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Expanding the horizons of power-to-heat: Cost assessment for new space heating concepts with Wind Powered Thermal Energy Systems

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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. We design generic models of the WTES concepts under consideration, taking into account component dimensioning, cost structures and efficiency parameters. 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 market.
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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 3840, 70569
4
Stuttgart, Germany
5
2 Current affiliation: ABO Wind Energías Renovables S.A., Av. Alicia Moreau de Justo 1050, Piso 4 Oficina 196
6
Dock 7, C1107AAP - Puerto Madero, Ciudad Autónoma de Buenos Aires, Argentina
7
3 Institute of Energy Storage, University of Stuttgart, Pfaffenwaldring 31, 70569 Stuttgart, Germany
8
* 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
25
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
44
in order to ensure a demand-oriented power generation. Still, commercially available large-
45
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
48
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,
51
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
54
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
59
of electricity or heat. Compared to existing power-to-heat solutions [9][10], the novelty of
60
these concepts relies on the inclusion of on-site conversion of wind energy into heat. In
61
particular, we define WTES as an innovative composition of state-of-the-art technologies, i.e.
62
wind energy converters, thermal storage and, depending on the application, a thermal
63
engine (Figure 1).
64
65
Figure 1: Basic concept of WTES
66
Due to their capability to work with high temperature heat, WTES can be potentially used for
67
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
69
measures or the development of renewable alternatives to fossil-fired combined heat and
70
power (CHP) plants. In this setup, WTES combine the systemic advantages of steam power
71
plants (i.e. rotating mass) with the use of the renewable resource wind.
72
The central element of WTES is the thermal energy storage. Its purpose is to balance
73
intermittent heat generation and demand. Available technologies are latent heat storage,
74
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
77
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
81
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
84
former is primarily based on the use of retarders for conversion of rotational energy into heat
85
within a wind turbine. Technological realizations of retarders are on the one hand
86
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,
88
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
92
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
96
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
118
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
121
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
125
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]
Rated power of
wind energy
converter(s) [MW]
Thermal storage
capacity [MWh]
Small
0.023
0.005 0.027
0.015
Medium
11.8
2.5 13.47
18.8
Large
118
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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606
607
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
... Many current power-to-heat projects and research approaches use excess wind generation [4][5][6][7][8]. But, converting the wind turbines' mechanical energy directly into heat ( Fig. 1) could save one conversion step and therefore be more cost-effective [9] and efficient [10,11]. Hence, the development of windthermal converters could make renewable heat more affordable and consequently provide the last of the three pillars of energy sustainability. ...
... We found three different concepts to convert wind energy directly into heat: compression, friction, and induction; or a combination of two concepts [9]. In all proposed devices, wind energy is converted into rotational energy by the rotor of the wind turbine. ...
... Similar to wind to power converters, direct drive [27,42,46] and gearbox-type [43] windthermal converters are proposed for both vertical- [31,48,67] and horizontal-axis [9,38,42,43] wind turbines. ...
Article
Full-text available
Windthermal turbines convert wind directly into thermal energy. Albeit it is an uncharted field of research, the overall system efficiency and costs of fully developed windthermal turbines are promising; since they can contribute to a sustainable energy transition. We identify the current state of the art of windthermal conversion principles, technology maturity, applications, substitutes, advantages and disadvantages. To scope relevant literature, we follow the Joanna Briggs Institutes selection and screening process resulting in 61 relevant publications from which we identified three main conversion types, namely compression-, friction-, and induction-based windthermal devices. These devices can directly supply thermal energy for space heating or industrial processes, work as a component of wind-powered thermal energy systems, short WTES, or can substitute any conventional or renewable heat device. Although heat is the lowest form of energy, windthermal applications could provide cheap renewable energy that can be stored easily enhancing security of supply. However, these technologies are currently on laboratory-scale, and we suggest scaling up the existing prototypes to engineering-scale. Finally, due to a missing general terminology, we propose to establish one of the terms windthermal energy, ventothermal energy or anemothermal energy to distinguish these specific wind energy conversion technologies.
... The cost estimation showed that WTES has a cost advantage in long-duration storage applications over other conventional solutions such as storing wind power in electrical energy storage. Later, Cao et al. [56] investigated various heat generation technologies for a WTES that is used for space heating. Different system parameters such as system scales and capacity factors of wind power were taken into account for cost estimation. ...
