- Email: [email protected]
Flexibility in thermal grids: a review of short-term storage in district heating distribution networks
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Energyonline Procedia 00 (2018) 000–000 Available onlineatat www.sciencedirect.com Available www.sciencedirect.com Energy Procedia 00 (2018) 000–000
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www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia 158 Energy Procedia 00(2019) (2017)2430–2434 000–000 www.elsevier.com/locate/procedia
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China
Flexibility in thermal grids: a review of short-term storage in district Thethermal 15th International Heating and Coolingin district Flexibility in grids: Symposium a reviewonofDistrict short-term storage heating distribution networks heating distribution networks Assessing the feasibility of using the heat demand-outdoor Jay Hennessyab* , Hailong Lib† , Fredrik Wallinbb, Eva Thorinbb ab* b† Jay Hennessy , Hailong Li , Fredrik Wallin heat , Eva Thorin temperature function for a long-term district demand forecast RISE Research Institutes of Sweden, Box 857, SE-501 15 Borås, Sweden a
b
a School of Business, Society and Engineering, Mälardalen 23 Västerås, Sweden RISE Research Institutes of Sweden, Box 857,University, SE-501 15SE-721 Borås, Sweden a,b,c a a b c b School of Business, Society and Engineering, Mälardalen University, SE-721 23 Västerås, Sweden
I. Andrić a
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract Future energy systems need to be more flexible. The use of cross-sector coupling in combination with thermal storage in thermal Future energy to be more The use cross-sector coupling in combination withstorage thermal in storage in thermal grids has beensystems shownneed to provide suchflexible. flexibility. Theofpresented study reviews how short-term district heating grids has been shownis used to provide such flexibility. Thewhat presented reviews how short-term in knowledge district heating distribution networks or modelled for flexibility, are the study most important parameters, and storage where the gaps Abstract distribution is used modelled forfor flexibility, what aredistrict the most important andexploited. where theSensible knowledge gaps remain. Thenetworks results show thatorthe potential flexibility from heating has parameters, not been fully thermal remain. The results show times that the potential flexibility fromand district heating not been fully exploited. thermal storage tanks are 50–100 cheaper thanfor electrical storage storage in thehas distribution network requiresSensible little additional Districttanks heating networks are commonly addressed instorage the of literature as onein of most solutions forlittle decreasing the storage 50–100 times cheaper than electrical and storage thethe distribution network requires additional investment in are infrastructure. In some countries, the majority district heating systems haveeffective sensible thermal storage tanks, with greenhouseingas emissions from the building sector. These systems require high investments which are returned through thewith heat investment infrastructure. In some countries, the majority of district heating systems have sensible thermal storage tanks, as much as 64 % of their capacity available for flexibility services. Initial results suggest that only smaller networks are prevented sales. Due to%distribution the changed climate andthebuilding renovation policies, demand in thenetworks futureand could decrease, as much as 64 of their capacity available for flexibility services. results suggest that only smaller are from using the network forconditions storage, but impacts ofInitial this type of use onheat the physical components theprevented capacity prolonging the investment return period. from using remain the distribution network storage, but the impacts of this of useThere on the andinthe capacity limitations unclear and show for a need for standardised methods fortype analysis. is aphysical growingcomponents interest, both Europe and The main scope ofunclear this paper to assess the theflexibility, heat demand – outdoor temperature demand limitations remain and is show a need forfeasibility standardised methods for analysis. There is aingrowing bothfor in heat Europe China, in the use of short-term storage in district heating of to using provide particularly the forminterest, of function ancillary services toand the forecast. The of Alvalade, in Lisbon (Portugal), was used as a case study. The district is consisted of 665 China, in the usedistrict of short-term storagelocated in heating to provide flexibility, particularly in the form ofaancillary services to the electricity grid, but implementations ofdistrict these techniques are rare. The presented study identifies number of remaining buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district electricity but should implementations of inthese are rare. flexibility The presented study identifies a number of remaining knowledge grid, gaps that be addressed ordertechniques to harness available in district heating. renovationgaps scenarios were be developed intermediate, deep).flexibility To estimate the error, obtained heat demand values were knowledge that should addressed(shallow, in order to harness available in district heating. compared with results from a dynamic heat demand model, previously developed and validated by the authors. Copyright © 2018 Elsevier Ltd. All rights reserved. ©The 2019 The Authors. Published by Elsevier Ltd. results showed that when only weather change is considered, the margin of error could be acceptable for someon applications th Copyright © 2018 Elsevier Ltd. All rights reserved. Conference Applied Selection and peer-review under responsibility of the scientific committee of the 10 International This an open accessdemand article under the CCthan BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) (the iserror in annual was responsibility lower 20% weather scenarios considered). However, after introducing Conference onrenovation Applied Selection and peer-review under of for the all scientific committee of the 10th International Energy (ICAE2018). Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). Energy (ICAE2018). The value of slope increased on average within the range of 3.8% up thermal to 8% inertia; per decade, corresponds to the Keywords: thermal grids;coefficient district heating and cooling; flexibility, curtailment, renewable energy; thermalthat storage decrease thermal in the number of heating hours of 22-139h during the heating season (depending on thethermal combination Keywords: grids; district heating and cooling; flexibility, curtailment, renewable energy; thermal inertia; storage of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.
