- Email: [email protected]
District heating and ethanol production through polygeneration in Stockholm
Applied Energy 91 (2012) 214–221
Contents lists available at SciVerse ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
District heating and ethanol production through polygeneration in Stockholm Danica Djuric Ilic a,⇑, Erik Dotzauer b, Louise Trygg a a b
Division of Energy Systems, Department of Management and Engineering, Linköping University, SE-581 83 Linköping, Sweden School of Sustainable Development of Society and Technology, Mälardalen University, SE-72123 Västerås, Sweden
a r t i c l e
i n f o
Article history: Received 5 November 2010 Received in revised form 16 September 2011 Accepted 21 September 2011 Available online 19 October 2011 Keywords: District heating Polygeneration Biofuel Case study
a b s t r a c t Ethanol can be produced with little impact on the environment through the use of polygeneration technology. This paper evaluates the potential of integrating a lignocellulosic ethanol plant into a district heating system by case study; the plant has an ethanol capacity of 95 MW with biogas, electricity and heat as by-products. Stockholm’s district heating system is used as the case study, but the results may be relevant also for other urban areas. The system has been studied using MODEST – an optimisation model framework. The results show that introducing the plant would lead to a significant reduction in the cost of heat production. The income from the biofuels and electricity produced would be about €76 million and €130 million annually, respectively, which is an increase of 70% compared to the income from the electricity produced in the system today. Assuming that the electricity produced will replace marginal electricity on the European electricity market and that the biofuel produced will replace gasoline in the transport sector, the introduction of the polygeneration plant in the district heating system would lead to a reduction of global CO2 emissions of about 0.7 million tonnes annually. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction In March 2007, the European Council adopted the integrated energy and climate policy known as the 20-20-20 targets [1]. This policy refers to a 20% reduction in greenhouse gas emissions and a 20% reduction in primary energy use compared to the year 1990. The last target aims to meet 20% of the total energy needed from renewable sources, and to increase the share of renewable energy in the transport sector up to 10% [1]. These ambitious targets, which should be achieved by 2020, present a challenge and are important steps in the EUs energy and climate policy. The target for the transport sector can be met by increasing the share of renewable electricity use or by increasing the share of biofuel [1]. Sweden, for example, reached a 4.9% share of biofuel in the transport sector in 2008, mainly by mixing gasoline with 5% bioethanol [2]. Since biomass is a key element in the European energy and climate policy, and considering that the availability of biomass is uncertain for the future, it is of vital importance to increase the efficiency of its use. In Europe, coal-fired condensing power plants have the highest variable cost and therefore work as the marginal source of electricity [3]. Moreover, when considering a fully deregulated electricity market, as prescribed in the EUs Electricity Directive from 1996 [4], coal-fired condensing power plants would also become the marginal electricity sources in Sweden. This is an important assump⇑ Corresponding author. Tel.: +46 13 281114; fax: +46 13 281788. E-mail address: [email protected] (D. Djuric Ilic). 0306-2619/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.apenergy.2011.09.030
tion for this case study. Those power plants also have the highest carbon dioxide (CO2) emissions per generated megawatt-hour of electricity [5]. Consequently, any electricity production with lower CO2 emissions than in the coal-fired condensing power plants in Sweden, as well as the rest of the EU, should lead to lower global CO2 emissions in the common system. In this context, it is necessary to mention the EU Emissions Trading Scheme (EU ETS), which limits CO2 emissions in the trading sectors (including the power generation sector). With a perfectly functioning EU ETS, measures affecting electricity production or consumption would have no impact on global emissions; see e.g. Dotzauer [6] for details. However, it is still of the utmost importance to find cost-effective measures that would lead to future reductions of the CO2 cap in the EU ETS system. The aim of this paper is to analyze the effects of introducing an ethanol polygeneration plant into the district heating system in Stockholm, Sweden. While in some previous studies on ethanol polygeneration the focus of the research has been on the cost of ethanol production [7], or on the polygeneration system itself [8,9]; the focus in this study is on the district heating production. The ethanol polygeneration plant considered in this study involves power and heat cogeneration as well as biogas production. By introducing such a plant in a district heating system, additional income from the sale of ethanol, biogas and electricity could lead to a decrease in the heat production cost. Assuming that the by-products would replace products with higher CO2 emissions in the European energy system, the introduction of the plant would also lead to a reduction in global CO2 emissions.
215
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221
with molasses. Enzymes are required for this process, but these are purchased from external suppliers. Most of the glucan is hydrolysed and about 90% of the fermentable sugar is converted to ethanol, which is then separated by distillation and dehydrated. [18,19] Excess solid residues from the process (the stillage from the distillation and the flash streams from the pretreatment) can be utilised for the production of by-products that can contribute to the overall revenue. In previous research, process scenarios with different combinations of by-products have been compared in order to identify ways to improve the total energy efficiency [20,17]. The by-products considered in the earlier research were: pellets, biogas, electricity and heat. The results have shown that the most profitable ethanol production processes are those that include biogas, electricity and heat production [17]. During the process, the stillage from the distillation and the flash streams from the pretreatment are treated by anaerobic digestion and raw biogas is upgraded using pressure swing absorption technology. The solid fraction of the residues from the anaerobic digestion is directly utilised for steam production while the liquid fraction is first treated aerobically. After the steam required for the process is separated, the excess steam is used for combined heat and power (CHP) production [17]. Fig. 1 shows a simplified configuration scheme of such an ethanol production from lignocellulosic biomass. This type of production, known as polygeneration, is a cost-effective technology that has the potential to significantly increase the efficient use of resources.
2. Polygeneration – an economical technology for bioethanol production
FP
molasses
Distillation
Ethanol Dehydration
stillage
flash-streams
high-pressure steam
The methodology used in this paper includes a field study and data collection, as well as optimisation of the district heating system and integration of bioethanol production into the model. The district heating system has been studied using MODEST, a model framework based on linear programming, which has been
SSF and yeast cultivation
Pretreatment
Biogas
raw biogas
Anaerobic digestion
3. Methodology of study
low-pressure steam
Feedstock handling low-pressure steam
Upgrading
CHP production
solid
Electricity Heat
liquid
Aerobic treatment
BF
sludge
process steam
Raw material
enzymes
SO2
water ammonia
The use of biofuels is one way to reduce both dependency on fossil fuels and environmental pollution. However, according to the European Commission, biofuels are the most expensive form of renewable energy [1]. The economics of biofuel production depend on a variety of factors, including the feedstock, plant capacity, process technology [10,11] and structure of the production system [12,13]. The ethanol used in Sweden is mainly imported from Brazil, where it is produced from sugarcane [7]. However, the technology of ethanol production from wood, so-called lignocellulosic ethanol production, offers an opportunity for the large-scale production of ethanol in Sweden at a competitive cost [14]. Compared with other ethanol production technologies, an ethanol production process based on sulphur dioxide (SO2) catalysed steam pretreatment followed by simultaneous saccharification and fermentation (SSF) has been shown to result in highest economic benefits and, consequently, is the closest to becoming commercially available [15,16]. The process generally involves pretreatment, SSF and yeast cultivation, distillation and dehydration; however, the number of stages in the process may vary, as well as the plant configuration, depending on combinations of desired by-products during the process [17]. The purpose of pretreatment is to make the feedstock more accessible to further biological or chemical treatment. The feedstock that has previously been impregnated with gaseous SO2 and preheated with low-pressure steam is fed to the pretreatment reactor together with the highpressure steam. After that, the steam pretreated slurry is flashcooled by pressure reduction and the pH of the slurry is neutralised with ammonia. Before a liquid fraction for yeast cultivation is separated, the slurry is diluted with fresh water in order to adjust the dry matter to 10% water insoluble solids. SSF is performed at 37 °C with yeast that is cultivated on the liquid fraction supplemented
Fig. 1. A simplified configuration scheme of ethanol polygeneration production from lignocellulosic biomass.
