conversion. The
former is primarily based on the use of retarders for conversion of rotational energy into heat
within a wind turbine. Technological realizations of retarders are on the one hand
hydrodynamic retarders. Due to their broad application as truck brakes  they have
considerably lower costs and weight compared to electric generators. On the other hand,
induction retarders are similar to eddy-current brakes . In addition to retarders,
mechanical heat pumps can be used for direct energy conversion (compare section 2.1.1).
Indirect heat generation concepts still rely on electricity generation with a conventional
generator and the subsequent conversion into heat. Theoretically, such concepts provide
advantages with regard to the hybrid use of heat and electricity. For example, the principle
of pumped-heat-energy-storage can be used in order to achieve the most efficient
conversion between electricity and heat. The high-temperature heat is generated by means
of electric heat pumps, which can result in a total efficiency of 54 % for the reconversion of
1.3 Wind Powered Thermal Energy Systems in the literature
With regard to the three major objectives for energy supply, i.e. economic efficiency,
reliability and sustainability, possible WTES implementations are not yet sufficiently
examined. Initial analyzes by  for a pure electricity generation concept show that
electricity production costs of WTES are competitive with the ones of conventional wind
energy converters extended by back-up gas turbines. Especially compared to wind-battery-
systems, significant cost benefits are found. In the context of power-to-heat conceptions,
other analyses emphasize the assessment of individual technical solutions which we interpret
as sub-concepts of WTES. This especially applies to indirect heat conversion using electric
heat pumps and boilers. Previous studies in this field concerning district heating supply in the
Scandinavian region are frequently of system-analytical nature. For example, in  the
objective is to ensure economically sensible system integration of a high proportion of wind
power. There are only a few further scientific publications regarding WTES. A model-based
study for direct heat conversion with vertical rotors and retarders is presented by .
Moreover,  propose the extension of CSP plants with wind energy converters. The idea of
direct wind-to-heat-conversion is taken up in patents that either focus on the application of
heat pumps  or hydrodynamic retarders [19,20].
Finally, a WTES research project for storing wind energy in a solid fuel storage tank at
temperatures of around 600°C is carried out by Siemens Gamesa. The stored heat can
generate 1.5 MW of electrical power via a steam turbine over a period of 24 hours. The
researchers expect to achieve an efficiency of around 25 % at this early stage of
development; a potential for efficiencies of 50 % in the future is expected .
In summary, at this state the technologies we refer to as WTES are in the conception phase.
Although a broad variety of WTES realizations with state-of-the-art components is
conceivable, a systematic assessment of cost structures of different WTES concepts and
resulting energy production costs is still missing. This applies particularly for WTES concepts
with direct heat conversion.
In this paper we present the first techno-economic comparison of different WTES
applications. Thus, we lay the foundations for in-depth analyses of WTES concepts that are
useful for low-carbon energy supply.
Our economic analyses focus on the heat generation path, as it uses commercially available
components compared to power generation. Accordingly, we emphasize the comparison of
different concepts for space heating with supply temperatures below 100° C.
First sufficient compositions of technical components to supply heat with WTES are identified.
These systems are subsequently dimensioned for different heat consumption use cases and
benchmarked against state-of-the art space heating technologies on the basis of an
economic indicator, the levelized costs of energy supplied (LCOE). We deliberately chose a
straight-forward-method for determining this indicator in order to identify those WTES
concepts which are promising for a more detailed analysis. The appropriate setup for this
examination is presented in the following chapter.
2.1 Setup and assumptions
2.1.1 Considered concepts
For the conversion of rotational energy into heat we define five different setups according to
Figure 2. Each of the heat conversion concepts is equipped with a generic heat storage unit.
In this context, indirect heat generation by a conventional wind energy converter and an
electrical boiler (EB) represents the reference case which is expected to be the most
expensive WTES realization.
