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Expanding the horizons of power-to-heat: Cost assessment for new space heating
1
concepts with wind powered thermal energy systems
2
Karl-Kiên Cao1*, Alejandro Nicolás Nitto2, Evelyn Sperber1 and André Thess1,3
3
1 Institute of Engineering Thermodynamics, German Aerospace Center (DLR), Pfaffenwaldring 38–40, 70569
4
Stuttgart, Germany
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2 Current affiliation: ABO Wind Energías Renovables S.A., Av. Alicia Moreau de Justo 1050, Piso 4 Oficina 196 –
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Dock 7, C1107AAP - Puerto Madero, Ciudad Autónoma de Buenos Aires, Argentina
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3 Institute of Energy Storage, University of Stuttgart, Pfaffenwaldring 31, 70569 Stuttgart, Germany
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* Corresponding author
9
Abstract
10
Wind Powered Thermal Energy Systems (WTES) are the entirety of all conceivable
11
combinations that consist of wind energy converters and thermal energy storage facilities.
12
Although there is still a pressing demand for innovative technological solutions that allow the
13
decarbonization of power and especially heat supply, comparative costs assessments that
14
include the direct conversion of wind energy into heat are pending. In this paper, we conduct
15
such an analysis for the first time. In particular, a techno-economic analysis based on the
16
calculation of levelized costs of heat supply (LCOE) is presented. The novelty of this study is
17
the comparison of five specific WTES concepts which either make use of electric boilers,
18
hydro-dynamic retarders or heat pumps. The spectrum of applications considered ranges
19
from heat supply for individual buildings to small villages and cities. The results show that
20
LCOE below 5 c€/kWh can be reached. This indicates already competitiveness compared to
21
conventional space heating technologies. In this means, we provide a systematic framework
22
for future studies to evaluate the particular economic potentials of WTES in the energy
23
market.
24
Keywords
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Wind powered energy systems, wind energy, space heating, thermal energy storage
26
Abbreviations
27
AHP
Absorption heat pump
CAPEX
Capital expenditures
CF
Capacity factor
CHP
Combined heat and power
CSP
Concentrated solar power
EB
Electrical boiler
eHP
Electrical heat pump
LCOE
Levelized cost of energy (heat) supplied
mHP
Mechanical heat pump
OPEX
Operational expenditures
ORC
Organic rankine cycle
RET
Retarder
SCOP
Seasonal coefficient of performance
WTES
Wind powered energy systems
1 Introduction
28
1.1 Demand-oriented supply of renewable energy
29
Technologies for renewable energy supply, such as wind converters and photovoltaics, are
30
not suited for generating power at any desired time. Given the growing demand for
31
integration of low-carbon technologies into energy systems, the need to balance the variable
32
availability of renewable energy resources is increasing. Frequently discussed solutions
33
include, inter alia, power storage systems which, however, cause additional costs for
34
construction and operation [1].
35
Wind turbines are nowadays one of the most cost-effective ways of generating electricity
36
from renewable energy resources and thus can contribute significantly to low-carbon energy
37
supply in the future. However, since the majority of wind turbines tends to provide power at
38
the same time for a local spatial scale, a high supply of electricity is generated
39
simultaneously [2] but not necessarily demand-oriented. Furthermore, extreme weather
40
events pose the challenge to ensure security of supply with dispatchable generators, such as
41
biomass-fired plants, over time periods in the range of weeks [3]. However, biomass
42
resources are limited and can therefore only be exploited to a certain extent [4].
43
Similar to photovoltaic systems, wind turbines can be extended with energy storage systems
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in order to ensure a demand-oriented power generation. Still, commercially available large-
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scale storage technologies, such as pumped-hydro storage plants or compressed-air
46
reservoirs, underlie spatial restrictions and can therefore only be installed if suitable site-
47
conditions are given [5]. Opposed to that, energy storage technologies independent of
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location, such as lithium-ion or redox flow batteries entail relatively high investment costs if
49
they are used as long-term storage [6]. The combination of both extensive location-
50
independence and cost-efficiency can be provided by thermal storage systems [7]. However,
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so far, these storage facilities are only operated in concentrated solar power plants (CSP) for
52
balancing the daily variability of solar energy [8].
53
1.2 Wind Powered Thermal Energy Systems
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In conclusion, there exists a gap in the spectrum of renewable energy technologies for wind
55
energy converters (WECs) that supplement energy supply at locations with low solar
56
radiation at reasonable costs and in line with demand in terms of time and space. This gap
57
can be filled by Wind Powered Thermal Energy Systems (WTES). WTES describes all
58
combinations of wind turbines with thermal storage facilities for the demand-oriented supply
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of electricity or heat. Compared to existing power-to-heat solutions [9][10], the novelty of
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these concepts relies on the inclusion of on-site conversion of wind energy into heat. In
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particular, we define WTES as an innovative composition of state-of-the-art technologies, i.e.
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wind energy converters, thermal storage and, depending on the application, a thermal
63
engine (Figure 1).