216
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 Table 1 Major district heating networks in Stockholm. Network
Heat production in the year 2005 (TW h)
Installed heat capacity (MW)
Installed electricity capacity (MW)
Types of base production
South Central Northwest Southeast
5.0 4.4 2.2 0.5
2200 1800 700 300
148 345 105 20
Waste-fired CHP Coal-fired CHP Biomass-fired CHP Biomass-fired CHP
developed for optimisation of dynamic energy systems with timedependent components and boundary conditions. The aim of the optimisation is to minimize the annual system cost of supplying the heat and/or electricity demand during the analyzed period, by choosing the best operation at the right time from existing and potential new plants in the system. The system cost includes: new investments, operation and maintenance costs, fuel costs including taxes and fees, as well as revenues from by-products, and lastly, the present value of all the capital costs. The plants in the model are described in terms of their efficiencies, maximum capacity, power-toheat ratio if it is a CHP plant, maintenance periods and costs, technical lifetime, economic lifetime and investment cost if it is a new plant. The input data that also needs to be defined are study period, time division, discount rate and the system’s energy demands that shall be fulfilled [21,22]. The MODEST optimisation model was developed at Linköping University in Sweden, and during the last 10 years it has been applied to different kinds of energy systems with different purposes; it has been used to analyze the potential for the reduction of global CO2 emissions by producing the electricity in CHP plants [23–25] and to analyze possibilities for cooperation between district heating systems and industry [26,27]. 4. Case study Stockholm, the capital of Sweden and the largest city in Scandinavia, is located in the southeast of Sweden. Including its surrounding communities, the city has just under 2 million inhabitants [28]. 4.1. The district heating system At present, there are four large district heating networks in Stockholm that deliver more than 12 TW h of heat annually. Table 1 shows heat production, the various types of base production and the installed heat and electricity capacity in the networks. There is connectivity between the southern and central district heating networks, so these two can be analyzed as one. The district heating system consists of approximately 70 heating plants owned by five different heating companies [29]. Six of these 70 heating plants are CHP plants with a total electricity capacity of about 600 MW, which makes it possible to produce over 2 TW h of electricity annually. The two CHP plants that have the highest installed electricity capacity, 200 MW and 145 MW, are fuelled by oil and coal, respectively; the other four CHP units are fuelled by solid biomass and waste [29]. The differences in base production in the four networks cause the notable differences in heat production costs among them [29,30]. 4.2. The transport sector More than 30% of the total local CO2 emissions in the county of Stockholm are released by the transport sector. Since 1990, the number of residents has increased by 20% and at present, about 1 million vehicles are registered in the county of Stockholm. Despite this, Stockholm has succeeded in reducing the transport sector’s local emissions by 25% during the last two decades, mainly by
using alternative fuels and by introducing a congestion charge [31]. The process of introducing clean vehicles and alternative fuels started as early as 1994. In 2007, about 90,000 m3 of ethanol and 6000 m3 of biogas were sold in the County of Stockholm and that amount has increased over the last 2 years [32]. In Fig. 2, the shares of biogas and ethanol sales of the total fuel sales in Stockholm are shown [32,33]. 4.3. Modeling the energy system of Stockholm In this study a model of Stockholm’s district heating system has been built according to the data from Dahlroth [29]. The period analyzed is 10 years and the capital costs in the model are based on a discount rate of 6%. Each year is divided into 88 periods that depict seasonal variations in the heat demand, prices and plant efficiencies. For each of the months from April to October, four time periods are modelled: days and nights during the weekdays, as well as days and nights during the weekends. For the remainder of the year, heat demand peaks and heat demand variations are significant. During this time frame the time division is at its highest increment; the months are divided into 12 periods and are sometimes modelled hour by hour. This time division was earlier used in several MODEST studies and is described in more detail in Henning [21]. Based on the district heating production in 2007, the curves of the district heating demands for the different parts of the system have been calculated and adjusted to the time division. The operation and maintenance periods have also been included in the model. After that, the model has been shaped according to detailed production data from 2007. Based on the description of the process given in Section 2, a simplified model for ethanol production from lignocellulosic biomass has been created (Fig. 1) and integrated into the district heating system model. It is assumed that the energy requirement for ethanol and biogas production is a linear function of feedstock input. The input and output data for the plant that have been used in the model (Table 2) have been taken from Barta et al. [17]. The installed ethanol capacity of the polygeneration plant has been chosen to fulfil the annual ethanol demand in Stockholm’s transport sector. The calculation of ethanol demand is based on ethanol sales in the county of Stockholm during 2008, which was approximately 110,000 m3 [32]. Since the ratio between the ethanol and biogas production is constant (Table 2), it is not possible to limit them separately at the same time. This leads to biogas production being much higher than the current biogas sales in the Stockholm transport sector. Since the heating demand in the district heating system is much lower during the summer than during the other seasons, it is also assumed that the plant is shut down during August, while during the other months the ethanol production and consequently all other productions from the plant are constant. Investments for the separate units in the polygeneration plant are calculated using an overall scaling factor (R) of 0.71 according to
Costa ¼ Costb 1
Sizea Sizeb
R ;
The average value for chemical process plants [34].
ð1Þ
217
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 3
2,5
%
2
1,5
1
0,5
0 2000
2001
2002
2003 Biogas
Ethanol
2004
2005
2006
2007
2008
Ethanol in 95 octane petrol
Fig. 2. The share of biogas and ethanol sales of the total fuel sales in Stockholm.
Table 2 The input and output data of the polygeneration plant [17]. Input
(MW)
Output
(MW)
Biomass Molasses Enzymes
272.55 4.25 1.75
Ethanol Biogas Electricity Heat
95.00 69.75 13.25 77.75
where Costa and Costb represent the costs of equipment for the base ethanol plant (Sizea = 109 MWbiomass) and for the ethanol plant in the study (Sizeb = 272.55 MWbiomass), respectively (Table 3). During the calculation of the fixed capital investment, it is assumed that the ratio of the total indirect costs to the total direct costs does not depend on the plant size. The annual operating and maintenance costs are 2.5% of the total fixed capital investment [17]. It is assumed that the economic lifetime of the plant is 25 years and that the technical lifetime is 30 years.
Table 3 A summary of the equipment costs for the polygeneration system calculated according to Eq. (1).
a b c
Size of the plant
Sizea = 109 (MWbiomass)
Sizeb = 272.55 (MWbiomass)
Component Raw material handling Pretreatment Yeast cultivation and SSF Distillation and purification Separationb CHP unitc Storage Heat exchanger network Anaerobic digestion and biogas purification Total direct costs Total indirect costs Fixed capital investment The annual operating and maintenance costs
Costa (€ma) [17] 1 13 13 5 3 27 3 1 12
Costb (€m) 2 24 25 10 5 51 6 2 23
78 61 139 3.5
148 115 263 6.6
Million euros. Refers to the separation of the effluent of anaerobic digestion. Includes the flue gas condenser.