© 2017 The Authors. Published by Elsevier Ltd. * Corresponding author (J. Hennessy). Tel.: +46-73-810-6005. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * E-mail address:author [email protected] Corresponding (J. Hennessy). Tel.: +46-73-810-6005. Cooling. † Corresponding (H. Li). Tel.: +46-21-103-159. E-mail address:author [email protected]
† E-mail address:author [email protected] Corresponding (H. Li). Tel.: +46-21-103-159. Keywords: Heat demand; Forecast; Climate change E-mail address: [email protected] 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018).
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.302
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Jay Hennessy et al. / Energy Procedia 158 (2019) 2430–2434 Author name / Energy Procedia 00 (2018) 000–000
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1. Introduction Flexibility of energy systems is an increasingly pressing issue. The Paris Agreement reinforces targets to cut greenhouse gas emissions with the increasing penetration of renewable energy sources (RES). As RES become increasingly competitive their growth is accelerating, with the International Energy Agency predicting that renewable electricity generation will grow 43 % between 2017 and 2022. This growth is mostly from volatile sources such as solar photovoltaics and wind power, and as these start to be introduced into a power system at a large scale, new kinds of flexibility measures are needed to balance the mismatches of supply and demand [1] at different timescales [2]. The short-term risk is that variability and uncertainty of RES can lead to high-cost curtailment of renewable generation and deployment of expensive fast-starting units [4]. Such variability is already seen today, for example China experienced as much as 20 % curtailment of wind power in 2015, a significant amount of lost energy considering it had 27 % of global wind power capacity [5]. Variation of generation from RES is also seen in production shortfalls, wind power production across the Nordic countries dipped to 2–3 % of nominal capacity in 2015. In the EU, such large variations are partly managed through cross-border interconnections, which allowed Denmark to generate a peak of 140 % of its electricity demand in 2015. It is suggested that both crossborder and cross-sector interconnectivity increase system utilisation of RES and system efficiency, but cross-sector interconnectivity gives the best system performance [6]. Many recent studies consider the flexibility of thermal grids to facilitate the integration of RES in both Europe and China, locations that have differing types of DH flow regulation [7,8] and different electricity market structures leading to different system solutions. Nomenclature CHP DH
combined heat and power (or co-generation) district heating
RES TES
renewable energy sources thermal energy storage
1.1. Definition of flexibility There is no general definition of flexibility in energy systems [2]. In their review of control strategies for district heating and cooling flexibility, Vandermeulen et al. [9] define flexibility as the ability to speed up or delay the input or output of energy into/out of a system. They further state that flexibility only requires that the system has inertia, or thermal capacity in the case of thermal grids. In a definition of generation flexibility, Bessa et al. [4] use factors such as ramp rate, minimum generation level, and start-up and shut-down time, which could be considered measures of the former definition. However, with their focus on inertia, Ref. [9] appears to ignore cross-sector interconnectivity, where the availability and capacities of coupling points between energy systems is also important. 1.2. Flexibility in thermal grids There are a large number of possible sources of energy system flexibility [1]. District heating (DH) networks have a proven track record of flexible operation [10] and possible sources of flexibility include, but are not limited to, combined heat and power (CHP) plants [10,11], power to heat [12], heat to power [13] and thermal energy storage (TES). To mitigate the uncertainty and variability of RES the use of storage devices has been identified as particularly valuable [4] and sensible TES is 50–100 times cheaper than electrical storage [14,15]. TES in thermal grids can be short-term – including heat storage tanks, thermal inertia in connected buildings, and the contents of the network pipeline (‘network storage’) – or long-term TES in boreholes, pits and tanks [16]. Short-term TES, considered here to be in the order of an hour up to a few days, is the most common and is used for production flexibility and peak-shaving of heat demand [16,17]. To consider how storage can facilitate energy system flexibility it is necessary to quantify the storage capacity available. In this study a review of short-term storage in DH distribution networks is presented, including centralised storage tanks and network storage, with the aim of identifying knowledge gaps and parameters with a high impact on performance. A focus is made on peer-reviewed research, published within the last few years. The scope is limited to sensible heat storage, being the most common.