64
65
Figure 1: Basic concept of WTES
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Due to their capability to work with high temperature heat, WTES can be potentially used for
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both heat and power supply. This ultimately results in a very broad spectrum of conceivable
68
WTES implementation concepts. For example, WTES provide the opportunity for retrofit
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measures or the development of renewable alternatives to fossil-fired combined heat and
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power (CHP) plants. In this setup, WTES combine the systemic advantages of steam power
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plants (i.e. rotating mass) with the use of the renewable resource wind.
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The central element of WTES is the thermal energy storage. Its purpose is to balance
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intermittent heat generation and demand. Available technologies are latent heat storage,
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thermochemical storage and systems for storing sensitive heat. Today's commercial systems
75
store high-temperature heat in bulk materials made of natural materials such as granite or
76
basalt with air as the heat transport and heat transfer medium. For WTES, the size of the
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Heat Generation
& Storage
Heat Eletricity
Wind Energy
Converter
WTES Supply
storage is crucial since it defines possible operation strategies. Therefore, an appropriate
78
dimensioning includes the consideration of temperature and performance range, the working
79
medium and the required reaction times. For example, to keep losses for electricity
80
reconversion with thermal engines low (Carnot efficiency), the thermal energy storage needs
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to work with high-temperature heat (>350°C). At this temperature power reconversion with
82
efficiencies of up to 25% can be achieved by organic rankine cycle (ORC) processes [11].
83
Heat generation in WTES can be distinguished into direct and indirect energy conversion. The
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former is primarily based on the use of retarders for conversion of rotational energy into heat
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within a wind turbine. Technological realizations of retarders are on the one hand
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hydrodynamic retarders. Due to their broad application as truck brakes [33] they have
87
considerably lower costs and weight compared to electric generators. On the other hand,
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induction retarders are similar to eddy-current brakes [12]. In addition to retarders,
89
mechanical heat pumps can be used for direct energy conversion (compare section 2.1.1).
90
Indirect heat generation concepts still rely on electricity generation with a conventional
91
generator and the subsequent conversion into heat. Theoretically, such concepts provide
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advantages with regard to the hybrid use of heat and electricity. For example, the principle
93
of pumped-heat-energy-storage can be used in order to achieve the most efficient
94
conversion between electricity and heat. The high-temperature heat is generated by means
95
of electric heat pumps, which can result in a total efficiency of 54 % for the reconversion of
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electricity [13].
97
1.3 Wind Powered Thermal Energy Systems in the literature
98
With regard to the three major objectives for energy supply, i.e. economic efficiency,
99
reliability and sustainability, possible WTES implementations are not yet sufficiently
100
examined. Initial analyzes by [14] for a pure electricity generation concept show that
101
electricity production costs of WTES are competitive with the ones of conventional wind
102
energy converters extended by back-up gas turbines. Especially compared to wind-battery-
103
systems, significant cost benefits are found. In the context of power-to-heat conceptions,
104
other analyses emphasize the assessment of individual technical solutions which we interpret
105
as sub-concepts of WTES. This especially applies to indirect heat conversion using electric
106
heat pumps and boilers. Previous studies in this field concerning district heating supply in the
107
Scandinavian region are frequently of system-analytical nature. For example, in [15] the
108
objective is to ensure economically sensible system integration of a high proportion of wind
109
power. There are only a few further scientific publications regarding WTES. A model-based
110
study for direct heat conversion with vertical rotors and retarders is presented by [16].
111
Moreover, [17] propose the extension of CSP plants with wind energy converters. The idea of
112
direct wind-to-heat-conversion is taken up in patents that either focus on the application of
113
heat pumps [18] or hydrodynamic retarders [19,20].
114
Finally, a WTES research project for storing wind energy in a solid fuel storage tank at
115
temperatures of around 600°C is carried out by Siemens Gamesa. The stored heat can
116
generate 1.5 MW of electrical power via a steam turbine over a period of 24 hours. The
117
researchers expect to achieve an efficiency of around 25 % at this early stage of
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development; a potential for efficiencies of 50 % in the future is expected [21].
119
In summary, at this state the technologies we refer to as WTES are in the conception phase.
120
Although a broad variety of WTES realizations with state-of-the-art components is
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conceivable, a systematic assessment of cost structures of different WTES concepts and
122
resulting energy production costs is still missing. This applies particularly for WTES concepts
123
with direct heat conversion.
124
1.4 Objective
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In this paper we present the first techno-economic comparison of different WTES
126
applications. Thus, we lay the foundations for in-depth analyses of WTES concepts that are
127
useful for low-carbon energy supply.
128
Our economic analyses focus on the heat generation path, as it uses commercially available
129
components compared to power generation. Accordingly, we emphasize the comparison of
130
different concepts for space heating with supply temperatures below 100° C.
131
4
First sufficient compositions of technical components to supply heat with WTES are identified.
132
These systems are subsequently dimensioned for different heat consumption use cases and
133
benchmarked against state-of-the art space heating technologies on the basis of an
134
economic indicator, the levelized costs of energy supplied (LCOE). We deliberately chose a
135
straight-forward-method for determining this indicator in order to identify those WTES
136
concepts which are promising for a more detailed analysis. The appropriate setup for this
137
examination is presented in the following chapter.