Fuel prices, taxes and maintenance costs for all plants are included in the model as well as revenues from electricity, ethanol and biogas. The price of biogas is assumed to be €18/MW h [35]. The import prices of ethanol, including tax on imports and excluding the import tax, are assumed to be €87/MW h and €67/MW h, respectively [36]. The prices for average annual purchases and sales of electricity, including all taxes and tradable green certificates (TGC), are presented in Table 4. The prices for fuel used in the model are not presented in this paper due to the district heating companies’ privacy policies. The net CO2 emissions used in this paper are shown in Table 5. Since the greenhouse effect is a global problem, CO2 emissions are also considered from a global perspective. The global CO2 emissions in the scenarios presented are calculated based on an assumed common European electricity market with coal-condensing power as the marginal power source, which means that 1 kWh of electricity equals 950 kg of global CO2 emissions (see Section 1). Similarly, it is assumed that ethanol and biogas produced in the plant will replace gasoline used in the transport sector. 4.4. Description of scenarios To analyze local CO2 emissions, the system’s influence on global CO2 emissions, and the economic properties of the system, a number of different scenarios have been proposed concerning possible future cases (Table 6). In scenarios 1–4, the existing district heating system has been analyzed. In those scenarios, the influences of higher biomass and electricity prices have been investigated. Those scenarios have been used as reference scenarios in the study. Since the types of base production in the networks are different, as are the district heating demands (Table 1), the influence of introducing a polygeneration plant into the system depends on the location of the plant. The aim of scenarios 5–8 is to determine the optimal location of a polygeneration plant in the district heating system. In order to facilitate efficient transport of the biomass, the polygeneration plant is built near shipping ports respective to the networks. Moreover, there are only a few locations in the system where such a big plant can be built, therefore the four most suitable sites have been chosen, each in different parts of the system. In order to improve the distribution of heat between the part
218
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221
Table 4 The prices of electricity including taxes and TGC. Current price of electricity [37,2], (€/MW h)
European price of electricity [38,2] (€/MW h)
Purchase
Sale
Sale with TGC included
Purchase
Sale
Sale with TGC included
70.10
35.46
67.56
83.30
48.65
80.77
Table 5 Net emissions of CO2 [39,40].
a
Fuel
Oil
Coal
Waste
Biomass
Electricitya
Gasoline
Emissions (kg/MW h fuel)
280
330
100
0
950
260
The marginal electricity that is produced in coal-fired condensing power plants (see Section 1).
Table 6 List of the chosen scenarios.
a b c
Sc.
Plants in the district heating system
Electricity price
Ethanol import price (€/MW h)
Average biomass price [41] ((€/MW h))
1 2 3 4 5 6 7 8 9 10 11 12
Existing d.h.s.a Existing d.h.s. Existing d.h.s. Existing d.h.s. +p.p. in the south n.b +p.p. in the northwest n. +p.p. in the southeast n. +p.p. in the central n. +p.p. in the systemc +p.p. in the system +p.p. in the system +p.p. in the system
Nordpool EU market Nordpool EU market Nordpool Nordpool Nordpool Nordpool EU market Nordpool Nordpool EU market
– – – – 87 87 87 87 87 67 87 87
20 20 24 24 20 20 20 20 20 20 24 24
Existing d.h.s. = the existing district heating system without introducing the polygeneration plant. +p.p. in the south n. = the district heating system with the polygeneration plant introduced in the south network. +p.p. in the system = the district heating system with the polygeneration plant sited at the optimal location.
of the system where the polygeneration plant is built and the other parts, increased capacities for existing pipes are introduced. Sensitivity analysis is done with respect to different factors. In scenarios 9 and 12, the potential future cases in which higher electricity prices would be introduced are described. The influence of a lower import price for ethanol is presented in scenario 10, where it is assumed that tax on ethanol imports does not exist. In scenarios 11 and 12, the consequences of an increase in the biomass price have been analyzed. 5. Results and discussion Due to its global availability, wood is a promising feedstock for producing ethanol. However, despite the fact that biofuel production from wood would reduce competition with food production, it may cause a negative impact on raw material availability, for example, in the panel and pulp-and-paper industry. In addition, the increased competition for wood raw material, and the potential significant difference between wood supply and demand may lead to local shortages and to a precipitous increase in the price of wood. Considering these problems, it is vital to increase efficiency in the use of wood for both the energy production as well as for raw material for industry. When the ethanol is produced with efficient technology such as polygeneration where CHP production and biogas production are included, lignocellulosic material as feedstock becomes more attractive, especially for forest-rich countries where district heating systems are well developed. Thus, introducing a polygeneration plant into Stockholm’s district heating systems would be a good strategy for the effective use of biomass. The location found to be optimal for the polygeneration plant is in the central district heating network (Table 7 – Sc. 8). As shown
in Fig. 3, the biomass-fired plants and the waste-fired plants generate the major part of the district heating in each scenario, while the oil-fired plants cover the peak load. With the polygeneration plant in the system, the biomass used would increase from 6.5 TW h/year to 8.5 TW h/year and the total fuel consumption in the system would be about 2 TW h higher than in the existing system. In spite of this, even if the ethanol price decreases by 20%2 (Sc. 10) the system cost would be reduced due to the added income from the sale of by-products; the electricity production would increase and the ethanol and biogas production would be 0.75 TW h and 0.55 TW h, respectively. The global CO2 emissions of the system would be reduced by about 0.4 million tonnes annually (Sc. 8 and Sc. 10), when considering the electricity production3. If both the electricity produced and the reduction in CO2 emissions in the transport sector are considered, the reduction in global CO2 emissions would be about 0.7 million tonnes annually. With the introduction of the polygeneration plant into the system the biomass share increases from about 50% to about 60% (Fig. 3), which makes the system cost more dependent on the biomass price. In spite of this, even if the biomass price increased by 20% with the polygeneration plant, the system cost would be 12% lower (Sc. 11) than the cost of the existing district heating system with the higher biomass price (Sc. 3). In most of the scenarios the total fossil fuel consumption in the system, and consequently local CO2 emissions, are not significantly changed after the introduction of the polygeneration plan, but even then the reduction in global CO2 emissions are considerable. The largest reduction in both global CO2 emissions and in system costs 2
Compared to the current price. Assuming coal condensing as the marginal source of power in a European electricity system. 3
219
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 Table 7 Results for the scenarios. Sc.
1 2 3 4 5 6 7 8 9 10 11 12
Biomass share in the system (%)
Electricity Annual prod. (TW h)
Income from electricity (€m)
Annual prod. (TW h)
Income from ethanol (€m)
Annual prod. (TW h)
Income from biogas (€m)
258 243 292 278 219 218 223 213 196 228 257 240
48 49 47 48 56 56 56 58 58 58 57 57
2.30 2.35 2.28 2.44 2.38 2.31 2.32 2.36 2.42 2.36 2.35 2.48
122 150 121 157 128 124 124 129 156 129 128 161
0 0 0 0 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75
0 0 0 0 66 66 66 66 66 50 66 66
0 0 0 0 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.55
0 0 0 0 10 10 10 10 10 10 10 10
Ethanol
Biogas
Million euros.
18 16 14 12
TWh
10 8 6 4 2 0 1
2
3
4
5
6
7
8
9
10
11
12
9
10
11
12
scenarios biomass waste coal
electricity oil
Fig. 3. Amounts of various fuels in the system.
3,00
2,50
2,00
1,50
million ton
a
Annual system costs (€ma)
1,00
0,50
0,00 1
2
3
4
5
6
7
8
-0,50
-1,00
scenarios Local emissions of CO2 Global emissions of CO2 considering the produced bio-fuel Global emissions of CO2 considering the produced electricity Global emissions of CO2 considering the produced bio-fuel and electricity
Fig. 4. Annual emissions of CO2.