The advantage of applying a heat pump as heat converter is the potential to reach high
efficiencies. Therefore, the second indirect heat conversion path is characterized by using
electrical heat pumps (eHP). However, as compressors of eHPs are more or less rotating
machines, the third heat conversion concept relies on directly driving a heat pump by
coupling it to the shaft of a WEC (mechanical heat pump, mHP). Opposed to heat pumps,
retarders are a mass product and thus imply low investment costs. Accordingly, the rationale
behind direct heat-conversion and retarder-based WTES is cost-efficiency. This is due to the
possibility to remove the electrical components from a WEC. Besides the exceptional
application of a hydrodynamic retarder (RET), the combination of such a device with an
absorption heat pump (AHP) allows for higher conversion efficiencies.
Figure 2: Considered heat conversion concepts for WTES dimensioned for space heating
2.1.2 System sizes and component dimensioning
To take into account economies of scale, we investigate three system sizes derived from
typical heat demands of 1) a single family houses (“small”), 2) a small district heating
network in a village consisting of 2000 inhabitants (“medium”) and 3) a medium-sized
district heating network in a city with 20,000 inhabitants (“large”). An additional criterion for
the selection of particular system sizes is that energy supply is supposed to be in a range
that can be covered by a small WEC, a single state-of-the-art multi-megawatt WEC and a
wind farm, respectively. The resulting heat demand is based on a specific annual heat
demand per inhabitant of 5.9 MWh  and checked against plausible ranges for this
parameter. However, for reasons of simplicity this parameter is fixed for the following
analyses of different system sizes. The resulting number and sizes of wind energy converters
is varying according to the range given in Table 1. This is due to the fact that the rated
power of WECs depends on the overall heat conversion efficiency of the individual WTES
E-Machine E-Heat Pump
Mechanical Heat Pump
Retarder Absorbtion Heat
Heat Storage Heat Supply
concepts as well as on site conditions (Table 1). We address the latter by varying the
capacity factor from 0.1 to 0.35.
To estimate an appropriate size of the thermal energy storage we account for the number of
hours to constantly supply a predefined peak load (Table 1). According to  this value is
derived by multiplying the total annual demand with a factor of 0.000319 1/h. The latter
factor results from a time series calculation as per . The assumed number of hours to
constantly supply the estimated peak loads are 2, 5 and 10 hours for the small, medium and
large system setup, respectively.
Finally, in the case of large WTES setups, we exemplarily estimate the additional effort for
heat transmission to identify how a remote windfarm serves the given heat demand.
According to  a losses coefficient of 18.737 W/m is taken into account for this analysis.
Used annual heat
Thermal peak load
Rated power of
0.005 – 0.027
2.5 – 13.47
24.5 – 134.7
Table 1: System sizes in terms of annual heat demand, rated power of wind energy
converter(s) and thermal storage capacity
2.1.3 Cost decomposition
Cost assumptions for different WTES concepts are summarized in Table 3 of the Appendix.
For each component of the WTES a cost break-down is conducted. Depending on the
analyzed WTES concept, capacity specific capital expenditures (CAPEX) and operational and
maintenance expenditures (OPEX) are reduced according to simplifications in the
construction for WTES application compared to the commercial usage of the component. This
applies especially to components of a WEC as in the case of direct heat conversion, electrical
components, such as the electricity generator, transformer, and power converters are
redundant. The cost-decomposition thus concerns primarily the CAPEX of the wind turbine.
Based on  we estimate these costs to be 75 % of the total investment costs of a multi-
megawatt WEC (see Table 2, Appendix). In addition, according to , we account for
economies of scale by considering a reduction of 22% of CAPEX for WECs in a wind farm.
Furthermore, we consider a discount on CAPEX of mechanically driven heat pumps compared
to their electrically powered counterparts due to the redundant electrical machine. Therefore,
the following assumptions are made: Small WTES setups are considered to have one
compressor which results in a fixed discount of 3,000 € representing the costs of one
electrical machine. Electrical heat pumps applied to medium and large systems with a rated
power greater than 2 MW are considered to have up to seven compressors . One could
account for the redundancy of the motors of these compressors by an appropriate expense
deduction. However, since the number of compressors has a high impact on the efficiency of
large heat pumps and due to reasons of simplicity these cost reductions are not considered
for medium and large systems. Further CAPEX reduction potentials, for example concerning
the tower (removing the electricity generator reduces the weight of the WEC’s hub) are not
With regard to OPEX the service and spare parts are influenced by the deduction of the
previously mentioned electrical components. For WECs we therefore reduce the OPEX by 2%,
whereas for heat pumps this discount is assumed to be 10%.