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2. The use of short-term storage in thermal grids A comparison of the DH network short-term storage considered in the present study is shown in Table 1. Table 1. Comparison of short-term storage solutions and their advantages, disadvantages and research knowledge gaps. Type
Advantages
Disadvantages
Knowledge gaps
Centralised storage tanks
Often already existing in DH systems [16]; low cost [18]; operational benefits [19]; decreases total DH system annual operating cost [20]; provides up to 10 times more storage than network storage [18,21]; extends to medium-term (weekly) storage [20].
Greater investment cost compared to the use of network storage, payback period may exceed 10 years [20,22]; not all DH systems have tank TES [16,23].
For systems with TES tanks designed to be bigger than that needed for daily variations, their purpose or existing use and therefore their availability, is unclear.
Network storage
Minimal physical infrastructure investments required; some amount of network storage is available in all DH systems (but see also Disadvantages).
Additional temperature cycling may cause increased stresses on the physical components [9]; increased return temperatures would decrease efficiency [7]; smaller networks have insufficient capacity for storage beyond peak shaving [17]; to control mass flow for better control of storage, enduser control equipment must be deployed [24]; storage capacity decreases with mass flow, which, in Europe, decreases with reduced heat load [24].
Calculations of storage capacity are approximated and not standardised; modelling does not take account of additional stresses on pipes; there is no estimation of the threshold size of a network needed to enable storage.
2.1. Centralised storage tanks A centralised thermal storage tank installed next to a CHP is the most common TES configuration in DH [25]. In fact, in Sweden and Denmark, where thermal grids are prevalent, nearly all CHP plants have short-term sensible storage tanks to cover peak demand periods, enabling the plant peak capacity to be reduced and to operate at full capacity for a greater period [16,23]. The cost of this type of TES is approximately 500–3000 EUR/MWh [18,20,22]. In Denmark, DH steel tanks amount to approximately 50 GWh of storage, compared to an average daily demand of 115 GWh [18,21]. In Sweden, tank TES amounts to more than 42 GWh, against an average daily demand of 156 GWh [26,27], with 62 % of DH systems that deliver the majority of DH in Sweden having tank TES [23,26]. An estimated 27 GWh or 64 % of this storage is available for flexibility in addition to expected daily variations [26]. Kiviluoma and Meibom [19] considered the cost optimisation for investments of additional sensible storage tanks, electric boilers and heat pumps in a thermal grid with a CHP, to facilitate the integration of RES. They show that additional tank TES creates benefits for many production types by shifting demand in time. 2.2. Network storage Many of the previous works [16,19,28–31] do not consider the contents of the pipeline network as storage. In the classic control of DH networks, the supply temperature of the heat supply units is varied such that heat supply is equal to demand, causing peaks of heat load [7,9]. Peak-shaving aims to counteract this through pre-loading of heat into the network [9], but is still driven by the heat load. Thermal grid TES for RES integration is driven primarily by supply and demand of electricity, rather than heat load. For this purpose, the scale of TES capacity available from the network may be significant. In Denmark, with an average daily DH demand of 115 GWh, Lund [18,21] approximates the total national storage capacity of the network, based on a 10 K increase, as 5 GWh, equivalent to 10 % of the capacity of all DH steel tanks. In a single, large thermal grid, such as that of Helsinki, with an average daily demand of 17–20 GWh [32], the capacity is estimated to be 1.2 GWh based on 15 K increase [33]. Calculations of the network storage capacity continue to be made based on a range of broad approximations. It is common to assume that the supply temperature can be increased by a limited number of degrees, either 10 K, 15 K or 20 K [17,18,33]. Additional constraints, such as a maximum supply temperature are sometimes included [17,33]. Some studies assume only half the contents of the network can be used [18,24], i.e. not the return pipes, to limit the