220
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221
would be achieved by introducing the polygeneration plant, in combination with an increase in electricity prices (Sc. 9). As the electricity price increases, the system cost would be 20% lower if the polygeneration plant were introduced into the system (comparing Sc. 9 with the corresponding Sc. 2). With the assumption that the electricity produced replaces the marginal electricity (see Section 1), and the ethanol and biogas produced both replace gasoline in the transport sector, the system’s global CO2 emissions would be about 0.52 million tonnes annually; that is considerably lower than today’s emissions (Fig. 4). The highest electricity production in the system is found in the scenarios with the higher electricity and biomass prices (Sc. 4 and 12). The reason for this is that the two CHP plants with the largest installed electricity capacity are fuelled by oil and coal (see Section 4.1); when biomass and electricity prices are higher it is more profitable to run those two CHP units than to run boilers fuelled by biomass. The higher electricity and biomass prices with the additional polygeneration plant as a complement (Sc. 12) increase the electricity production by 8% compared to the existing system (Sc. 1). The electricity sale is a parameter which has a substantial effect on the system cost and in most of the scenarios the annual income from the sold electricity is as high as 60% of the annual system cost. The income from ethanol and biogas, in scenarios where the polygeneration plant is included, reduces the system cost by €76 million annually. This confirms that heat production in cogeneration or polygeneration plants has a great influence not only on global CO2 emissions, but also on the district heating production cost. The technology of simultaneous production of heat, power, ethanol and biogas considered in this paper is still under development. An ethanol polygeneration plant is a complex system and introducing such a plant into a district heating system requires considerable investment. In spite of this, the introduction of polygeneration plants into district heating systems should be considered for future technology for more cost- and resource-effective production of heat. It should also be considered a feasible strategy to achieve a local fossil-fuel-free transport system, and above all, a strategy for reduction of global CO2 emissions. 6. Conclusion The findings in this study indicate that ethanol and biogas production integrated with a CHP plant would be a competitive alternative to pure heat production in district heating systems. The production of ethanol and biogas in such a plant introduced into Stockholm’s district heating system would provide substantial benefits from economic and CO2 viewpoints. A plant with ethanol capacity of 95 MW would fulfil the ethanol and biogas demand in Stockholm’s transport sector, and at the same time, would produce 110 GWh of electricity annually. Considering the increased electricity production and the income from the sold biofuel, the total income from the by-products produced in the district heating system would increase from €122 million to €205 million annually. Assuming that the biofuel produced would replace gasoline in the transport sector, and that the electricity produced would replace the electricity generated in coal-fired condensing power plants, the global CO2 emissions of the system would be reduced by 225%. A higher electricity price would encourage a higher electricity production; thus if the plant would be introduced into the system and if the electricity price would increase by 20%, the global CO2 emissions of the system would be even lower and the income from the sold by-products would be about €232 million annually. Acknowledgments This research was conducted under the auspices of the Energy Systems Programme, which is financially supported by the
Swedish Energy Agency. The authors would like to express their gratitude to Professor Björn G. Karlsson for helpful discussions and to doctoral students Shahnaz Amiri and Elisabeth Wetterlund for their support and valuable comments.
References [1] COM 2006. Renewable energy road map–renewable energies in the 21st century: building a more sustainable future. Communication from the Commission to the Council and the European Parliament. COM (2006) 848 final. 2007. [2] Statens energimyndighet. Energy in Sweden 2009. Swedish National Energy Administration, ET 2009:30, Eskilstuna, Sweden; 2009. [3] SEA. Marginal elproduktion och CO2-utsläpp i Sverige (Marginal electricity production and CO2-emissions in Sweden, in Swedish), Swedish National Energy Administration, ER 14:2002, Eskilstuna, Sweden; 2002. [4] Directive 96/92/EC ‘Second report to the Council and the European Parliament on harmonisation requirements concerning common rules for the internal market in electricity’ Luxembourg. [5] Karlsson B, Sjödin J, Carlson A. System perspectives on bioenergy, external effects and power utilisation in Europe. In: Pelkonen P, Hakkila P, Karjalainen T, Schlamadinger, editors. Woody biomass as an energy source–challenges in Europe. EFI Proceedings No. 39. Joensuu, Finland. Finland: European Forest Institute; 2000 September 25–28. p. 29–44. [6] Dotzauer E. Greenhouse gas emissions from power generation and consumption in a nordic perspective. Energy Policy 2010;38(2):701–4. [7] Leduc S, Starfelt F, Dotzauer E, Kindermann G, McCallum I, Obersteiner M, et al. Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy 2010;35(6):2709–16. [8] Starfelt F, Thorin E, Dotzauer E, Yan J. Performance evaluation of adding ethanol production into an existing combined heat and power plant. Bioresour Technol 2010;101(2):613–8. [9] Starfelt F, Daianova L, Yan J, Thorin E, Dotzauer E. Increased renewable electricity production in combined heat power plants by introducing ethanol production. In: Proceeding of the first international conference on applied energy (ICAE09). Hong Kong, China; 2009 January 5–7. [10] Demirbas A. Political, economic and environmental impacts of biofuels: a review. Appl Energy 2009;86(1):108–17. [11] Murphy JD, McCarthy K. Ethanol production from energy crops and waste for use as a transport fuel in Ireland. Appl Energy 2005;82(2):148–66. [12] Demirbas MF. Biorefineries for biofuel upgrading: a critical review. Appl Energy 2009;86(1):151–61. [13] Eriksson G, Kjellström B. Assessment of combined heat and power (CHP) integrated with wood based ethanol production. Appl Energy 2010;87(12):3632–41. [14] Reith J, Veenkamp J, Van Ree R, De Laat W, Niessen J, De Jong E, Elbersen HW, Weusthuis R, van Dijken JP, Raamsdonk L. Coproduction of bio-ethanol, electricity and heat from biomass wastes: potential and R&D issues. In: Proceeding of the first European conference on agriculture & renewable energy. Amsterdam, The Netherlands; 2001 May 6–8. [15] Söderström J, Galbe M, Zacchi G. Separate versus simultaneous saccharification and fermentation of two-step steam pretreated softwood for ethanol production. J Wood Chem Technol 2005;25(3):187–202. [16] Wingren A, Gable M, Zacchi G. Techno-economic evaluation of producing ethanol from softwood: comparison of SSF and SHF and identification of bottlenecks. Biotechnol Prog 2003;19(4):1109–17. [17] Barta Z, Reczey K, Zacchi G. Techno-economic evaluation of stillage treatment with anaerobic digestion in a softwood-to-ethanol process. Biotechnology for Biofuels; 2010.. [18] Barta Z, Kovacs K, Reczey K, Zacchi G. Process design and economics of on-site cellulase production on various carbon sources in a softwood-based ethanol plant. Enzyme Research; 2010. doi:10.4061/2010/734182. . [21] Henning D. Optimisation of local and national energy systems. Development and use of the MODEST model (Dissertation No. 559). Linköping (Sweden): Linköping University; 1999. [22] Gebremedhin A. Regional and industrial co-operation in district heating systems (Dissertations No. 849). Linköping (Sweden): Linköping University; 2003. [23] Amiri S, Trygg L, Moshfegh B. Assessment of the natural gas potential for heat and power generation in the county of Östergötland in Sweden. Energy Policy 2009;37(2):496–506. [24] Trygg L, Amiri S. European perspective on absorption cooling in a combined heat and power system–a case study of energy utility and industries in Sweden. Appl Energy 2007;84(12):1319–37. [25] Danestig M, Gebremehdin A, Karlsson B. Stockholms CHP potential–an opportunity for CO2 reductions? Energy Policy 2007;35(9):4650–60. [26] Trygg L, Karlsson B. Industrial DSM in a deregulated European electricity market—a case study of 11 plants in Sweden. Energy policy 2005;33(11):1445–59.