138
2 Methodology
139
2.1 Setup and assumptions
140
2.1.1 Considered concepts
141
For the conversion of rotational energy into heat we define five different setups according to
142
Figure 2. Each of the heat conversion concepts is equipped with a generic heat storage unit.
143
In this context, indirect heat generation by a conventional wind energy converter and an
144
electrical boiler (EB) represents the reference case which is expected to be the most
145
expensive WTES realization.
146
The advantage of applying a heat pump as heat converter is the potential to reach high
147
efficiencies. Therefore, the second indirect heat conversion path is characterized by using
148
electrical heat pumps (eHP). However, as compressors of eHPs are more or less rotating
149
machines, the third heat conversion concept relies on directly driving a heat pump by
150
coupling it to the shaft of a WEC (mechanical heat pump, mHP). Opposed to heat pumps,
151
retarders are a mass product and thus imply low investment costs. Accordingly, the rationale
152
behind direct heat-conversion and retarder-based WTES is cost-efficiency. This is due to the
153
possibility to remove the electrical components from a WEC. Besides the exceptional
154
application of a hydrodynamic retarder (RET), the combination of such a device with an
155
absorption heat pump (AHP) allows for higher conversion efficiencies.
156
157
Figure 2: Considered heat conversion concepts for WTES dimensioned for space heating
158
2.1.2 System sizes and component dimensioning
159
To take into account economies of scale, we investigate three system sizes derived from
160
typical heat demands of 1) a single family houses (“small”), 2) a small district heating
161
network in a village consisting of 2000 inhabitants (“medium”) and 3) a medium-sized
162
district heating network in a city with 20,000 inhabitants (“large”). An additional criterion for
163
the selection of particular system sizes is that energy supply is supposed to be in a range
164
that can be covered by a small WEC, a single state-of-the-art multi-megawatt WEC and a
165
wind farm, respectively. The resulting heat demand is based on a specific annual heat
166
demand per inhabitant of 5.9 MWh [34] and checked against plausible ranges for this
167
parameter. However, for reasons of simplicity this parameter is fixed for the following
168
analyses of different system sizes. The resulting number and sizes of wind energy converters
169
is varying according to the range given in Table 1. This is due to the fact that the rated
170
power of WECs depends on the overall heat conversion efficiency of the individual WTES
171
E-Machine E-Boiler
E-Machine E-Heat Pump
Mechanical Heat Pump
Hydrodynamic Retarder
Retarder Absorbtion Heat
Pump
EB:
eHP:
mHP:
RET:
AHP
+
+
+
Heat Storage Heat Supply
<100°C
5
concepts as well as on site conditions (Table 1). We address the latter by varying the
172
capacity factor from 0.1 to 0.35.
173
To estimate an appropriate size of the thermal energy storage we account for the number of
174
hours to constantly supply a predefined peak load (Table 1). According to [34] this value is
175
derived by multiplying the total annual demand with a factor of 0.000319 1/h. The latter
176
factor results from a time series calculation as per [34]. The assumed number of hours to
177
constantly supply the estimated peak loads are 2, 5 and 10 hours for the small, medium and
178
large system setup, respectively.
179
Finally, in the case of large WTES setups, we exemplarily estimate the additional effort for
180
heat transmission to identify how a remote windfarm serves the given heat demand.
181
According to [22] a losses coefficient of 18.737 W/m is taken into account for this analysis.
182
System size
Used annual heat
demand [GWh]
Thermal peak load
[MW]
Rated power of
wind energy
converter(s) [MW]
Thermal storage
capacity [MWh]
Small
0.023
0.008
0.005 – 0.027
0.015
Medium
11.8
3.764
2.5 – 13.47
18.8
Large
118
37.642
24.5 – 134.7
376
Table 1: System sizes in terms of annual heat demand, rated power of wind energy
183
converter(s) and thermal storage capacity
184
2.1.3 Cost decomposition
185
Cost assumptions for different WTES concepts are summarized in Table 3 of the Appendix.
186
For each component of the WTES a cost break-down is conducted. Depending on the
187
analyzed WTES concept, capacity specific capital expenditures (CAPEX) and operational and
188
maintenance expenditures (OPEX) are reduced according to simplifications in the
189
construction for WTES application compared to the commercial usage of the component. This
190
applies especially to components of a WEC as in the case of direct heat conversion, electrical
191
components, such as the electricity generator, transformer, and power converters are
192
redundant. The cost-decomposition thus concerns primarily the CAPEX of the wind turbine.
193
Based on [29] we estimate these costs to be 75 % of the total investment costs of a multi-
194
megawatt WEC (see Table 2, Appendix). In addition, according to [23], we account for
195
economies of scale by considering a reduction of 22% of CAPEX for WECs in a wind farm.