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influence on the return temperature, others assume the whole contents [33]. In some cases, specific national design constraints are added, such as the maximum temperature gradient, or rate of change per minute, and can be limited further by individual operators to avoid unnecessary thermal stresses [34]. The supply from different production units may also be limited to a difference of 10 K in relation to the other units [34]. Vandermeulen et al. [9] comment that more frequent cycling between higher and lower temperatures can lead to faster development of cracking in steel pipes. Pipe joints are particularly affected by mechanical stresses caused by large temperature differences. Generalised methods exist to calculate stresses [7], however in the literature these have not been applied to the additional use of the network for storage. If such use leads to an overall temperature increase this could also decrease the system efficiency. Using the network as storage for peak-shaving has been shown to increase distribution losses by 0.3 %, however overall cost is reduced [17]. Higher return temperatures would affect plant efficiencies, with the associated cost for 27 Swedish DH networks estimated to be 0.3– 3.8 SEK.MWh-1.K-1 (approximately 3–38 EUR.MWh-1.K-1) [7]. In China, constant flow regulation operation should be changed to decouple primary and secondary DH networks [8]. 3. Discussion This study omitted some other forms of short-term storage in thermal grids. Literature on distributed TES devices in DH are less common [25] but includes, for example, a comparison of centralised TES with highly distributed TES in a small theoretical heat network for flexible CHP operation [29]. The use of the thermal inertia of DH-connected buildings for demand management and heat storage has also seen significant interest recently [20]. Connected buildings are considered in the present study as outside the DH system, but building inertia is increasingly used in the literature to increase the integration of RES in DH [9,25,28,30,31] and for peak shaving [30]. 4. Conclusions The presented study has focused on two types of short-term thermal energy storage in district heating distribution networks: centralised storage tanks and the contents of the pipeline network itself. It is evident from the increasing interest in these areas and the results of recent research that there is a strong potential to exploit these types of storage to provide flexibility in district heating systems, not least as ancillary services to the electricity grid, but evidence of implementations in networks are rare. It has been shown that in Sweden, where district heating is prevalent, the majority of district heating systems have sensible thermal storage tanks, with perhaps 64 % of their capacity available for flexibility services. Regarding network storage, the results suggest that only smaller networks are prevented from using the distribution network for storage, but the existing body of research is lacking in a number of areas, which prevents a more accurate calculation of national flexibility potentials. Not least, the impacts of this type of use on the physical components, the allowable temperature variations and therefore the capacity limitations, remain unclear. There is a need for standardised methods for analysis of network storage, taking account of the supply temperature effect on heat propagation, the resultant stresses on the network components, the effect of the return temperature on production efficiency and the resultant cost implications. Acknowledgements This study was part-financed by RISE Research Institutes of Sweden and conducted under the auspices of the Reesbe industrial post-graduate school, which is financed by the Knowledge Foundation (KK-stiftelsen), Sweden. References [1] Lund PD, Lindgren J, Mikkola J, Salpakari J. Review of energy system flexibility measures to enable high levels of variable renewable electricity. Renew Sustain Energy Rev 2015;45:785–807. doi:10.1016/j.rser.2015.01.057. [2] Alizadeh MI, Parsa Moghaddam M, Amjady N, Siano P, Sheikh-El-Eslami MK. Flexibility in future power systems with high renewable penetration: A review. Renew Sustain Energy Rev 2016;57:1186–93. doi:10.1016/j.rser.2015.12.200. [3] Huber M, Dimkova D, Hamacher T. Integration of wind and solar power in Europe: Assessment of flexibility requirements. Energy 2014;69:236–46. doi:10.1016/j.energy.2014.02.109.