2.1.4 Efficiency accounting
Assumptions regarding conversion efficiencies of different WTES concepts that are applicable
for the case studies on hand are derived from literature and are given in Table 3, Appendix.
Equally to the cost decomposition, conversion efficiencies are adjusted for WTES concepts
where certain sub-components are deduced compared to the technical setup of commercially
available devices. This applies to the electrical components of WECs and heat pumps
resulting on the one hand in a total efficiency increase of 14% regarding small WECs and 2%
in the case of multi-megawatt WECs. On the other hand the seasonal coefficient of
performance (SCOP) for mechanically driven heat pumps is adjusted from 2.8 (used for
electrical heat pumps) to 3.26 in the case of large systems and 2.92 for the rest.
2.2 Calculation of levelized cost of energy supplied
For the economic assessment and comparison of the different presented WTES concepts, a
simple model in form of the following equation is used. Eq. (1) calculates the levelized cost of
energy supplied (LCOE), i.e. heat, based on :
In this context, the appropriate investment expenditures are calculated based on the
capacity specific CAPEX and the annual heat generation divided by the full load hours that
result from a certain capacity factor. For example, for WECs this results in eq. (2):
Similarly to equation (2), the capacity specific OPEX of each component as well as the
investment expenditures of heat converters and storage are calculated. CAPEX and OPEX for
any required district heating network are not considered in the initial case of this analysis.
2.3 Sensitivity analysis and remote supply
The cost values used for the calculation of LCOE are taken from the literature (Table 3,
Appendix). We refer to them as BASE scenario. To account for the uncertainty of considered
CAPEX and OPEX, a sensitivity analysis is conducted. Therefore, two additional cost scenarios
(HIGH and LOW) are estimated, resulting from assumptions for lower and upper cost
boundaries for each component of a WTES (Table 4, Appendix). For example, in the case of
heat pumps no discount for the deduced electrical machines is considered in the HIGH
scenario. We are also aware of further uncertainties concerning additional cost for the
integration of individual commercially components to a WTES. are likely to occur, such an
estimation requires a technologically more detailed dimensioning of beyond the scope of this
With regard to heat transport from on-site generated heat to consumers, we exemplarily
analyze the impact of this aspect for a large WTES setup. This is due to the fact that
medium-sized and large systems need to transfer and distribute heat from a wind farm to a
multitude of consumers. Therefore, it is more likely that additional losses and costs due to
heat transport occur. Accordingly, we consider linearly increasing losses, CAPEX and OPEX
for WTES concepts that rely on direct heat conversion. The rated power of WECs as well as
the thermal storage size is adapted with respect to the transmission distance and the LCOE
are modified for the last part of the following results section (Eq. (3)):
However, opposed to this, indirect heat conversion concepts are assumed to use electricity
transmission. Thus, all of the scenarios still involve an optimistic assumption since no
expenditures for electricity transport infrastructure are considered and an existing electricity
grid is supposed.
In the following, three aspects regarding the resulting LCOE for the five different WTES
concepts are analyzed. First, for the BASE cost scenario the LCOE is evaluated for different
site-conditions indicated by the capacity factor. Second, ranges of the resulting LCOE are
indicated for typical capacity factors between 0.15 and 0.25 taking into account the cost
scenarios HIGH and LOW. Finally, also the effects of heat transport are shown for WTES
concepts with direct heat conversion.