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 [27] Difs K, Danestig M, Trygg L. Increased use of district heating in industrial processes – impacts on heat load duration. Appl Energy 2009;86(11):2327–34. [28] Stockholm Office of Research and Statistics, Statistical Yearbook of Stockholm 2010. Report, 2009.. [cited 10.12.09] [29] Dahlroth B. Öppnade fjärrvärmenät i Storstockholm (Open district heating network in greater Stockholm). Stockholm, Sweden: Fastighetsägarna Stockholm, 2009. [30] Dotzauer E. Experiences in mid-term planning of district heating systems. Energy 2003;28(15):1545–55. [31] Statistik Sweden. . [cited 16.12.09] [32] Hugosson B, Sjölin L, Nilsson L. Forsaljning av miljofordon och fornybara drivmedel i Stockholm, Report, Sweden; 2008. . [33] Stockholms stad (Internet). . [cited 14.12.09] [34] Remer DS, Chai LH. Design cost factors for scaling-up engineering equipment. Chem Eng Prog 1990;86(8):77–82. [35] Kärrman E, Olofsson M, Persson B, Sander A, Aberg H. Köksavfallskvarnar–en teknik för uthållig resursanvändning? En förstudie i Göteborg (Food waste disposers – a technical solution for sustainable resource management? A pre-study in
[36] [37] [38]
[39]
[40] [41]
221
Gothenburg) VA-Forsk; Jönköping, (Sweden); 2001.. F.O. Licht’s world ethanol & biofuels report. 2007. . Nordpool. Nordpool electricity spot market. 2009. . Melkerson M, Söderberg S-O. Dynamiska elpriser – elprissättning på en integrerad europeisk elmarknad (Dynamic electricity prices – pricing in an integrated European electricity market – in Swedish) (degree project). Linköping (Sweden): Institute of Technology, Dept. of Mechanical Engineering. Linköping University; 2004. Levinson N, Freiman R. Optimal kraftvärme och nätinvestering I Stockholms fjärrvärmesystem (Optimal CHP and district heating network investments in Stockholm) (degree project). Linköping (Sweden): Institute of Technology, Dept. of Mechanical Engineering, Linköping University; 2005. Statistik Sweden. . [cited 10.03.10] STEM. Prisblad för biobränslen, torv m.m. Nr 1/2009. Eskilstuna, Sweden: Swedish Energy Agency; 2009.
Contents lists available at SciVerse ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
District heating and ethanol production through polygeneration in Stockholm Danica Djuric Ilic a,⇑, Erik Dotzauer b, Louise Trygg a a b
Division of Energy Systems, Department of Management and Engineering, Linköping University, SE-581 83 Linköping, Sweden School of Sustainable Development of Society and Technology, Mälardalen University, SE-72123 Västerås, Sweden
a r t i c l e
i n f o
Article history: Received 5 November 2010 Received in revised form 16 September 2011 Accepted 21 September 2011 Available online 19 October 2011 Keywords: District heating Polygeneration Biofuel Case study
a b s t r a c t Ethanol can be produced with little impact on the environment through the use of polygeneration technology. This paper evaluates the potential of integrating a lignocellulosic ethanol plant into a district heating system by case study; the plant has an ethanol capacity of 95 MW with biogas, electricity and heat as by-products. Stockholm’s district heating system is used as the case study, but the results may be relevant also for other urban areas. The system has been studied using MODEST – an optimisation model framework. The results show that introducing the plant would lead to a significant reduction in the cost of heat production. The income from the biofuels and electricity produced would be about €76 million and €130 million annually, respectively, which is an increase of 70% compared to the income from the electricity produced in the system today. Assuming that the electricity produced will replace marginal electricity on the European electricity market and that the biofuel produced will replace gasoline in the transport sector, the introduction of the polygeneration plant in the district heating system would lead to a reduction of global CO2 emissions of about 0.7 million tonnes annually. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction In March 2007, the European Council adopted the integrated energy and climate policy known as the 20-20-20 targets [1]. This policy refers to a 20% reduction in greenhouse gas emissions and a 20% reduction in primary energy use compared to the year 1990. The last target aims to meet 20% of the total energy needed from renewable sources, and to increase the share of renewable energy in the transport sector up to 10% [1]. These ambitious targets, which should be achieved by 2020, present a challenge and are important steps in the EUs energy and climate policy. The target for the transport sector can be met by increasing the share of renewable electricity use or by increasing the share of biofuel [1]. Sweden, for example, reached a 4.9% share of biofuel in the transport sector in 2008, mainly by mixing gasoline with 5% bioethanol [2]. Since biomass is a key element in the European energy and climate policy, and considering that the availability of biomass is uncertain for the future, it is of vital importance to increase the efficiency of its use. In Europe, coal-fired condensing power plants have the highest variable cost and therefore work as the marginal source of electricity [3]. Moreover, when considering a fully deregulated electricity market, as prescribed in the EUs Electricity Directive from 1996 [4], coal-fired condensing power plants would also become the marginal electricity sources in Sweden. This is an important assump⇑ Corresponding author. Tel.: +46 13 281114; fax: +46 13 281788. E-mail address: [email protected] (D. Djuric Ilic). 0306-2619/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.apenergy.2011.09.030
tion for this case study. Those power plants also have the highest carbon dioxide (CO2) emissions per generated megawatt-hour of electricity [5]. Consequently, any electricity production with lower CO2 emissions than in the coal-fired condensing power plants in Sweden, as well as the rest of the EU, should lead to lower global CO2 emissions in the common system. In this context, it is necessary to mention the EU Emissions Trading Scheme (EU ETS), which limits CO2 emissions in the trading sectors (including the power generation sector). With a perfectly functioning EU ETS, measures affecting electricity production or consumption would have no impact on global emissions; see e.g. Dotzauer [6] for details. However, it is still of the utmost importance to find cost-effective measures that would lead to future reductions of the CO2 cap in the EU ETS system. The aim of this paper is to analyze the effects of introducing an ethanol polygeneration plant into the district heating system in Stockholm, Sweden. While in some previous studies on ethanol polygeneration the focus of the research has been on the cost of ethanol production [7], or on the polygeneration system itself [8,9]; the focus in this study is on the district heating production. The ethanol polygeneration plant considered in this study involves power and heat cogeneration as well as biogas production. By introducing such a plant in a district heating system, additional income from the sale of ethanol, biogas and electricity could lead to a decrease in the heat production cost. Assuming that the by-products would replace products with higher CO2 emissions in the European energy system, the introduction of the plant would also lead to a reduction in global CO2 emissions.
215
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221
with molasses. Enzymes are required for this process, but these are purchased from external suppliers. Most of the glucan is hydrolysed and about 90% of the fermentable sugar is converted to ethanol, which is then separated by distillation and dehydrated. [18,19] Excess solid residues from the process (the stillage from the distillation and the flash streams from the pretreatment) can be utilised for the production of by-products that can contribute to the overall revenue. In previous research, process scenarios with different combinations of by-products have been compared in order to identify ways to improve the total energy efficiency [20,17]. The by-products considered in the earlier research were: pellets, biogas, electricity and heat. The results have shown that the most profitable ethanol production processes are those that include biogas, electricity and heat production [17]. During the process, the stillage from the distillation and the flash streams from the pretreatment are treated by anaerobic digestion and raw biogas is upgraded using pressure swing absorption technology. The solid fraction of the residues from the anaerobic digestion is directly utilised for steam production while the liquid fraction is first treated aerobically. After the steam required for the process is separated, the excess steam is used for combined heat and power (CHP) production [17]. Fig. 1 shows a simplified configuration scheme of such an ethanol production from lignocellulosic biomass. This type of production, known as polygeneration, is a cost-effective technology that has the potential to significantly increase the efficient use of resources.