196
Furthermore, we consider a discount on CAPEX of mechanically driven heat pumps compared
197
to their electrically powered counterparts due to the redundant electrical machine. Therefore,
198
the following assumptions are made: Small WTES setups are considered to have one
199
compressor which results in a fixed discount of 3,000 € representing the costs of one
200
electrical machine. Electrical heat pumps applied to medium and large systems with a rated
201
power greater than 2 MW are considered to have up to seven compressors [24]. One could
202
account for the redundancy of the motors of these compressors by an appropriate expense
203
deduction. However, since the number of compressors has a high impact on the efficiency of
204
large heat pumps and due to reasons of simplicity these cost reductions are not considered
205
for medium and large systems. Further CAPEX reduction potentials, for example concerning
206
the tower (removing the electricity generator reduces the weight of the WEC’s hub) are not
207
considered.
208
With regard to OPEX the service and spare parts are influenced by the deduction of the
209
previously mentioned electrical components. For WECs we therefore reduce the OPEX by 2%,
210
whereas for heat pumps this discount is assumed to be 10%.
211
2.1.4 Efficiency accounting
212
Assumptions regarding conversion efficiencies of different WTES concepts that are applicable
213
for the case studies on hand are derived from literature and are given in Table 3, Appendix.
214
6
Equally to the cost decomposition, conversion efficiencies are adjusted for WTES concepts
215
where certain sub-components are deduced compared to the technical setup of commercially
216
available devices. This applies to the electrical components of WECs and heat pumps
217
resulting on the one hand in a total efficiency increase of 14% regarding small WECs and 2%
218
in the case of multi-megawatt WECs. On the other hand the seasonal coefficient of
219
performance (SCOP) for mechanically driven heat pumps is adjusted from 2.8 (used for
220
electrical heat pumps) to 3.26 in the case of large systems and 2.92 for the rest.
221
2.2 Calculation of levelized cost of energy supplied
222
For the economic assessment and comparison of the different presented WTES concepts, a
223
simple model in form of the following equation is used. Eq. (1) calculates the levelized cost of
224
energy supplied (LCOE), i.e. heat, based on [30]:
225
(1)
:
In this context, the appropriate investment expenditures are calculated based on the
226
capacity specific CAPEX and the annual heat generation divided by the full load hours that
227
result from a certain capacity factor. For example, for WECs this results in eq. (2):
228
(2)
Similarly to equation (2), the capacity specific OPEX of each component as well as the
229
investment expenditures of heat converters and storage are calculated. CAPEX and OPEX for
230
any required district heating network are not considered in the initial case of this analysis.
231
2.3 Sensitivity analysis and remote supply
232
The cost values used for the calculation of LCOE are taken from the literature (Table 3,
233
Appendix). We refer to them as BASE scenario. To account for the uncertainty of considered
234
CAPEX and OPEX, a sensitivity analysis is conducted. Therefore, two additional cost scenarios
235
(HIGH and LOW) are estimated, resulting from assumptions for lower and upper cost
236
7
boundaries for each component of a WTES (Table 4, Appendix). For example, in the case of
237
heat pumps no discount for the deduced electrical machines is considered in the HIGH
238
scenario. We are also aware of further uncertainties concerning additional cost for the
239
integration of individual commercially components to a WTES. are likely to occur, such an
240
estimation requires a technologically more detailed dimensioning of beyond the scope of this
241
study.
242
With regard to heat transport from on-site generated heat to consumers, we exemplarily
243
analyze the impact of this aspect for a large WTES setup. This is due to the fact that
244
medium-sized and large systems need to transfer and distribute heat from a wind farm to a
245
multitude of consumers. Therefore, it is more likely that additional losses and costs due to
246
heat transport occur. Accordingly, we consider linearly increasing losses, CAPEX and OPEX
247
for WTES concepts that rely on direct heat conversion. The rated power of WECs as well as
248
the thermal storage size is adapted with respect to the transmission distance and the LCOE
249
are modified for the last part of the following results section (Eq. (3)):
250
(3)
:
However, opposed to this, indirect heat conversion concepts are assumed to use electricity
251
transmission. Thus, all of the scenarios still involve an optimistic assumption since no
252
expenditures for electricity transport infrastructure are considered and an existing electricity
253
grid is supposed.
254
3 Results
255
In the following, three aspects regarding the resulting LCOE for the five different WTES
256
concepts are analyzed. First, for the BASE cost scenario the LCOE is evaluated for different
257
site-conditions indicated by the capacity factor. Second, ranges of the resulting LCOE are
258
indicated for typical capacity factors between 0.15 and 0.25 taking into account the cost
259
scenarios HIGH and LOW. Finally, also the effects of heat transport are shown for WTES
260
concepts with direct heat conversion.
261
Concerning the structure of the remainder of this chapter, each sub-section consists of the
262
presentation of results and explanation of figures followed by a discussion of the appropriate
263
observations.
264
3.1 Base scenario
265
Figure 3 depicts the LCOE as a function of capacity factor of WECs for typical German sites
266
for the three analyzed system sizes. The different WTES concepts are indicated by the
267
colored lines. In addition, costs for heat production with conventional heating technologies
268
are represented by dotted lines. In particular, for small systems these lines show costs
269
resulting from an evaluation of the German heat market between 2012 and 2014 [35], while
270
for medium and large system LCOE values are taken from [25] as benchmark
i
. For both the
271
WTES concepts and the reference technologies district heating network costs are not
272
included.