... The energy costs of different configurations for WTES were estimated in [55], [56], but those costs are calculated without considering wind power profiles. Unlike standalone energy storage systems, the input power to a GIES system is determined by its generation units, and it cannot be controlled if the system is powered by a VRE source such as wind power or solar energy. ...
... Cao et al. [56] investigated the cost of wind-powered heating systems configured with different heating technologies such as resistance heaters, heat pumps and hydrodynamics retarders (see Figure 2.3). The system has heat storage with the capacity to supply two to ten hours of peak heat demand. ...
Thesis
The focus of this research is a techno-economic assessment of a wind-powered thermal energy system (WTES), which directly converts wind power into heat at the generation site and stores this heat in thermal energy storage for later use. Compared to conventional systems that convert wind to electricity, WTES can be a cost-effective solution for producing heat from wind power due to its minimal energy conversion steps. Two challenges in the development of WTES are investigated in this work. Firstly, the technology that converts the kinetic energy from wind turbine rotors into heat has not been thoroughly investigated yet. Several studies have investigated the wind-driven heater for water heating but not for high-temperature heat generation, which enables a wider range of applications. Secondly, the role of WTES in the future energy system is unexplored. A few studies have estimated the energy costs of WTES for electricity and heat generation, but generation and demand profiles and required storage systems have not been considered. In this research, eddy current heaters are selected to be investigated for wind-to-heat conversion due to their potential for high-temperature heat generation at low rotational speeds. The key design parameters and technical challenges of this technology were analysed, and a proof-of-concept device was designed and constructed for parametric study. The role of WTES for electricity and heat generation was investigated by operational simulations with wind power and system output profiles being taken into account. The energy cost of WTES was evaluated and compared with the cost of the systems that can provide similar services, such as electricity-generating wind turbines integrated with electrical or thermal energy storage. The analysis suggests that, for electricity generation, WTES has a cost advantage when a high fraction (e.g. 73-94%) of wind power is to charge storage, but the simulation results for different scenarios show that this fraction for WTES is not over 70%. Furthermore, the capital costs and conversion efficiency of different components for wind-to-heat conversion are reviewed and analysed. The results show that the energy cost of WTES for heat generation could be lower than other wind-to-heat conversion routes (e.g. electrical heating or hydrogen heating). However, converting wind power to heat at the generation site limits the use of wind energy in other sectors or energy networks. This study is the first comprehensive assessment of WTES in different aspects and can be the foundation of future research.
Article
The thermophysical properties of a working-fluid play an important role in the process of stirring-heating. The heating process of stirring is accompanied by two processes: the friction between the solid mechanism and the working-fluid and the viscous dissipation of the working liquid. Traditionally, the sensible heat of water-based working-fluids is low, while that of oil-based working-fluids is higher, but the load capacity is relatively low. In order to find a balance between the two, an optimal stirring working-fluid should be selected. In this study, an experimental method was used to study the heating process of 30 kinds of working-fluids. The numerical evaluation model of the effects of thermophysical properties on the comprehensive evaluation index of heat (CEIH) was established by multiple linear regression methods, and a computational fluid dynamics (CFD) tool was used to analyze the heat generation and flow field of different working-fluids in the stirring-heating device. The results show that viscous dissipation is the most important way of stirring-heating. CFD can completely replace the experiment to study the heating effect of stirring. The thermophysical properties of the working-fluid affect the upper circulation and the overall velocity of the double circulation flow. The experimental results and regression model analysis show that specific heat capacity has the greatest effect on the heating effect, but density will also play a positive role in the stirring-heating. Water-based salt solutions such as KCl can achieve a better heating effect, and oil-based working-fluids are not always the best choice.
Article
Using renewable energy for heating has attracted more attentions in recent years. In this study, a novel wind-to-heat system that uses the wind turbine to drive the compressor directly, is proposed. Since there is no intermediate electric energy conversion link, the energy loss of the system is evidently reduced compared with conventional wind-heating systems. To verify the performance of this system, a prototype of that was established in the north of China and a series of tests had been conducted under different wind conditions. A four-stage smart control strategy for this system was developed by considering different response dynamics of the wind turbine and heat pump. It guarantees the system having high heating efficiency over the entire wind speed range. According to the test results, the rated heating capacity of the system is 150 kW with the rated wind speed being 9 m/s. The coefficient of performance of the system is approximately 3, the maximum power coefficient is 0.45, and the primary energy ratio exceeds 100%. At last, the inherent characteristics of the system are revealed and possibilities of further optimizations of the system are discussed.