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ScienceDirect ScienceDirect
Energyonline Procedia 00 (2018) 000–000 Available onlineatat www.sciencedirect.com Available www.sciencedirect.com Energy Procedia 00 (2018) 000–000
ScienceDirect ScienceDirect
www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia
Energy Procedia 158 Energy Procedia 00(2019) (2017)2430–2434 000–000 www.elsevier.com/locate/procedia
10th International Conference on Applied Energy (ICAE2018), 22-25 August 2018, Hong Kong, 10th International Conference on Applied Energy China(ICAE2018), 22-25 August 2018, Hong Kong, China
Flexibility in thermal grids: a review of short-term storage in district Thethermal 15th International Heating and Coolingin district Flexibility in grids: Symposium a reviewonofDistrict short-term storage heating distribution networks heating distribution networks Assessing the feasibility of using the heat demand-outdoor Jay Hennessyab* , Hailong Lib† , Fredrik Wallinbb, Eva Thorinbb ab* b† Jay Hennessy , Hailong Li , Fredrik Wallin heat , Eva Thorin temperature function for a long-term district demand forecast RISE Research Institutes of Sweden, Box 857, SE-501 15 Borås, Sweden a
b
a School of Business, Society and Engineering, Mälardalen 23 Västerås, Sweden RISE Research Institutes of Sweden, Box 857,University, SE-501 15SE-721 Borås, Sweden a,b,c a a b c b School of Business, Society and Engineering, Mälardalen University, SE-721 23 Västerås, Sweden
I. Andrić a
*, A. Pina , P. Ferrão , J. Fournier ., B. Lacarrière , O. Le Correc
IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France Abstract c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract Future energy systems need to be more flexible. The use of cross-sector coupling in combination with thermal storage in thermal Future energy to be more The use cross-sector coupling in combination withstorage thermal in storage in thermal grids has beensystems shownneed to provide suchflexible. flexibility. Theofpresented study reviews how short-term district heating grids has been shownis used to provide such flexibility. Thewhat presented reviews how short-term in knowledge district heating distribution networks or modelled for flexibility, are the study most important parameters, and storage where the gaps Abstract distribution is used modelled forfor flexibility, what aredistrict the most important andexploited. where theSensible knowledge gaps remain. Thenetworks results show thatorthe potential flexibility from heating has parameters, not been fully thermal remain. The results show times that the potential flexibility fromand district heating not been fully exploited. thermal storage tanks are 50–100 cheaper thanfor electrical storage storage in thehas distribution network requiresSensible little additional Districttanks heating networks are commonly addressed instorage the of literature as onein of most solutions forlittle decreasing the storage 50–100 times cheaper than electrical and storage thethe distribution network requires additional investment in are infrastructure. In some countries, the majority district heating systems haveeffective sensible thermal storage tanks, with greenhouseingas emissions from the building sector. These systems require high investments which are returned through thewith heat investment infrastructure. In some countries, the majority of district heating systems have sensible thermal storage tanks, as much as 64 % of their capacity available for flexibility services. Initial results suggest that only smaller networks are prevented sales. Due to%distribution the changed climate andthebuilding renovation policies, demand in thenetworks futureand could decrease, as much as 64 of their capacity available for flexibility services. results suggest that only smaller are from using the network forconditions storage, but impacts ofInitial this type of use onheat the physical components theprevented capacity prolonging the investment return period. from using remain the distribution network storage, but the impacts of this of useThere on the andinthe capacity limitations unclear and show for a need for standardised methods fortype analysis. is aphysical growingcomponents interest, both Europe and The main scope ofunclear this paper to assess the theflexibility, heat demand – outdoor temperature demand limitations remain and is show a need forfeasibility standardised methods for analysis. There is aingrowing bothfor in heat Europe China, in the use of short-term storage in district heating of to using provide particularly the forminterest, of function ancillary services toand the forecast. The of Alvalade, in Lisbon (Portugal), was used as a case study. The district is consisted of 665 China, in the usedistrict of short-term storagelocated in heating to provide flexibility, particularly in the form ofaancillary services to the electricity grid, but implementations ofdistrict these techniques are rare. The presented study identifies number of remaining buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district electricity but should implementations of inthese are rare. flexibility The presented study identifies a number of remaining knowledge grid, gaps that be addressed ordertechniques to harness available in district heating. renovationgaps scenarios were be developed intermediate, deep).flexibility To estimate the error, obtained heat demand values were knowledge that should addressed(shallow, in order to harness available in district heating. compared with results from a dynamic heat demand model, previously developed and validated by the authors. Copyright © 2018 Elsevier Ltd. All rights reserved. ©The 2019 The Authors. Published by Elsevier Ltd. results showed that when only weather change is considered, the margin of error could be acceptable for someon applications th Copyright © 2018 Elsevier Ltd. All rights reserved. Conference Applied Selection and peer-review under responsibility of the scientific committee of the 10 International This an open accessdemand article under the CCthan BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) (the iserror in annual was responsibility lower 20% weather scenarios considered). However, after introducing Conference onrenovation Applied Selection and peer-review under of for the all scientific committee of the 10th International Energy (ICAE2018). Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. scenarios, the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). Energy (ICAE2018). The value of slope increased on average within the range of 3.8% up thermal to 8% inertia; per decade, corresponds to the Keywords: thermal grids;coefficient district heating and cooling; flexibility, curtailment, renewable energy; thermalthat storage decrease thermal in the number of heating hours of 22-139h during the heating season (depending on thethermal combination Keywords: grids; district heating and cooling; flexibility, curtailment, renewable energy; thermal inertia; storage of weather and renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and improve the accuracy of heat demand estimations.