2. Polygeneration – an economical technology for bioethanol production
FP
molasses
Distillation
Ethanol Dehydration
stillage
flash-streams
high-pressure steam
The methodology used in this paper includes a field study and data collection, as well as optimisation of the district heating system and integration of bioethanol production into the model. The district heating system has been studied using MODEST, a model framework based on linear programming, which has been
SSF and yeast cultivation
Pretreatment
Biogas
raw biogas
Anaerobic digestion
3. Methodology of study
low-pressure steam
Feedstock handling low-pressure steam
Upgrading
CHP production
solid
Electricity Heat
liquid
Aerobic treatment
BF
sludge
process steam
Raw material
enzymes
SO2
water ammonia
The use of biofuels is one way to reduce both dependency on fossil fuels and environmental pollution. However, according to the European Commission, biofuels are the most expensive form of renewable energy [1]. The economics of biofuel production depend on a variety of factors, including the feedstock, plant capacity, process technology [10,11] and structure of the production system [12,13]. The ethanol used in Sweden is mainly imported from Brazil, where it is produced from sugarcane [7]. However, the technology of ethanol production from wood, so-called lignocellulosic ethanol production, offers an opportunity for the large-scale production of ethanol in Sweden at a competitive cost [14]. Compared with other ethanol production technologies, an ethanol production process based on sulphur dioxide (SO2) catalysed steam pretreatment followed by simultaneous saccharification and fermentation (SSF) has been shown to result in highest economic benefits and, consequently, is the closest to becoming commercially available [15,16]. The process generally involves pretreatment, SSF and yeast cultivation, distillation and dehydration; however, the number of stages in the process may vary, as well as the plant configuration, depending on combinations of desired by-products during the process [17]. The purpose of pretreatment is to make the feedstock more accessible to further biological or chemical treatment. The feedstock that has previously been impregnated with gaseous SO2 and preheated with low-pressure steam is fed to the pretreatment reactor together with the highpressure steam. After that, the steam pretreated slurry is flashcooled by pressure reduction and the pH of the slurry is neutralised with ammonia. Before a liquid fraction for yeast cultivation is separated, the slurry is diluted with fresh water in order to adjust the dry matter to 10% water insoluble solids. SSF is performed at 37 °C with yeast that is cultivated on the liquid fraction supplemented
Fig. 1. A simplified configuration scheme of ethanol polygeneration production from lignocellulosic biomass.
216
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 Table 1 Major district heating networks in Stockholm. Network
Heat production in the year 2005 (TW h)
Installed heat capacity (MW)
Installed electricity capacity (MW)
Types of base production
South Central Northwest Southeast
5.0 4.4 2.2 0.5
2200 1800 700 300
148 345 105 20
Waste-fired CHP Coal-fired CHP Biomass-fired CHP Biomass-fired CHP
developed for optimisation of dynamic energy systems with timedependent components and boundary conditions. The aim of the optimisation is to minimize the annual system cost of supplying the heat and/or electricity demand during the analyzed period, by choosing the best operation at the right time from existing and potential new plants in the system. The system cost includes: new investments, operation and maintenance costs, fuel costs including taxes and fees, as well as revenues from by-products, and lastly, the present value of all the capital costs. The plants in the model are described in terms of their efficiencies, maximum capacity, power-toheat ratio if it is a CHP plant, maintenance periods and costs, technical lifetime, economic lifetime and investment cost if it is a new plant. The input data that also needs to be defined are study period, time division, discount rate and the system’s energy demands that shall be fulfilled [21,22]. The MODEST optimisation model was developed at Linköping University in Sweden, and during the last 10 years it has been applied to different kinds of energy systems with different purposes; it has been used to analyze the potential for the reduction of global CO2 emissions by producing the electricity in CHP plants [23–25] and to analyze possibilities for cooperation between district heating systems and industry [26,27]. 4. Case study Stockholm, the capital of Sweden and the largest city in Scandinavia, is located in the southeast of Sweden. Including its surrounding communities, the city has just under 2 million inhabitants [28]. 4.1. The district heating system At present, there are four large district heating networks in Stockholm that deliver more than 12 TW h of heat annually. Table 1 shows heat production, the various types of base production and the installed heat and electricity capacity in the networks. There is connectivity between the southern and central district heating networks, so these two can be analyzed as one. The district heating system consists of approximately 70 heating plants owned by five different heating companies [29]. Six of these 70 heating plants are CHP plants with a total electricity capacity of about 600 MW, which makes it possible to produce over 2 TW h of electricity annually. The two CHP plants that have the highest installed electricity capacity, 200 MW and 145 MW, are fuelled by oil and coal, respectively; the other four CHP units are fuelled by solid biomass and waste [29]. The differences in base production in the four networks cause the notable differences in heat production costs among them [29,30]. 4.2. The transport sector More than 30% of the total local CO2 emissions in the county of Stockholm are released by the transport sector. Since 1990, the number of residents has increased by 20% and at present, about 1 million vehicles are registered in the county of Stockholm. Despite this, Stockholm has succeeded in reducing the transport sector’s local emissions by 25% during the last two decades, mainly by
using alternative fuels and by introducing a congestion charge [31]. The process of introducing clean vehicles and alternative fuels started as early as 1994. In 2007, about 90,000 m3 of ethanol and 6000 m3 of biogas were sold in the County of Stockholm and that amount has increased over the last 2 years [32]. In Fig. 2, the shares of biogas and ethanol sales of the total fuel sales in Stockholm are shown [32,33]. 4.3. Modeling the energy system of Stockholm In this study a model of Stockholm’s district heating system has been built according to the data from Dahlroth [29]. The period analyzed is 10 years and the capital costs in the model are based on a discount rate of 6%. Each year is divided into 88 periods that depict seasonal variations in the heat demand, prices and plant efficiencies. For each of the months from April to October, four time periods are modelled: days and nights during the weekdays, as well as days and nights during the weekends. For the remainder of the year, heat demand peaks and heat demand variations are significant. During this time frame the time division is at its highest increment; the months are divided into 12 periods and are sometimes modelled hour by hour. This time division was earlier used in several MODEST studies and is described in more detail in Henning [21]. Based on the district heating production in 2007, the curves of the district heating demands for the different parts of the system have been calculated and adjusted to the time division. The operation and maintenance periods have also been included in the model. After that, the model has been shaped according to detailed production data from 2007. Based on the description of the process given in Section 2, a simplified model for ethanol production from lignocellulosic biomass has been created (Fig. 1) and integrated into the district heating system model. It is assumed that the energy requirement for ethanol and biogas production is a linear function of feedstock input. The input and output data for the plant that have been used in the model (Table 2) have been taken from Barta et al. [17]. The installed ethanol capacity of the polygeneration plant has been chosen to fulfil the annual ethanol demand in Stockholm’s transport sector. The calculation of ethanol demand is based on ethanol sales in the county of Stockholm during 2008, which was approximately 110,000 m3 [32]. Since the ratio between the ethanol and biogas production is constant (Table 2), it is not possible to limit them separately at the same time. This leads to biogas production being much higher than the current biogas sales in the Stockholm transport sector. Since the heating demand in the district heating system is much lower during the summer than during the other seasons, it is also assumed that the plant is shut down during August, while during the other months the ethanol production and consequently all other productions from the plant are constant. Investments for the separate units in the polygeneration plant are calculated using an overall scaling factor (R) of 0.71 according to
Costa ¼ Costb 1
Sizea Sizeb
R ;
The average value for chemical process plants [34].
ð1Þ
217
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 3
2,5
%
2
1,5
1
0,5
0 2000
2001
2002
2003 Biogas
Ethanol
2004
2005
2006
2007
2008
Ethanol in 95 octane petrol
Fig. 2. The share of biogas and ethanol sales of the total fuel sales in Stockholm.
Table 2 The input and output data of the polygeneration plant [17]. Input
(MW)
Output
(MW)
Biomass Molasses Enzymes
272.55 4.25 1.75
Ethanol Biogas Electricity Heat
95.00 69.75 13.25 77.75
where Costa and Costb represent the costs of equipment for the base ethanol plant (Sizea = 109 MWbiomass) and for the ethanol plant in the study (Sizeb = 272.55 MWbiomass), respectively (Table 3). During the calculation of the fixed capital investment, it is assumed that the ratio of the total indirect costs to the total direct costs does not depend on the plant size. The annual operating and maintenance costs are 2.5% of the total fixed capital investment [17]. It is assumed that the economic lifetime of the plant is 25 years and that the technical lifetime is 30 years.