Article
Heating with wind and solar energy is an effective way to reduce carbon dioxide emissions. Vapor Compression Heat Pumps (VCHP) were generally used to improve the utilization rate of wind power. However, normal VCHP driven by wind power or solar energy has low performances in low temperature environment and low supply temperature of heating water, and it is also difficult to achieve continues and stable heating because of the intermittence of wind power. The present paper introduces a new integrated heat pump system, in which a VCHP absorbs heat from the environment and sends it to an Absorption Heat Pump (AHP) as its low temperature heat source after temperature lift. Thermal storage system is also equipped for continues heating and it serves as the driving force of the AHP. The results show that the integrated heat pump can produce heating water at 50 °C or even higher with a COP of about 1.42 when the environment temperature is as low as −30 °C. Also, the power consumption of the VCHP accounts for only 5%–18% of the total energy input. This indicates that the energy consumed by the integrated heat pump can be mainly from off-peak electricity produced by the wind turbine.
Article
The Climate Change (Scotland) Act sets greenhouse gases net-zero emissions targets by 2045, and wind energy can be used as the alternative energy source to reduce domestic energy consumption. Aberdeen, Edinburgh, Glasgow, and Carlisle were selected as typical regions based on population density, energy consumption, and wind resources, and a wind turbine-driven heat pump system is designed to heat detached houses by using DesignBuilder and TRNSYS. Wind heating efficiency, load satisfaction, CO2 emission reduction, and profitability indicators are proposed to evaluate the performance. Results show that wind turbines can meet energy requirements of detached houses with the assistance of the municipal grid. The wind heating efficiency and the load satisfaction probability reached 69% and 98% in these four regions, respectively. Compared to the modeled emissions, the annual CO2 emissions reduction ratio is 3.0–6.5%. Increasing the capacity of batteries and wind turbines can increase wind heating efficiency, load satisfaction, and CO2 emission reduction. The increase of the wind turbine's capacity can reduce the wind heating efficiency. Since the low profitability could affect the economic feasibility of the system, increasing the government economic incentives and reducing costs are of great significance to the promotion of this system in Scotland.
Thesis
Full-text available
Driven by carbon-neutrality, the deployment of photovoltaic arrays and wind turbines increases rapidly in the power, heating and mobility sectors. To comply with the needs of each sector, these renewable energy systems are coupled with different energy storage technologies and energy conversion technologies, resulting in a diverse set of hybrid renewable energy systems. Designing such a hybrid renewable energy system requires information on the technical, economic and environmental performance of each component, as well as information on the climate and energy demand. These parameters are likely to vary during the system lifetime (i.e., aleatory uncertainty), and data resources on these variations are usually limited (i.e., epistemic uncertainty). Considering these uncertainties in the design of hybrid renewable energy systems is still an exception rather than the norm. Although, disregarding uncertainty can result in a drastic mismatch between simulated and actual performance, and thus lead to a kill-by-randomness of the system. In other fields, such as structural mechanics and aerospace engineering, robust design optimization has already resulted in improved product quality, by providing designs that are less sensitive to the random environment. Despite its potential, applying robust design optimization on hybrid renewable energy systems is not yet studied. Therefore, the research question of this thesis reads: What is the added value of robust design optimization to hybrid renewable energy systems? To answer this question, I followed three steps. First, I developed a surrogate-assisted robust design optimization framework, using state-of-the-art optimization and uncertainty quantification algorithms. Despite being limited to problems with a low stochastic dimension (i.e., less than 15 uncertainties), this framework allows defining robust designs for two-component renewable energy systems, optimized for a single quantity of interest. However, hybrid renewable energy systems are typically multi-component systems, with multiple, cross-field objectives (i.e., technical, economic and environmental objectives). Hence, in the second step of this thesis, I modified the uncertainty quantification algorithm. This modification allowed to handle a large stochastic dimension, and thus to define robust designs for complex, multi-component hybrid renewable energy systems in a holistic context. In the third and final step, I proposed an imprecise probability method, to distinguish between epistemic and aleatory uncertainty on a parameter. In this new formulation, the robust design is optimized for the irreducible, aleatory uncertainty, and the global sensitivity analysis is reserved for the reducible, epistemic uncertainty. The robust design optimization algorithm has been applied on three specific hybrid renewable energy systems: a photovoltaic-battery-hydrogen system, a renewable-powered hydrogen refueling station and a photovoltaic-battery-heat pump system with thermal storage. The results indicate that the robust designs are characterized by a higher penetration of renewable energy systems and by considering energy storage: Coupling battery storage and hydrogen storage to a grid-connected photovoltaic array reduces the standard deviation of the levelized cost of electricity by 42%; A photovoltaic-battery-heat pump with thermal storage system reduces the standard deviation of the levelized cost of exergy by 36%, as opposed to the photovoltaic-battery-gas boiler system; Shifting towards a bus fleet that partly consists of hydrogen-fueled buses (54% of the fleet) reduces the standard deviation of the levelized cost of driving (36%), the mean of the carbon intensity (46%) and the standard deviation of the carbon intensity (51%), at the expense of a limited increase in the mean of the levelized cost of driving (11%). Conclusively, robust design optimization provides an added value in the design of hybrid renewable energy systems, the method complies with the computational burden of holistic design expectations, and it is adaptable to more advanced uncertainty characterization techniques.