273
In Figure 3, all LCOE curves show a similar shape: While for capacity factors up to 0.25 a
274
significant non-linear shape can be observed, for higher capacity factors it is approximately
275
linear.
276
8
When comparing the LCOE curves for the different WTES concepts the following can be
277
observed: With costs between 56.4 and 16.2 c€/kWh the reference WTES setup, represented
278
by electric boilers powered by WECs, is the most expensive one for a single houshold. This
279
holds also for both medium and large systems where the dark blue line in all subplots of
280
Figure 3 is at the top. However, with regard to the former, for capacity factors greater than
281
0.23, the appropriate LCOE curve cuts the upper cost estimation for heat supply from wood-
282
chip-boilers. In the case of heat supply for a city with 20,000 inhabitants this tipping point is
283
already reached for a capacity factor of 0.19. Given site-conditions with more than 2700 full
284
load hours (i.e. capacity factor of > 0.31), also the upper production costs with gas boilers
285
are achievable.
286
Furthermore, the comparision of subplots in Figure 3 shows that there exists a fixed ranking
287
of WTES concepts with regard to the resulting LCOE. This ranking is more or less
288
independent of analyzed system size or site-conditions. Correspondingly, mechanical heat
289
pumps directly driven by WECs appear to be the most cost effective WTES concept for heat
290
supply, followed by systems that make use of electrical heat pumps, absorption heat pumps,
291
retarders and electric boilers, respectively. Regarding the benchmark against conventional
292
heating technologies this means, on the one hand side that the tipping points described
293
above are reached the earlier the better LCOE-based ranking of a particular WTES concept is.
294
On the other hand, for example at capacity factor 0.2, LCOE between 6.1 and 8.1 c€/kWh for
295
heat supply by large WTES facilities with heat pumps already lie within the cost range of gas
296
boilers.
297
Finally, for small systems two additional aspects can be observed. The LCOE-based ranking is
298
less distinct since the red line representing the LCOE of electric heat pumps shows an equal
299
slope as the light blue line indicating the same for absorption heat pumps. Moreover,
300
especially in the case of low capacity factors, the spread of LCOE is significantly larger than
301
for WTES concepts powered by multi-megawatt WECs (e.g. at capacity factor 0.1: 39,1
302
c€/kWh for small systems, but 8 and 5.4 c€/kWh for medium and large system,
303
respectively). This also corresponds to the steeper slope of colored curves in the sub-plot
304
concerning small systems.
305
0
10
20
30
40
50
60
0.10 0.15 0.20 0.25 0.30 0.35
LCOE [c€/kWh]
WEC+EB
WEC+RET
WEC+eHP
WEC+RET+AHP
WEC+mHP
9
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
306
system size, due to the steeper slope for capacity factors below 0.2 the impact of site-
307
conditions dominates the LCOE more strongly than in the case of higher capacity factors. For
308
example, medium-sized, retarder-based WTES experience a LCOE reduction of 2.5 c€/kWh
309
between capacity factor 0.15 and 0.20. Opposed to that, for an increase of capacity factor
310
from 0.25 to 0.30 only a decrease in LCOE of 1 c€/kWh can be observed.
311
The decreasing costs over the three defined systems sizes are strongly influenced by the
312
specific investment costs for WECs. The significant differences between small systems and
313
their larger counterparts stem in particular from the initial CAPEX found in the literature.
314
With a value of 6 €/MWh for small WECs these costs are nearly three times as high as in the
315
case of multi-megawatt WECs. Opposed to that, the less significant differences between
316
medium and large systems can be explained by economies of scale considered with reduction
317
of 22% of WECs’ CAPEX.
318
With regard to the ranking of different WTES concepts it can be concluded that conventional,
319
wind driven power-to-heat with electrical boilers is less cost effective. Rather, the SCOP
320
introduced by heat pumps used as heat converters strongly influences the competitiveness in
321
terms of cost efficiency for heat supply. The following example illustrated this: Although the
322
CAPEX of heat pumps are 30 times higher than in the case of retarders (Table 3) the
323
resulting LCOE of the appropriate WTES concepts are lower. This is due to the dominance of
324
the CAPEX of the WECs (Table 3) which obviously can be significantly decreased if the total
325
power conversion efficiency is improved by the application of heat pumps. Therefore,
326
0
5
10
15
20
25
0.10 0.15 0.20 0.25 0.30 0.35
LCOE [c€/kWh]
WEC+EB
WEC+RET
WEC+RET+AHP
WEC+eHP
WEC+mHP
0
2
4
6
8
10
12
14
16
18
0.10 0.15 0.20 0.25 0.30 0.35
LCOE [c€/kWh]
Capacity Factor
WEC+EB
WEC+RET
WEC+RET+AHP
WEC+eHP
WEC+mHP
10
especially WTES with heat pumps show the highest potential to be competitive to traditional
327
space heating with gas or wood chip boilers.