© 2017 The Authors. Published by Elsevier Ltd. * Corresponding author (J. Hennessy). Tel.: +46-73-810-6005. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * E-mail address:author [email protected] Corresponding (J. Hennessy). Tel.: +46-73-810-6005. Cooling. † Corresponding (H. Li). Tel.: +46-21-103-159. E-mail address:author [email protected]
† E-mail address:author [email protected] Corresponding (H. Li). Tel.: +46-21-103-159. Keywords: Heat demand; Forecast; Climate change E-mail address: [email protected] 1876-6102 Copyright © 2018 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility the scientific 1876-6102 Copyright © 2018 Elsevier Ltd. All of rights reserved. committee of the 10th International Conference on Applied Energy (ICAE2018). Selection and peer-review under responsibility of the scientific committee of the 10th International Conference on Applied Energy (ICAE2018).
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. 1876-6102 © 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 – The 10th International Conference on Applied Energy. 10.1016/j.egypro.2019.01.302
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1. Introduction Flexibility of energy systems is an increasingly pressing issue. The Paris Agreement reinforces targets to cut greenhouse gas emissions with the increasing penetration of renewable energy sources (RES). As RES become increasingly competitive their growth is accelerating, with the International Energy Agency predicting that renewable electricity generation will grow 43 % between 2017 and 2022. This growth is mostly from volatile sources such as solar photovoltaics and wind power, and as these start to be introduced into a power system at a large scale, new kinds of flexibility measures are needed to balance the mismatches of supply and demand [1] at different timescales [2]. The short-term risk is that variability and uncertainty of RES can lead to high-cost curtailment of renewable generation and deployment of expensive fast-starting units [4]. Such variability is already seen today, for example China experienced as much as 20 % curtailment of wind power in 2015, a significant amount of lost energy considering it had 27 % of global wind power capacity [5]. Variation of generation from RES is also seen in production shortfalls, wind power production across the Nordic countries dipped to 2–3 % of nominal capacity in 2015. In the EU, such large variations are partly managed through cross-border interconnections, which allowed Denmark to generate a peak of 140 % of its electricity demand in 2015. It is suggested that both crossborder and cross-sector interconnectivity increase system utilisation of RES and system efficiency, but cross-sector interconnectivity gives the best system performance [6]. Many recent studies consider the flexibility of thermal grids to facilitate the integration of RES in both Europe and China, locations that have differing types of DH flow regulation [7,8] and different electricity market structures leading to different system solutions. Nomenclature CHP DH
combined heat and power (or co-generation) district heating
RES TES
renewable energy sources thermal energy storage
1.1. Definition of flexibility There is no general definition of flexibility in energy systems [2]. In their review of control strategies for district heating and cooling flexibility, Vandermeulen et al. [9] define flexibility as the ability to speed up or delay the input or output of energy into/out of a system. They further state that flexibility only requires that the system has inertia, or thermal capacity in the case of thermal grids. In a definition of generation flexibility, Bessa et al. [4] use factors such as ramp rate, minimum generation level, and start-up and shut-down time, which could be considered measures of the former definition. However, with their focus on inertia, Ref. [9] appears to ignore cross-sector interconnectivity, where the availability and capacities of coupling points between energy systems is also important. 1.2. Flexibility in thermal grids There are a large number of possible sources of energy system flexibility [1]. District heating (DH) networks have a proven track record of flexible operation [10] and possible sources of flexibility include, but are not limited to, combined heat and power (CHP) plants [10,11], power to heat [12], heat to power [13] and thermal energy storage (TES). To mitigate the uncertainty and variability of RES the use of storage devices has been identified as particularly valuable [4] and sensible TES is 50–100 times cheaper than electrical storage [14,15]. TES in thermal grids can be short-term – including heat storage tanks, thermal inertia in connected buildings, and the contents of the network pipeline (‘network storage’) – or long-term TES in boreholes, pits and tanks [16]. Short-term TES, considered here to be in the order of an hour up to a few days, is the most common and is used for production flexibility and peak-shaving of heat demand [16,17]. To consider how storage can facilitate energy system flexibility it is necessary to quantify the storage capacity available. In this study a review of short-term storage in DH distribution networks is presented, including centralised storage tanks and network storage, with the aim of identifying knowledge gaps and parameters with a high impact on performance. A focus is made on peer-reviewed research, published within the last few years. The scope is limited to sensible heat storage, being the most common.