Table 3 A summary of the equipment costs for the polygeneration system calculated according to Eq. (1).
a b c
Size of the plant
Sizea = 109 (MWbiomass)
Sizeb = 272.55 (MWbiomass)
Component Raw material handling Pretreatment Yeast cultivation and SSF Distillation and purification Separationb CHP unitc Storage Heat exchanger network Anaerobic digestion and biogas purification Total direct costs Total indirect costs Fixed capital investment The annual operating and maintenance costs
Costa (€ma) [17] 1 13 13 5 3 27 3 1 12
Costb (€m) 2 24 25 10 5 51 6 2 23
78 61 139 3.5
148 115 263 6.6
Million euros. Refers to the separation of the effluent of anaerobic digestion. Includes the flue gas condenser.
Fuel prices, taxes and maintenance costs for all plants are included in the model as well as revenues from electricity, ethanol and biogas. The price of biogas is assumed to be €18/MW h [35]. The import prices of ethanol, including tax on imports and excluding the import tax, are assumed to be €87/MW h and €67/MW h, respectively [36]. The prices for average annual purchases and sales of electricity, including all taxes and tradable green certificates (TGC), are presented in Table 4. The prices for fuel used in the model are not presented in this paper due to the district heating companies’ privacy policies. The net CO2 emissions used in this paper are shown in Table 5. Since the greenhouse effect is a global problem, CO2 emissions are also considered from a global perspective. The global CO2 emissions in the scenarios presented are calculated based on an assumed common European electricity market with coal-condensing power as the marginal power source, which means that 1 kWh of electricity equals 950 kg of global CO2 emissions (see Section 1). Similarly, it is assumed that ethanol and biogas produced in the plant will replace gasoline used in the transport sector. 4.4. Description of scenarios To analyze local CO2 emissions, the system’s influence on global CO2 emissions, and the economic properties of the system, a number of different scenarios have been proposed concerning possible future cases (Table 6). In scenarios 1–4, the existing district heating system has been analyzed. In those scenarios, the influences of higher biomass and electricity prices have been investigated. Those scenarios have been used as reference scenarios in the study. Since the types of base production in the networks are different, as are the district heating demands (Table 1), the influence of introducing a polygeneration plant into the system depends on the location of the plant. The aim of scenarios 5–8 is to determine the optimal location of a polygeneration plant in the district heating system. In order to facilitate efficient transport of the biomass, the polygeneration plant is built near shipping ports respective to the networks. Moreover, there are only a few locations in the system where such a big plant can be built, therefore the four most suitable sites have been chosen, each in different parts of the system. In order to improve the distribution of heat between the part
218
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221
Table 4 The prices of electricity including taxes and TGC. Current price of electricity [37,2], (€/MW h)
European price of electricity [38,2] (€/MW h)
Purchase
Sale
Sale with TGC included
Purchase
Sale
Sale with TGC included
70.10
35.46
67.56
83.30
48.65
80.77
Table 5 Net emissions of CO2 [39,40].
a
Fuel
Oil
Coal
Waste
Biomass
Electricitya
Gasoline
Emissions (kg/MW h fuel)
280
330
100
0
950
260
The marginal electricity that is produced in coal-fired condensing power plants (see Section 1).
Table 6 List of the chosen scenarios.
a b c
Sc.
Plants in the district heating system
Electricity price
Ethanol import price (€/MW h)
Average biomass price [41] ((€/MW h))
1 2 3 4 5 6 7 8 9 10 11 12
Existing d.h.s.a Existing d.h.s. Existing d.h.s. Existing d.h.s. +p.p. in the south n.b +p.p. in the northwest n. +p.p. in the southeast n. +p.p. in the central n. +p.p. in the systemc +p.p. in the system +p.p. in the system +p.p. in the system
Nordpool EU market Nordpool EU market Nordpool Nordpool Nordpool Nordpool EU market Nordpool Nordpool EU market
– – – – 87 87 87 87 87 67 87 87
20 20 24 24 20 20 20 20 20 20 24 24
Existing d.h.s. = the existing district heating system without introducing the polygeneration plant. +p.p. in the south n. = the district heating system with the polygeneration plant introduced in the south network. +p.p. in the system = the district heating system with the polygeneration plant sited at the optimal location.
of the system where the polygeneration plant is built and the other parts, increased capacities for existing pipes are introduced. Sensitivity analysis is done with respect to different factors. In scenarios 9 and 12, the potential future cases in which higher electricity prices would be introduced are described. The influence of a lower import price for ethanol is presented in scenario 10, where it is assumed that tax on ethanol imports does not exist. In scenarios 11 and 12, the consequences of an increase in the biomass price have been analyzed. 5. Results and discussion Due to its global availability, wood is a promising feedstock for producing ethanol. However, despite the fact that biofuel production from wood would reduce competition with food production, it may cause a negative impact on raw material availability, for example, in the panel and pulp-and-paper industry. In addition, the increased competition for wood raw material, and the potential significant difference between wood supply and demand may lead to local shortages and to a precipitous increase in the price of wood. Considering these problems, it is vital to increase efficiency in the use of wood for both the energy production as well as for raw material for industry. When the ethanol is produced with efficient technology such as polygeneration where CHP production and biogas production are included, lignocellulosic material as feedstock becomes more attractive, especially for forest-rich countries where district heating systems are well developed. Thus, introducing a polygeneration plant into Stockholm’s district heating systems would be a good strategy for the effective use of biomass. The location found to be optimal for the polygeneration plant is in the central district heating network (Table 7 – Sc. 8). As shown
in Fig. 3, the biomass-fired plants and the waste-fired plants generate the major part of the district heating in each scenario, while the oil-fired plants cover the peak load. With the polygeneration plant in the system, the biomass used would increase from 6.5 TW h/year to 8.5 TW h/year and the total fuel consumption in the system would be about 2 TW h higher than in the existing system. In spite of this, even if the ethanol price decreases by 20%2 (Sc. 10) the system cost would be reduced due to the added income from the sale of by-products; the electricity production would increase and the ethanol and biogas production would be 0.75 TW h and 0.55 TW h, respectively. The global CO2 emissions of the system would be reduced by about 0.4 million tonnes annually (Sc. 8 and Sc. 10), when considering the electricity production3. If both the electricity produced and the reduction in CO2 emissions in the transport sector are considered, the reduction in global CO2 emissions would be about 0.7 million tonnes annually. With the introduction of the polygeneration plant into the system the biomass share increases from about 50% to about 60% (Fig. 3), which makes the system cost more dependent on the biomass price. In spite of this, even if the biomass price increased by 20% with the polygeneration plant, the system cost would be 12% lower (Sc. 11) than the cost of the existing district heating system with the higher biomass price (Sc. 3). In most of the scenarios the total fossil fuel consumption in the system, and consequently local CO2 emissions, are not significantly changed after the introduction of the polygeneration plan, but even then the reduction in global CO2 emissions are considerable. The largest reduction in both global CO2 emissions and in system costs 2
Compared to the current price. Assuming coal condensing as the marginal source of power in a European electricity system. 3
219
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 Table 7 Results for the scenarios. Sc.
1 2 3 4 5 6 7 8 9 10 11 12
Biomass share in the system (%)
Electricity Annual prod. (TW h)
Income from electricity (€m)
Annual prod. (TW h)
Income from ethanol (€m)
Annual prod. (TW h)
Income from biogas (€m)
258 243 292 278 219 218 223 213 196 228 257 240
48 49 47 48 56 56 56 58 58 58 57 57
2.30 2.35 2.28 2.44 2.38 2.31 2.32 2.36 2.42 2.36 2.35 2.48
122 150 121 157 128 124 124 129 156 129 128 161
0 0 0 0 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.75
0 0 0 0 66 66 66 66 66 50 66 66
0 0 0 0 0.55 0.55 0.55 0.55 0.55 0.55 0.55 0.55
0 0 0 0 10 10 10 10 10 10 10 10
Ethanol
Biogas
Million euros.