328
Finally, compared to medium and large WTES setups, the steeper cost decrease towards
329
higher capacity factors implies that site-conditions are more crucial for small systems. This
330
especially applies to capacity factors below 0.2 because in this area heat pump based WTES
331
show a prominent potential to reach LCOE which are competetive with gas boilers. However,
332
due to distinctly lower tower heights typical capacity factors for small WECs lie in a range
333
between 0.12-0.22, opposed to 0.16-0.4 [30] for multi-megawatt WECs with tower heights
334
greater than 100m for European sites.
335
3.2 Cost sensitivity
336
To better account for cost uncertainties caused by different site-conditions and assumptions
337
for CAPEX and OPEX of each of the analyzed WTES concepts, Figure 4 depicts ranges for the
338
resulting LCOE. The bar plots and error bars result from considering the HIGH and LOW cost
339
scenario for conservative onshore site-conditions ranging between capacity factors of 0.15
340
and 0.25. This means, the upper bounds are derived from the HIGH cost scenario and a poor
341
capacity factor 0.15, the lower bounds stem from the LOW cost scenario and a better
342
capacity factor of 0.25. According to the findings from above, cost sensitivities are more
343
prominent for small WTES setups. For these systems the mHP-based concept definitely
344
shows the best performance as also in the worst case (capacity factor: 0.15, price scenario:
345
HIGH) the LCOE are in the same area as the average LCOE values of the next more
346
expensive WTES configurations.
347
For systems that make use of multi-megawatt WECs (i.e. large systems) the average LCOE
348
over all WTES concepts is 8.3 c€/kWh with a standard deviation of 2.8 c€/kWh. If only heat
349
pump-based configurations are considered these values become 7.3 c€/kWh with a standard
350
deviation of 2.1 c€/kWh. More specifically, for the individual WTES concepts the ranges of
351
LCOE significantly overlap each other, but still the ranking found above holds for worst case
352
and best case assumptions. With around 10.5 c€/kWh for heat supply with mechanical heat
353
pumps in large systems in the HIGH scenario, heat production costs lie above the typical
354
price range for gas boilers and only the upper bound for heat supply with wood chip boilers is
355
nearly met. However, seen from the other way round, in the best case (capacity factor: 0.25,
356
price scenario: LOW) even the most expensive WTES configuration with electric boilers is
357
able to fairly reach LCOE at the lower bound for heat supply with gas condensing boilers.
358
359
Figure 4: Ranges for LCOE for different system sizes and WTES concepts resulting from HIGH
360
and LOW cost scenario and capacity factors between 0.15 and 0.25
361
The results for small systems show that not only the site-conditions are crucial for the cost-
362
effectiveness of a certain WTES configuration, but also the choice between different WTES
363
concepts implies large differences for the LCOE.
364
0
10
20
30
40
50
EB eHP mHP RET RET +
AHP
EB eHP mHP RET RET +
AHP
EB eHP mHP RET RET +
AHP
Small system Medium system Large system
11
For medium and large system the results concerning the worst case depicted in Figure 4
365
suggest that in terms of production costs for heat supply a competitiveness of WTES
366
compared to the benchmark technologies is not guaranteed. But still, the average LCOE
367
especially of large systems with heat pumps show a high potential to be at least competitive
368
to the carbon-free alternative relying on wood chip fired boilers. Furthermore, in the best
369
case, even the LCOE of the more cost-efficient gas boilers can be undercut resulting in cost
370
savings for an individual household of up to 270 € per annum (considered heat demand:
371
23,000 kWh, LCOEmHP=4.3 c€/kWh compared to LCOEGas = 5.4 c€/kWh). However, these
372
potential cost savings strongly depend on possibly additional losses for heat transport
373
between the wind farm and the heat consumer.
374
3.3 Impact of heat transport
375
Figure 5 exemplarily shows the LCOE for WTES configurations with mHP as a function of the
376
distance between the windfarm and the final heat consumers. It is depicted by the green
377
curves. While the upper one corresponds to the best case, the lower one represents the
378
worst case regarding costs and wind site conditions (CF). Also for the benchmark heat supply
379
technologies both an upper as well as a lower LCOE estimation is illustrated in Figure 5.
380
These curves serve as a comparison in this sensitivity analysis and are not considered to
381
depend on the distance. Thus, they are represented by parallels to the abscissa. Since the
382
costs and losses caused by heat transmission are nearly independent of the considered heat
383
generator, the LCOE-based ranking of WTES technologies presented above remains the
384
same. For reasons of clarity, the distance dependent LCOE-curves for the other WTES
385
concepts are therefore not depicted.
386
As Figure 5 shows, the LCOE estimations for gas and wood chip boilers are nearly completely
387
within the shaded green area. This corresponds to the above mentioned finding that there is
388
no guarantee to be more cost efficient than traditional technologies for space heating. But
389
still, for distances up to 50 km, there is the potential for cost savings even if heat transport
390
is considered. In Figure 5, this potential is graphically illustrated by the triangular surface
391
that is created from the lower green and lower grey dotted line.