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2. The use of short-term storage in thermal grids A comparison of the DH network short-term storage considered in the present study is shown in Table 1. Table 1. Comparison of short-term storage solutions and their advantages, disadvantages and research knowledge gaps. Type
Advantages
Disadvantages
Knowledge gaps
Centralised storage tanks
Often already existing in DH systems [16]; low cost [18]; operational benefits [19]; decreases total DH system annual operating cost [20]; provides up to 10 times more storage than network storage [18,21]; extends to medium-term (weekly) storage [20].
Greater investment cost compared to the use of network storage, payback period may exceed 10 years [20,22]; not all DH systems have tank TES [16,23].
For systems with TES tanks designed to be bigger than that needed for daily variations, their purpose or existing use and therefore their availability, is unclear.
Network storage
Minimal physical infrastructure investments required; some amount of network storage is available in all DH systems (but see also Disadvantages).
Additional temperature cycling may cause increased stresses on the physical components [9]; increased return temperatures would decrease efficiency [7]; smaller networks have insufficient capacity for storage beyond peak shaving [17]; to control mass flow for better control of storage, enduser control equipment must be deployed [24]; storage capacity decreases with mass flow, which, in Europe, decreases with reduced heat load [24].
Calculations of storage capacity are approximated and not standardised; modelling does not take account of additional stresses on pipes; there is no estimation of the threshold size of a network needed to enable storage.
2.1. Centralised storage tanks A centralised thermal storage tank installed next to a CHP is the most common TES configuration in DH [25]. In fact, in Sweden and Denmark, where thermal grids are prevalent, nearly all CHP plants have short-term sensible storage tanks to cover peak demand periods, enabling the plant peak capacity to be reduced and to operate at full capacity for a greater period [16,23]. The cost of this type of TES is approximately 500–3000 EUR/MWh [18,20,22]. In Denmark, DH steel tanks amount to approximately 50 GWh of storage, compared to an average daily demand of 115 GWh [18,21]. In Sweden, tank TES amounts to more than 42 GWh, against an average daily demand of 156 GWh [26,27], with 62 % of DH systems that deliver the majority of DH in Sweden having tank TES [23,26]. An estimated 27 GWh or 64 % of this storage is available for flexibility in addition to expected daily variations [26]. Kiviluoma and Meibom [19] considered the cost optimisation for investments of additional sensible storage tanks, electric boilers and heat pumps in a thermal grid with a CHP, to facilitate the integration of RES. They show that additional tank TES creates benefits for many production types by shifting demand in time. 2.2. Network storage Many of the previous works [16,19,28–31] do not consider the contents of the pipeline network as storage. In the classic control of DH networks, the supply temperature of the heat supply units is varied such that heat supply is equal to demand, causing peaks of heat load [7,9]. Peak-shaving aims to counteract this through pre-loading of heat into the network [9], but is still driven by the heat load. Thermal grid TES for RES integration is driven primarily by supply and demand of electricity, rather than heat load. For this purpose, the scale of TES capacity available from the network may be significant. In Denmark, with an average daily DH demand of 115 GWh, Lund [18,21] approximates the total national storage capacity of the network, based on a 10 K increase, as 5 GWh, equivalent to 10 % of the capacity of all DH steel tanks. In a single, large thermal grid, such as that of Helsinki, with an average daily demand of 17–20 GWh [32], the capacity is estimated to be 1.2 GWh based on 15 K increase [33]. Calculations of the network storage capacity continue to be made based on a range of broad approximations. It is common to assume that the supply temperature can be increased by a limited number of degrees, either 10 K, 15 K or 20 K [17,18,33]. Additional constraints, such as a maximum supply temperature are sometimes included [17,33]. Some studies assume only half the contents of the network can be used [18,24], i.e. not the return pipes, to limit the