Concerning the structure of the remainder of this chapter, each sub-section consists of the
presentation of results and explanation of figures followed by a discussion of the appropriate
3.1 Base scenario
Figure 3 depicts the LCOE as a function of capacity factor of WECs for typical German sites
for the three analyzed system sizes. The different WTES concepts are indicated by the
colored lines. In addition, costs for heat production with conventional heating technologies
are represented by dotted lines. In particular, for small systems these lines show costs
resulting from an evaluation of the German heat market between 2012 and 2014 , while
for medium and large system LCOE values are taken from  as benchmark
. For both the
WTES concepts and the reference technologies district heating network costs are not
In Figure 3, all LCOE curves show a similar shape: While for capacity factors up to 0.25 a
significant non-linear shape can be observed, for higher capacity factors it is approximately
When comparing the LCOE curves for the different WTES concepts the following can be
observed: With costs between 56.4 and 16.2 c€/kWh the reference WTES setup, represented
by electric boilers powered by WECs, is the most expensive one for a single houshold. This
holds also for both medium and large systems where the dark blue line in all subplots of
Figure 3 is at the top. However, with regard to the former, for capacity factors greater than
0.23, the appropriate LCOE curve cuts the upper cost estimation for heat supply from wood-
chip-boilers. In the case of heat supply for a city with 20,000 inhabitants this tipping point is
already reached for a capacity factor of 0.19. Given site-conditions with more than 2700 full
load hours (i.e. capacity factor of > 0.31), also the upper production costs with gas boilers
Furthermore, the comparision of subplots in Figure 3 shows that there exists a fixed ranking
of WTES concepts with regard to the resulting LCOE. This ranking is more or less
independent of analyzed system size or site-conditions. Correspondingly, mechanical heat
pumps directly driven by WECs appear to be the most cost effective WTES concept for heat
supply, followed by systems that make use of electrical heat pumps, absorption heat pumps,
retarders and electric boilers, respectively. Regarding the benchmark against conventional
heating technologies this means, on the one hand side that the tipping points described
above are reached the earlier the better LCOE-based ranking of a particular WTES concept is.
On the other hand, for example at capacity factor 0.2, LCOE between 6.1 and 8.1 c€/kWh for
heat supply by large WTES facilities with heat pumps already lie within the cost range of gas
Finally, for small systems two additional aspects can be observed. The LCOE-based ranking is
less distinct since the red line representing the LCOE of electric heat pumps shows an equal
slope as the light blue line indicating the same for absorption heat pumps. Moreover,
especially in the case of low capacity factors, the spread of LCOE is significantly larger than
for WTES concepts powered by multi-megawatt WECs (e.g. at capacity factor 0.1: 39,1
c€/kWh for small systems, but 8 and 5.4 c€/kWh for medium and large system,
respectively). This also corresponds to the steeper slope of colored curves in the sub-plot
concerning small systems.
0.10 0.15 0.20 0.25 0.30 0.35
Figure 3: Levelized cost of heat supply for small (top), medium (center) and large (bottom)
WTES systems, including reference LCOE for gas boilers (grey dotted lines) and wood chip
boilers (brown dotted lines)
From the general shape of all LCOE curves the following can be derived: Regardless of the
system size, due to the steeper slope for capacity factors below 0.2 the impact of site-
conditions dominates the LCOE more strongly than in the case of higher capacity factors. For
example, medium-sized, retarder-based WTES experience a LCOE reduction of 2.5 c€/kWh
between capacity factor 0.15 and 0.20. Opposed to that, for an increase of capacity factor
from 0.25 to 0.30 only a decrease in LCOE of 1 c€/kWh can be observed.
The decreasing costs over the three defined systems sizes are strongly influenced by the
specific investment costs for WECs. The significant differences between small systems and
their larger counterparts stem in particular from the initial CAPEX found in the literature.
With a value of 6 €/MWh for small WECs these costs are nearly three times as high as in the
case of multi-megawatt WECs. Opposed to that, the less significant differences between
medium and large systems can be explained by economies of scale considered with reduction
of 22% of WECs’ CAPEX.