392
393
Figure 5: Comparison of LCOE considering heat transport in large WTES setups with
394
mechanical heat pumps
395
The difference of LCOE over a distance of 50 km lies in a range of 1 c€/kWh (lower green
396
curve) and 1.5 c€/kWh (upper green curve) for the mHP concept. Similar cost differences
397
can be observed over all WTES concepts when the capacity factor is increased from 0.20 to
398
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
399
c€/kWh). In conclusion, it can be stated that the impact of heat transport on the LCOE is
400
comparable to the influence of site-conditions within this range of capacity factors.
401
3
5
7
9
11
13
15
010 20 30 40 50 60
LCOE [c€/kWh]
Distance [km]
mHP
Wood
Chip
Boiler
Gas Boiler
12
Considering that the mean capacity factor of newly installed WECs in Germany for 2016 is
402
reported to be 0.31 (compared to an average of 0.19 over the last ten years)[26], it can be
403
expected that also WTES that rely on direct heat conversion can become a cost-effective
404
alternative to conventional heating technologies. This holds even though costs and losses
405
introduced by heat transmission are taken into account.
406
When discussing the aspect of remote supply for all of the different WTES concepts, it needs
407
to be noted, that in case of indirect heat conversion (by EB and eHP) it appears to be more
408
cost-efficient to use electricity transmission rather than heat transport via a district heating
409
network. This is not only due to the fewer losses. Even if it is assumed that no existing
410
electricity grid can be utilized, it is more likely that the appropriate length specific costs (e.g.
411
150 €/m for three-phase medium voltage cables [27]) lie below their counterparts for district
412
heating networks (Table 3, Appendix). Accordingly, it can be concluded that especially
413
indirect heat conversion with heat pumps represents the most promising WTES concept for
414
systems with high distances between WECs and heat consumption. However, further
415
investigations are necessary to account for detailed costs involved by either electricity or
416
heat transmission. For instance, this applies to CAPEX of length independent equipment such
417
as compressors or substations.
418
4 Conclusion and outlook
419
In this paper, we analyzed the capability of Wind Powered Thermal Energy Systems (WTES)
420
to provide space heat from a carbon-free resource. Compared to existing power-to-heat
421
studies we conducted techno-economic assessment of different WTES concepts which use
422
both direct and indirect heat converters. Therefore, only characteristics of commercially
423
available components were taken into account. In particular, we evaluated the LCOE and
424
identified a consistent ranking of WTES setups for different site-conditions and cost
425
scenarios. We found that directly coupling a wind energy converter to a heat pump
426
represents the most cost-effective WTES realization. Due to the negligible heat transport,
427
this holds especially for small systems that are supposed to exclusively provide heat for a
428
four-person household. For example, with around 2,400 € for space heating by WECs and
429
mechanical heat pumps the average annual generation costs are less than one third of the
430
costs associated with the use of an electrical boiler as heat converter instead.
431
We also analyzed larger system sizes that rely on the application of multi-megawatt wind
432
energy converters. Here, concepts based on heat pumps performed in a similar manner since
433
calculated LCOE bandwidths overlapped to a large extent. However, in large systems, for
434
capacity factors above 0.25, also retarder-based setups performed well in comparison to two
435
selected benchmark technologies for space heating, i.e. gas and wood chip fired boilers.
436
To account for additional costs and losses caused by heat transmission, we finally assessed
437
wind farm-fed systems with regard to the distance between heat generation and
438
consumption. It was found that even under such circumstances WTES can be competitive
439
compared to established heating concepts. However, there is no guarantee to be more cost-
440
efficient than these technologies since the LCOE strongly depend on the reachable capacity
441
factor for certain WECs and site-conditions. Since concepts based on indirect heat conversion
442
provide the possibility of electricity transmission, the WTES setup with electrical heat pumps
443
appears to be the most promising for further investigations on large systems. Nevertheless,
444
direct heat conversion concepts pose potentials for further cost reductions. This is due to the
445
redundancy of the electric generator. If it is removed from the gondola the weight of the
446
tower head can be reduced. An indicator for the associated CAPEX reduction potential can be
447
derived from the difference of estimated costs for WECs with and without gears. Especially
448
due to the higher weight of the synchronous machine in the latter the resulting total
449
component costs of WECs with gears are approximately 7% lower [27].
450
Since the LCOE-based assessment shows the economic potential of WTES to be a competitive
451
technology for space heat supply, two reasonable ways for further investigations are
452
conceivable.
453
On the one hand, for future energy scenarios with high shares of renewable energy supply,
454
the capability of WTES to provide demand-oriented heat as well as power enables an
455
additional way of integrating the variable energy resource wind into the system. Applications
456
can range from carbon-free CHP plants to hybrid power plants that integrate thermal heat
457
storage facilities. Therefore, also power-to-heat-to-power concepts needs to be further
458
13
examined assuming the availability of high temperature heat generation (Figure 6).
459
Appropriate energy conversion pathways can be integrated into state-of-the-art energy
460
system models. By treating uncertain WTES parameters, such as costs for high temperature
461
heat converters as variables, such modeling exercises are useful to identify those WTES
462
concepts and framework conditions under which this technology provides an added value to
463
the energy system.