Article
Hydrogen production and clean heating from renewable power are promising methods to promote renewable energy consumption and reduce carbon emission. This paper is concentrated on the cooperative planning and operation problems of Wind-Hydrogen-Heat multi-agent energy system. A cooperative planning and operative model for the Wind-Hydrogen-Heating multi-agent energy system is proposed based on the Nash bargaining game theory. This cooperative model is transformed into two subproblems on the alliance planning and operation cost minimization problem and the payment bargaining problem. To protect the privacy of each participant, two distributed algorithms are proposed based on the Alternating Direction Method of Multipliers to solve the two subproblems. Finally, the effectiveness of the proposed cooperative model and distributed algorithms are demonstrated. Simulation results demonstrate that the proposed cooperative model can improve the benefits of both each participant and the cooperative alliance significantly. Furthermore, the wind power curtailment can be reduced through cooperation. And the decline of feed-in tariff of wind power will incentivize the cooperation of Wind-Hydrogen-Heat agents to improve their own benefits.
Thesis
France aims to massively develop intermittent renewable energies --- wind and photovoltaic --- while reducing the share of dispatchable sources, in this case, nuclear power. This paradigm shift implies rethinking the management of energy systems. Indeed, renewables' variable nature generates a need for flexibility on different time-scales, from day to year. As dispatchable means' flexibility can no longer be relied on, this thesis questions the potential of other means to meet this need: electricity storage, oversized production and heating networks.Faced with the need for a systemic approach, we developed simple models to enhance the understanding of the interdependencies between production and storage. The optimized indicators are economic (€), but also environmental: embodied energy and greenhouse gas emissions over the entire life cycle. The performances of the systems considered are those of today and their development is limited by resource and space availability. Without going into the precise details of how each technology works, this physical approach points out optimal operation areas for the different technologies and the difficult cases for which solutions are still lacking.First, the need for flexibility generated for different intermittency penetration rates is quantified for several time scales. It enables us to compare the potential of different electricity storage technologies --- at each of these scales --- to bring production and consumption in phase. The results show that long time-scales --- typically seasonal storage --- require the largest investments for low profitability. The competition mechanisms between several storages and oversizing are then analyzed. It shows how the optimum solutions use complementary flexibility means. The study then addresses the potential of coupling between the electrical grid and the heating grid as a means of flexibility, particularly for the management of long-term needs.This thesis work focuses on the French scale, although the methodology is applicable elsewhere.
Article
Full-text available
Combining photovoltaic arrays with batteries, heat pumps and thermal storage further decarbonizes the heating sector. When evaluating the performance of such systems, the parameters are either fixed, or based on generic ranges, or characterized by precise distributions inferred from limited information. These assumptions result in suboptimal designs, for which the actual performance differs drastically from simulations. To address these limitations, we consider the effects of limited information (epistemic uncertainty) on the natural variability (aleatory uncertainty) through probability-boxes. First, we performed a robust design optimization on the natural variability of the levelized cost of exergy, followed by a sensitivity analysis on the effects of limited information on the optimized designs. This paper provides the least-sensitive designs to natural variability and effective actions to reduce the effects of limited information. The results indicate that a photovoltaic-battery-heat pump configuration achieves higher robustness towards aleatory uncertainty than a photovoltaic-battery-gas boiler configuration. To determine the true-but-unknown performance and ro-* Corresponding author bustness of the optimized designs, clarifying the grid electricity contract and adopting specific energy demand profiles are the main actions, while considering generic technology models contributes little to the epistemic uncertainty.