With regard to the ranking of different WTES concepts it can be concluded that conventional,
wind driven power-to-heat with electrical boilers is less cost effective. Rather, the SCOP
introduced by heat pumps used as heat converters strongly influences the competitiveness in
terms of cost efficiency for heat supply. The following example illustrated this: Although the
CAPEX of heat pumps are 30 times higher than in the case of retarders (Table 3) the
resulting LCOE of the appropriate WTES concepts are lower. This is due to the dominance of
the CAPEX of the WECs (Table 3) which obviously can be significantly decreased if the total
power conversion efficiency is improved by the application of heat pumps. Therefore,
0.10 0.15 0.20 0.25 0.30 0.35
0.10 0.15 0.20 0.25 0.30 0.35
especially WTES with heat pumps show the highest potential to be competitive to traditional
space heating with gas or wood chip boilers.
Finally, compared to medium and large WTES setups, the steeper cost decrease towards
higher capacity factors implies that site-conditions are more crucial for small systems. This
especially applies to capacity factors below 0.2 because in this area heat pump based WTES
show a prominent potential to reach LCOE which are competetive with gas boilers. However,
due to distinctly lower tower heights typical capacity factors for small WECs lie in a range
between 0.12-0.22, opposed to 0.16-0.4  for multi-megawatt WECs with tower heights
greater than 100m for European sites.
3.2 Cost sensitivity
To better account for cost uncertainties caused by different site-conditions and assumptions
for CAPEX and OPEX of each of the analyzed WTES concepts, Figure 4 depicts ranges for the
resulting LCOE. The bar plots and error bars result from considering the HIGH and LOW cost
scenario for conservative onshore site-conditions ranging between capacity factors of 0.15
and 0.25. This means, the upper bounds are derived from the HIGH cost scenario and a poor
capacity factor 0.15, the lower bounds stem from the LOW cost scenario and a better
capacity factor of 0.25. According to the findings from above, cost sensitivities are more
prominent for small WTES setups. For these systems the mHP-based concept definitely
shows the best performance as also in the worst case (capacity factor: 0.15, price scenario:
HIGH) the LCOE are in the same area as the average LCOE values of the next more
expensive WTES configurations.
For systems that make use of multi-megawatt WECs (i.e. large systems) the average LCOE
over all WTES concepts is 8.3 c€/kWh with a standard deviation of 2.8 c€/kWh. If only heat
pump-based configurations are considered these values become 7.3 c€/kWh with a standard
deviation of 2.1 c€/kWh. More specifically, for the individual WTES concepts the ranges of
LCOE significantly overlap each other, but still the ranking found above holds for worst case
and best case assumptions. With around 10.5 c€/kWh for heat supply with mechanical heat
pumps in large systems in the HIGH scenario, heat production costs lie above the typical
price range for gas boilers and only the upper bound for heat supply with wood chip boilers is
nearly met. However, seen from the other way round, in the best case (capacity factor: 0.25,
price scenario: LOW) even the most expensive WTES configuration with electric boilers is
able to fairly reach LCOE at the lower bound for heat supply with gas condensing boilers.
Figure 4: Ranges for LCOE for different system sizes and WTES concepts resulting from HIGH
and LOW cost scenario and capacity factors between 0.15 and 0.25
The results for small systems show that not only the site-conditions are crucial for the cost-
effectiveness of a certain WTES configuration, but also the choice between different WTES
concepts implies large differences for the LCOE.
EB eHP mHP RET RET +
EB eHP mHP RET RET +
EB eHP mHP RET RET +
Small system Medium system Large system
For medium and large system the results concerning the worst case depicted in Figure 4
suggest that in terms of production costs for heat supply a competitiveness of WTES
compared to the benchmark technologies is not guaranteed. But still, the average LCOE
especially of large systems with heat pumps show a high potential to be at least competitive
to the carbon-free alternative relying on wood chip fired boilers. Furthermore, in the best
case, even the LCOE of the more cost-efficient gas boilers can be undercut resulting in cost
savings for an individual household of up to 270 € per annum (considered heat demand:
23,000 kWh, LCOEmHP=4.3 c€/kWh compared to LCOEGas = 5.4 c€/kWh). However, these
potential cost savings strongly depend on possibly additional losses for heat transport
between the wind farm and the heat consumer.