464
465
Figure 6: Overview of WTES concepts for heat and electricity supply
466
On the other hand, more detailed analyses especially of heat pump-based concepts for space
467
heat supply enable a precise assessment of the economic feasibility of such WTES setups.
468
Accordingly, a more sophisticated dimensioning and siting of the storage unit it is necessary
469
to assess the trade-of between heat and electricity transmission as well as between central
470
and decentral storage concepts. In this regard also the benefits and drawbacks concerning
471
the placement close to heat generators or consumers play a role. Appropriate analyses
472
require time series-based simulations that consider WEC tower heights and site-specific
473
wind-speeds. With regard to the demand side, sector-specific heat consumption profiles
474
provide the possibility to identify already existing markets for renewable heat supply with
475
WTES. In particular, it can be expected that conceivable applications are sited at locations
476
with comparably low solar radiation and limited access to biomass. To give an example for
477
potential use-cases, low temperature heat driven processes, such as greenhouses, beer
478
brewing or liquor distillation may be equipped with WTES in order to completely cover energy
479
demand by renewables. In Germany, initiatives that are specialized on the utilization of solar
480
energy for this issue are already licensed with the Solar® label [28].
481
i
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.
On-Site Heat
Generation
Electricity
Generation
Indirect Heat
Generation
Heat Transmission
Electricity
Transmission
Heat Supply
Heat Storage
Eletricity Supply
Electricity
Generation
14
Acknowledgement
482
Financial support provided by the German Aerospace Center is gratefully acknowledged. We
483
would like to thank Yvonne Scholz for her valuable comments and advice during the
484
preparation of this paper.
485
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486
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17
Appendix
608
Multi-megawatt wind energy
converter
Component
Share
Tower
0.22
Rotor Blades
0.19
Rotor Hub
0.01
Rotor Bearings
0.01
Main Shaft
0.02
Main Frame
0.02
Gearbox
0.11
Generator
0.03
Yaw System
0.01
Pitch System
0.02
Power Converter
0.04
Transformer
0.03
Break System
0.01
Nacelle Housing
0.01
Cables
0.01
Screws
0.01
Small wind energy converter
Component
Share
Turbine
0.37
Tower
0.31
Charge Regulator
0.04
Inverter
0.1
Cables and Switches
0.1
Installation
0.04
Grid Connection
0.03
Permitting
0.01
Table 2: Decomposition of total capital expenditures for small and multi-megawatt wind
609
energy converters based on [29]
610
611
18
Technology
CAPEX
OPEXFIXED
OPEXVARIABLE
η
(SCOP)
Ref.
[M€/MW]
[€/MW/yr]
[€/MWh]
[-]
Traditional WEC (< 5
MW)
1.97
-
20.00
0.93
[30]
WEC not for electricity
generation
With gearbox
1.77
-
19.60
0.95
Without gearbox
1.56
-
19.20
1.00
Wind farm (20-50 MW)
1.53
-
20.00
0.93
Windfarm not for
electricity generation
With gearbox
1.38
-
19.60
0.95
Without gearbox
1.21
-
19.20
1.00
Small WEC
6.00
25,000
-
0.86
[31]
Small WEC not for
electricity generation
With gearbox
4.38
22,500
-
0.95
Without gearbox
-
22,500
-
1.00
Electric boiler
0.10
1,100
0.50
1.00
[32]
Electrically driven heat
pump (eHP)
0.70
5,500
-
2.80
Mechanically driven
heat pump (mHP)
0.70
4,950
-
2.92 –
3.26
Absorption heat pump
(AHP)
0.40
18,500
-
1.70
Retarder
0.01
250
-
1.00
[33]
CAPEX
[M€/MWh]
OPEXFIXED
[%/yr]
OPEXVARIABLE
[€/MWh]
Small TES
0.023
0.7 %
-
[34]
Medium TES
0.011
0.7 %
-
Large TES
0.009
0.7 %
-
CAPEX
[€/m]
OPEXFIXED
[%/yr]
OPEXVARIABLE
[€/MWh]
District heating network
200
1 %
-
[35]
Table 3: Cost and efficiency assumptions in BASE cost scenario derived from literature
612
19
Cost
scenario
CAPEX [M€/MW]
OPEXFIXED[€/MW/yr]
WECs for electricity generation
Small
HIGH
8.20
35,000
LOW
6.00
20,000
Medium
HIGH
2.39
LOW
1.18
Large
HIGH
1.86
LOW
0.92
WECs for direct heat conversion
Small
HIGH
5.99
31,500
LOW
4.38
18,000
Medium
HIGH
2.14
LOW
1.06
Large
HIGH
1.67
LOW
0.82
Heat generators
EB
HIGH
0.15
1,100
LOW
0.06
1,100
HP
HIGH
1.004
7,300
LOW
0.68
3,700
mHP
HIGH
1.004
7,300
LOW
0.68
3,300
RET
HIGH
0.05
1,250
LOW
0.01
250
AHP
HIGH
0.42
21,000
LOW
0.37
16,000
Table 4: Differing cost assumptions for LOW and HIGH cost scenario compared to BASE
613