Article
Full-text available
One of the major challenges of renewable energy systems is the inherently limited dispatchability of power generators that rely on variable renewable energy (VRE) sources. To overcome this insufficient system flexibility, electrical energy storage (EES) is a promising option. The first contribution of our work is to address the role of EES in highly renewable energy systems in Europe. For this purpose, we apply the energy system model REMix which endogenously determines both capacity expansion and dispatch of all electricity generation as well as storage technologies. We derive an EES capacity of 206 GW and 30 TWh for a system with a renewable share of 89%, relative to the annual gross power generation. An extensive sensitivity analysis shows that EES requirements range from 126 GW and 16 TWh (endogenous grid expansion) to 272 GW and 54 TWh (low EES investment costs). As our second contribution, we show how the spatial distribution of EES capacity depends on the residual load, which—in turn—is influenced by regionally predominant VRE technologies and their temporal characteristics in terms of power generation. In this sense, frequent periods of high VRE excess require short-term EES, which naturally feature low power-related investment costs. In contrast, long-term EES with low energy-related costs are characteristic for regions where high amounts of surplus energy occur. This relationship furthermore underlines how EES capacity distribution is implicitly influenced by technical potentials for VRE expansion.
Article
Full-text available
The Heat Roadmap Europe (HRE) studies estimated a potential increase of the district heating (DH) share to 50% of the entire heat demand by 2050, with approximately 25–30% of it being supplied using large-scale electric heat pumps. This study builds on this potential and aims to document that such developments can begin now with technologies currently available. We present a database and the status of the technology and its ability of expansion to other European locations by reviewing experiences aimed at further research or application in the heating industry. This is based on a survey of the existing capacity of electric large-scale heat pumps with more than 1 MW thermal output, operating in European DH systems. The survey is the first database of its kind containing the technical characteristics of these heat pumps, and provides the basis for the analysis of this paper. By quantifying the heat sources, refrigerants, efficiency and types of operation of 149 units with 1580 MW of thermal output, the study further uses this data to analyze if the deployment of this technology on a large-scale is possible in other locations in Europe. It finally demonstrates that the technical level of the existing heat pumps is mature enough to make them suitable for replication in other locations in Europe.
Article
Reducing energy consumption and increasing the use of renewable energy in the building sector are crucial to the mitigation of climate change. Wind power driven heat pumps have been considered as a sustainable measure to supply heat to the detached houses, especially those that even do not have access to the electricity grid. This work is to investigate the dynamic performance of a heat pump system driven by wind turbine through dynamic simulations. In order to understand the influence on the thermal comfort, which is the primary purpose of space heating, the variation of indoor temperature has been simulated in details. Results show that the wind turbine is not able to provide the electricity required by the heat pump during the heating season due to the intermittent characteristic of wind power. To improve the system performance, the influences of the capacity of wind turbine, the size of battery and the setpoint of indoor temperature were assessed. It is found that increasing the capacity of wind turbines is not necessary to reduce the loss of load probability; while on the contrary, increasing the size of battery can always reduce the loss of load probability. The setpoint temperature clearly affects the loss of load probability. A higher setpoint temperature results in a higher loss of thermal comfort probability. In addition, it is also found that the time interval used in the dynamic simulation has significant influence on the result. In order to have more accurate results, it is of great importance to choose a high resolution time step to capture the dynamic behaviour of the heat supply and its effect on the indoor temperature.
Article
Higher shares of variable renewable energy (VRE) in energy systems reduce electricity spot prices at times when the supply of these sources are most abundant, leading to a lower market value per unit for these sources compared to energy sources with a constant or adjustable supply. This disadvantage for VRE can be offset by evolving the energy system towards wider market integration and flexible demand or supply. This study analyses how increased integration of heat and power markets by use of power-to-heat in district heating system could increase the value VRE sources in the Northern European power system. For the quantification, we apply a partial equilibrium model with a detailed representation of power and district heat generation for a likely 2030 energy system. The results show a markedly increase in VRE market value when installed capacity of power-to-heat is increased, especially in scenarios with a large Nordic power surplus. The study concludes that power-to-heat solutions in district heating systems can increase system flexibility in a short time perspective that considers hours to weeks, but also in a longer perspective that accounts for the significant inter-annual variability in hydropower supply.