3.3 Impact of heat transport
Figure 5 exemplarily shows the LCOE for WTES configurations with mHP as a function of the
distance between the windfarm and the final heat consumers. It is depicted by the green
curves. While the upper one corresponds to the best case, the lower one represents the
worst case regarding costs and wind site conditions (CF). Also for the benchmark heat supply
technologies both an upper as well as a lower LCOE estimation is illustrated in Figure 5.
These curves serve as a comparison in this sensitivity analysis and are not considered to
depend on the distance. Thus, they are represented by parallels to the abscissa. Since the
costs and losses caused by heat transmission are nearly independent of the considered heat
generator, the LCOE-based ranking of WTES technologies presented above remains the
same. For reasons of clarity, the distance dependent LCOE-curves for the other WTES
concepts are therefore not depicted.
As Figure 5 shows, the LCOE estimations for gas and wood chip boilers are nearly completely
within the shaded green area. This corresponds to the above mentioned finding that there is
no guarantee to be more cost efficient than traditional technologies for space heating. But
still, for distances up to 50 km, there is the potential for cost savings even if heat transport
is considered. In Figure 5, this potential is graphically illustrated by the triangular surface
that is created from the lower green and lower grey dotted line.
Figure 5: Comparison of LCOE considering heat transport in large WTES setups with
mechanical heat pumps
The difference of LCOE over a distance of 50 km lies in a range of 1 c€/kWh (lower green
curve) and 1.5 c€/kWh (upper green curve) for the mHP concept. Similar cost differences
can be observed over all WTES concepts when the capacity factor is increased from 0.20 to
0.25 (mHP: 1.2 c€/kWh, eHP: 1.2 c€/kWh, RET: 1.2 c€/kWh, AHP: 1.3 c€/kWh, EB: 1.4
c€/kWh). In conclusion, it can be stated that the impact of heat transport on the LCOE is
comparable to the influence of site-conditions within this range of capacity factors.
010 20 30 40 50 60
Considering that the mean capacity factor of newly installed WECs in Germany for 2016 is
reported to be 0.31 (compared to an average of 0.19 over the last ten years), it can be
expected that also WTES that rely on direct heat conversion can become a cost-effective
alternative to conventional heating technologies. This holds even though costs and losses
introduced by heat transmission are taken into account.
When discussing the aspect of remote supply for all of the different WTES concepts, it needs
to be noted, that in case of indirect heat conversion (by EB and eHP) it appears to be more
cost-efficient to use electricity transmission rather than heat transport via a district heating
network. This is not only due to the fewer losses. Even if it is assumed that no existing
electricity grid can be utilized, it is more likely that the appropriate length specific costs (e.g.
150 €/m for three-phase medium voltage cables ) lie below their counterparts for district
heating networks (Table 3, Appendix). Accordingly, it can be concluded that especially
indirect heat conversion with heat pumps represents the most promising WTES concept for
systems with high distances between WECs and heat consumption. However, further
investigations are necessary to account for detailed costs involved by either electricity or
heat transmission. For instance, this applies to CAPEX of length independent equipment such
as compressors or substations.
4 Conclusion and outlook
In this paper, we analyzed the capability of Wind Powered Thermal Energy Systems (WTES)
to provide space heat from a carbon-free resource. Compared to existing power-to-heat
studies we conducted techno-economic assessment of different WTES concepts which use
both direct and indirect heat converters. Therefore, only characteristics of commercially
available components were taken into account. In particular, we evaluated the LCOE and
identified a consistent ranking of WTES setups for different site-conditions and cost
scenarios. We found that directly coupling a wind energy converter to a heat pump
represents the most cost-effective WTES realization. Due to the negligible heat transport,
this holds especially for small systems that are supposed to exclusively provide heat for a
four-person household. For example, with around 2,400 € for space heating by WECs and
mechanical heat pumps the average annual generation costs are less than one third of the
costs associated with the use of an electrical boiler as heat converter instead.
We also analyzed larger system sizes that rely on the application of multi-megawatt wind
energy converters. Here, concepts based on heat pumps performed in a similar manner since
calculated LCOE bandwidths overlapped to a large extent. However, in large systems, for
capacity factors above 0.25, also retarder-based setups performed well in comparison to two
selected benchmark technologies for space heating, i.e. gas and wood chip fired boilers.