18 16 14 12
TWh
10 8 6 4 2 0 1
2
3
4
5
6
7
8
9
10
11
12
9
10
11
12
scenarios biomass waste coal
electricity oil
Fig. 3. Amounts of various fuels in the system.
3,00
2,50
2,00
1,50
million ton
a
Annual system costs (€ma)
1,00
0,50
0,00 1
2
3
4
5
6
7
8
-0,50
-1,00
scenarios Local emissions of CO2 Global emissions of CO2 considering the produced bio-fuel Global emissions of CO2 considering the produced electricity Global emissions of CO2 considering the produced bio-fuel and electricity
Fig. 4. Annual emissions of CO2.
220
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221
would be achieved by introducing the polygeneration plant, in combination with an increase in electricity prices (Sc. 9). As the electricity price increases, the system cost would be 20% lower if the polygeneration plant were introduced into the system (comparing Sc. 9 with the corresponding Sc. 2). With the assumption that the electricity produced replaces the marginal electricity (see Section 1), and the ethanol and biogas produced both replace gasoline in the transport sector, the system’s global CO2 emissions would be about 0.52 million tonnes annually; that is considerably lower than today’s emissions (Fig. 4). The highest electricity production in the system is found in the scenarios with the higher electricity and biomass prices (Sc. 4 and 12). The reason for this is that the two CHP plants with the largest installed electricity capacity are fuelled by oil and coal (see Section 4.1); when biomass and electricity prices are higher it is more profitable to run those two CHP units than to run boilers fuelled by biomass. The higher electricity and biomass prices with the additional polygeneration plant as a complement (Sc. 12) increase the electricity production by 8% compared to the existing system (Sc. 1). The electricity sale is a parameter which has a substantial effect on the system cost and in most of the scenarios the annual income from the sold electricity is as high as 60% of the annual system cost. The income from ethanol and biogas, in scenarios where the polygeneration plant is included, reduces the system cost by €76 million annually. This confirms that heat production in cogeneration or polygeneration plants has a great influence not only on global CO2 emissions, but also on the district heating production cost. The technology of simultaneous production of heat, power, ethanol and biogas considered in this paper is still under development. An ethanol polygeneration plant is a complex system and introducing such a plant into a district heating system requires considerable investment. In spite of this, the introduction of polygeneration plants into district heating systems should be considered for future technology for more cost- and resource-effective production of heat. It should also be considered a feasible strategy to achieve a local fossil-fuel-free transport system, and above all, a strategy for reduction of global CO2 emissions. 6. Conclusion The findings in this study indicate that ethanol and biogas production integrated with a CHP plant would be a competitive alternative to pure heat production in district heating systems. The production of ethanol and biogas in such a plant introduced into Stockholm’s district heating system would provide substantial benefits from economic and CO2 viewpoints. A plant with ethanol capacity of 95 MW would fulfil the ethanol and biogas demand in Stockholm’s transport sector, and at the same time, would produce 110 GWh of electricity annually. Considering the increased electricity production and the income from the sold biofuel, the total income from the by-products produced in the district heating system would increase from €122 million to €205 million annually. Assuming that the biofuel produced would replace gasoline in the transport sector, and that the electricity produced would replace the electricity generated in coal-fired condensing power plants, the global CO2 emissions of the system would be reduced by 225%. A higher electricity price would encourage a higher electricity production; thus if the plant would be introduced into the system and if the electricity price would increase by 20%, the global CO2 emissions of the system would be even lower and the income from the sold by-products would be about €232 million annually. Acknowledgments This research was conducted under the auspices of the Energy Systems Programme, which is financially supported by the
Swedish Energy Agency. The authors would like to express their gratitude to Professor Björn G. Karlsson for helpful discussions and to doctoral students Shahnaz Amiri and Elisabeth Wetterlund for their support and valuable comments.
References [1] COM 2006. Renewable energy road map–renewable energies in the 21st century: building a more sustainable future. Communication from the Commission to the Council and the European Parliament. COM (2006) 848 final. 2007. [2] Statens energimyndighet. Energy in Sweden 2009. Swedish National Energy Administration, ET 2009:30, Eskilstuna, Sweden; 2009. [3] SEA. Marginal elproduktion och CO2-utsläpp i Sverige (Marginal electricity production and CO2-emissions in Sweden, in Swedish), Swedish National Energy Administration, ER 14:2002, Eskilstuna, Sweden; 2002. [4] Directive 96/92/EC ‘Second report to the Council and the European Parliament on harmonisation requirements concerning common rules for the internal market in electricity’ Luxembourg. [5] Karlsson B, Sjödin J, Carlson A. System perspectives on bioenergy, external effects and power utilisation in Europe. In: Pelkonen P, Hakkila P, Karjalainen T, Schlamadinger, editors. Woody biomass as an energy source–challenges in Europe. EFI Proceedings No. 39. Joensuu, Finland. Finland: European Forest Institute; 2000 September 25–28. p. 29–44. [6] Dotzauer E. Greenhouse gas emissions from power generation and consumption in a nordic perspective. Energy Policy 2010;38(2):701–4. [7] Leduc S, Starfelt F, Dotzauer E, Kindermann G, McCallum I, Obersteiner M, et al. Optimal location of lignocellulosic ethanol refineries with polygeneration in Sweden. Energy 2010;35(6):2709–16. [8] Starfelt F, Thorin E, Dotzauer E, Yan J. Performance evaluation of adding ethanol production into an existing combined heat and power plant. Bioresour Technol 2010;101(2):613–8. [9] Starfelt F, Daianova L, Yan J, Thorin E, Dotzauer E. Increased renewable electricity production in combined heat power plants by introducing ethanol production. In: Proceeding of the first international conference on applied energy (ICAE09). Hong Kong, China; 2009 January 5–7. [10] Demirbas A. Political, economic and environmental impacts of biofuels: a review. Appl Energy 2009;86(1):108–17. [11] Murphy JD, McCarthy K. Ethanol production from energy crops and waste for use as a transport fuel in Ireland. Appl Energy 2005;82(2):148–66. [12] Demirbas MF. Biorefineries for biofuel upgrading: a critical review. Appl Energy 2009;86(1):151–61. [13] Eriksson G, Kjellström B. Assessment of combined heat and power (CHP) integrated with wood based ethanol production. Appl Energy 2010;87(12):3632–41. [14] Reith J, Veenkamp J, Van Ree R, De Laat W, Niessen J, De Jong E, Elbersen HW, Weusthuis R, van Dijken JP, Raamsdonk L. Coproduction of bio-ethanol, electricity and heat from biomass wastes: potential and R&D issues. In: Proceeding of the first European conference on agriculture & renewable energy. Amsterdam, The Netherlands; 2001 May 6–8. [15] Söderström J, Galbe M, Zacchi G. Separate versus simultaneous saccharification and fermentation of two-step steam pretreated softwood for ethanol production. J Wood Chem Technol 2005;25(3):187–202. [16] Wingren A, Gable M, Zacchi G. Techno-economic evaluation of producing ethanol from softwood: comparison of SSF and SHF and identification of bottlenecks. Biotechnol Prog 2003;19(4):1109–17. [17] Barta Z, Reczey K, Zacchi G. Techno-economic evaluation of stillage treatment with anaerobic digestion in a softwood-to-ethanol process. Biotechnology for Biofuels; 2010.
D. Djuric Ilic et al. / Applied Energy 91 (2012) 214–221 [27] Difs K, Danestig M, Trygg L. Increased use of district heating in industrial processes – impacts on heat load duration. Appl Energy 2009;86(11):2327–34. [28] Stockholm Office of Research and Statistics, Statistical Yearbook of Stockholm 2010. Report, 2009.
[36] [37] [38]
[39]
[40] [41]
221
Gothenburg) VA-Forsk; Jönköping, (Sweden); 2001.