Article
As a clean and renewable energy, wind power gets a rapid growth in recent years. With the increasing proportion of wind power generation, the fluctuation and intermittency of wind energy impedes the safe and stable operation of national power grids, which causes wind curtailment and energy waste, hindering further development of wind power industry in China. To solve this problem, wind heating conversion was proposed. However, long distance transmission between wind fields and residential areas for thermal energy is an urgent issue for wind heating. This paper presents a novel wind heating conversion and long distance transmission system. A simple device was utilized for wind heating conversion in the present system, then thermal energy was transported to heat demand site through latent heat transmission of the working fluids. A model of the novel system was built and thermodynamics analysis showed that maximum transmission distance of the novel system could extended to 240 km, 9.6 times of that of typical hot water transmission system. And the novel system also could cut down the cost by greatly reducing pump work and pipe diameter. In addition, efficiency and circulation ratio was almost unchanged while wind power density increased from 350 W/m² to 650 W/m².
Thesis
Balancing of intermittent renewable power generation from wind and solar energy is one of the central challenges within the energy system transformation towards a more sustainable supply. This work addresses the potential role of flexible electric loads and power-controlled operation of combined heat and power (CHP) plants in meeting increasing balancing needs in Germany. It conducts an enhancement of the cross-sectoral REMix model, which is designed for the preparation and assessment of energy supply scenarios based on a system representation in high spatial and temporal resolution. The analysis is composed of three fundamental parts. The first part is dedicated to the quantification of theoretical potentials for demand response (DR), district heating (DH) and industrial CHP in Europe. Special attention is given to the geographic distribution of potentials, as well as the derivation of hourly heat and electricity demand profiles. In the second part, the linear optimization model within REMix is extended by DR and the heating sector, enabling economic assessments of the balancing function of flexible electric loads and power-controlled heat supply. In the third part, REMix is applied to assess the future energy supply in Germany, making use of the model enhancements and identified potentials. In order to account for different renewable energy (RE) and grid capacity development paths, as well as transport and heat sector structures, nine scenarios are considered. For each scenario, least-cost dimensioning and operation of DR capacities, as well as heat supply systems are evaluated. According to the REMix results, the application of DR is mostly limited to short time peak shaving of the residual load. This implies that its focus is on the provision of power, not energy. As a consequence of different cost structures, the exploitation of available DR potentials is attributed almost exclusively to industrial and commercial sector loads, whereas those in the residential sector are hardly accessed. The model results indicate that the temporal availability of DR potentials, as well as their characteristic intervention and shift times are particularly suited for a combination with PV power generation. In the simulations, power-controlled heat supply has proven to be an effective measure to increase RE integration. It is achieved by a modified operation pattern of CHP and -- to a lower extent -- heat pumps (HP) enabled by thermal energy storage (TES) on the one hand, and an utilization of surplus power for heating purposes on the other. Due to the greater potential and thus longer storage times of TES, as well as the comparatively low investment costs of electric boilers, an enhanced coupling between power and heat sector is found to be especially favorable in combination with wind power utilization. Load shifting across all sectors provides substantial amounts of positive balancing power, which can substitute other firm generation capacity. The highest load reduction is achieved by controlled electric vehicle charging, lower contributions come from adjusted HP operation and other DR. As a consequence of higher RE integration, load shifting and power-controlled heat supply can contribute substantially to CO2 emission reductions in Germany. However, this is only the case if the additional balancing potentials are not applied as well for an economically motivated shift in power generation from low-emitting to high-emitting fuels. Furthermore, load flexibility and enhanced power-heat-coupling can enable energy supply cost reductions, arising from the substitution of back-up power plant capacity on the one hand, and a more cost-efficient power and heat supply on the other. The model application reveals that electric load shifting and power-controlled CHP operation are not competing but complementary measures in the realization of higher RE integration and lower back-up capacity demand. Negative interferences between both balancing options are found to be very small. On the contrary, they even promote each other, for example in the reduction of RE curtailments. Based on the REMix results it can be concluded that both DR and power-controlled heat supply enabled by TES are important elements in a future German energy system mainly relying on renewable sources.
Chapter
The purpose of this paper is to present the design and performance tests of a wind powered heat pump. The system consists of a modified heat pump, a vertical axis wind turbine and a mechanical coupling between the heat pump and the wind turbine. Such a system either alone or combined with solar collectors has the potential for application to residential heating and air conditioning.