To account for additional costs and losses caused by heat transmission, we finally assessed
wind farm-fed systems with regard to the distance between heat generation and
consumption. It was found that even under such circumstances WTES can be competitive
compared to established heating concepts. However, there is no guarantee to be more cost-
efficient than these technologies since the LCOE strongly depend on the reachable capacity
factor for certain WECs and site-conditions. Since concepts based on indirect heat conversion
provide the possibility of electricity transmission, the WTES setup with electrical heat pumps
appears to be the most promising for further investigations on large systems. Nevertheless,
direct heat conversion concepts pose potentials for further cost reductions. This is due to the
redundancy of the electric generator. If it is removed from the gondola the weight of the
tower head can be reduced. An indicator for the associated CAPEX reduction potential can be
derived from the difference of estimated costs for WECs with and without gears. Especially
due to the higher weight of the synchronous machine in the latter the resulting total
component costs of WECs with gears are approximately 7% lower .
Since the LCOE-based assessment shows the economic potential of WTES to be a competitive
technology for space heat supply, two reasonable ways for further investigations are
On the one hand, for future energy scenarios with high shares of renewable energy supply,
the capability of WTES to provide demand-oriented heat as well as power enables an
additional way of integrating the variable energy resource wind into the system. Applications
can range from carbon-free CHP plants to hybrid power plants that integrate thermal heat
storage facilities. Therefore, also power-to-heat-to-power concepts needs to be further
examined assuming the availability of high temperature heat generation (Figure 6).
Appropriate energy conversion pathways can be integrated into state-of-the-art energy
system models. By treating uncertain WTES parameters, such as costs for high temperature
heat converters as variables, such modeling exercises are useful to identify those WTES
concepts and framework conditions under which this technology provides an added value to
the energy system.
Figure 6: Overview of WTES concepts for heat and electricity supply
On the other hand, more detailed analyses especially of heat pump-based concepts for space
heat supply enable a precise assessment of the economic feasibility of such WTES setups.
Accordingly, a more sophisticated dimensioning and siting of the storage unit it is necessary
to assess the trade-of between heat and electricity transmission as well as between central
and decentral storage concepts. In this regard also the benefits and drawbacks concerning
the placement close to heat generators or consumers play a role. Appropriate analyses
require time series-based simulations that consider WEC tower heights and site-specific
wind-speeds. With regard to the demand side, sector-specific heat consumption profiles
provide the possibility to identify already existing markets for renewable heat supply with
WTES. In particular, it can be expected that conceivable applications are sited at locations
with comparably low solar radiation and limited access to biomass. To give an example for
potential use-cases, low temperature heat driven processes, such as greenhouses, beer
brewing or liquor distillation may be equipped with WTES in order to completely cover energy
demand by renewables. In Germany, initiatives that are specialized on the utilization of solar
energy for this issue are already licensed with the Solar® label .
Assuming an average exchange rate of 0.9 €/$, the associated heating costs with gas boilers
lie in a range between 9.3 and 13.4 c€/kWh for a single household and between 5.4 and 6.8
c€/kWh for larger systems. In the case of wood-chip boilers the LCOE are reported in a range
between 7.2 and 9.9 c€/kWh.
Financial support provided by the German Aerospace Center is gratefully acknowledged. We
would like to thank Yvonne Scholz for her valuable comments and advice during the
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Multi-megawatt wind energy
Small wind energy converter
Cables and Switches
Table 2: Decomposition of total capital expenditures for small and multi-megawatt wind
energy converters based on 
Traditional WEC (< 5
WEC not for electricity
Wind farm (20-50 MW)
Windfarm not for
Small WEC not for
Electrically driven heat
heat pump (mHP)
Absorption heat pump
District heating network
Table 3: Cost and efficiency assumptions in BASE cost scenario derived from literature
WECs for electricity generation
WECs for direct heat conversion
Table 4: Differing cost assumptions for LOW and HIGH cost scenario compared to BASE