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influence on the return temperature, others assume the whole contents [33]. In some cases, specific national design constraints are added, such as the maximum temperature gradient, or rate of change per minute, and can be limited further by individual operators to avoid unnecessary thermal stresses [34]. The supply from different production units may also be limited to a difference of 10 K in relation to the other units [34]. Vandermeulen et al. [9] comment that more frequent cycling between higher and lower temperatures can lead to faster development of cracking in steel pipes. Pipe joints are particularly affected by mechanical stresses caused by large temperature differences. Generalised methods exist to calculate stresses [7], however in the literature these have not been applied to the additional use of the network for storage. If such use leads to an overall temperature increase this could also decrease the system efficiency. Using the network as storage for peak-shaving has been shown to increase distribution losses by 0.3 %, however overall cost is reduced [17]. Higher return temperatures would affect plant efficiencies, with the associated cost for 27 Swedish DH networks estimated to be 0.3– 3.8 SEK.MWh-1.K-1 (approximately 3–38 EUR.MWh-1.K-1) [7]. In China, constant flow regulation operation should be changed to decouple primary and secondary DH networks [8]. 3. Discussion This study omitted some other forms of short-term storage in thermal grids. Literature on distributed TES devices in DH are less common [25] but includes, for example, a comparison of centralised TES with highly distributed TES in a small theoretical heat network for flexible CHP operation [29]. The use of the thermal inertia of DH-connected buildings for demand management and heat storage has also seen significant interest recently [20]. Connected buildings are considered in the present study as outside the DH system, but building inertia is increasingly used in the literature to increase the integration of RES in DH [9,25,28,30,31] and for peak shaving [30]. 4. Conclusions The presented study has focused on two types of short-term thermal energy storage in district heating distribution networks: centralised storage tanks and the contents of the pipeline network itself. It is evident from the increasing interest in these areas and the results of recent research that there is a strong potential to exploit these types of storage to provide flexibility in district heating systems, not least as ancillary services to the electricity grid, but evidence of implementations in networks are rare. It has been shown that in Sweden, where district heating is prevalent, the majority of district heating systems have sensible thermal storage tanks, with perhaps 64 % of their capacity available for flexibility services. Regarding network storage, the results suggest that only smaller networks are prevented from using the distribution network for storage, but the existing body of research is lacking in a number of areas, which prevents a more accurate calculation of national flexibility potentials. Not least, the impacts of this type of use on the physical components, the allowable temperature variations and therefore the capacity limitations, remain unclear. There is a need for standardised methods for analysis of network storage, taking account of the supply temperature effect on heat propagation, the resultant stresses on the network components, the effect of the return temperature on production efficiency and the resultant cost implications. Acknowledgements This study was part-financed by RISE Research Institutes of Sweden and conducted under the auspices of the Reesbe industrial post-graduate school, which is financed by the Knowledge Foundation (KK-stiftelsen), Sweden. References [1] Lund PD, Lindgren J, Mikkola J, Salpakari J. Review of energy system flexibility measures to enable high levels of variable renewable electricity. Renew Sustain Energy Rev 2015;45:785–807. doi:10.1016/j.rser.2015.01.057. [2] Alizadeh MI, Parsa Moghaddam M, Amjady N, Siano P, Sheikh-El-Eslami MK. Flexibility in future power systems with high renewable penetration: A review. Renew Sustain Energy Rev 2016;57:1186–93. doi:10.1016/j.rser.2015.12.200. [3] Huber M, Dimkova D, Hamacher T. Integration of wind and solar power in Europe: Assessment of flexibility requirements. Energy 2014;69:236–46. doi:10.1016/j.energy.2014.02.109.
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