Energy Systems and Technologies for the Coming Century ...

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3.1 Base caseA northern European energy system including the Scandinavian countries and Germany,is used for the analyses. Each country is modelled as one region except from Denmarkand Germany, due to bottlenecks in the system.Power and transport demand is set according to [18] (Table 1). The source only includesEU-countries. For estimating Norwegian demand, Swedish demand has been scaledaccording to historical demand.Table 1 Demand input data year 2030 (source [18])Denmark DenmarkGermanySweden Norway FinlandEast West(total)Electricity demand(TWh/yr)16 24 153 133 104 620District heat demand(TWh/yr)12 15 46 3 56 102Transport demand(bill. persons km/yr)31 41 148 69 86 1,262Balancing supply and demand requires investment possibilities in new plants.Investments are possible in the technologies shown in Table 2. Hydrogen is not includedbecause preliminary analyses show that hydrogen is too expensive and will not be used.Table 2 Technology investment options in the simulation. Investment costs forheat storage is given as M€/MWh storage capacity.TechnologyVar O&M Fixed O&MSourInv costsEfficiFuelcostcostce(M€/MW)ency*(€/MWh) (k€/MW/yr)Onshore wind [19] Wind 1.22 11.5 1Offshore wind [19] Wind 2.2 15 1Coal extr.,[19] Coal 1.1 34 0.51Steam TurbineOpen cycle gasturbineCombined cyclegas turbine,cond.Combined cyclegas turbine,extr.[19][20][19]NaturalgasNaturalgasNaturalgas0.57 3 8.6 0.420.56 3.4 21.4 0.580.47 4.2 0.61CHP plant,[19] Wood 1.6 3.2 23 0.485biomass (med)CHP plant,Woodwaste[19]4 140 0.25biomass (small)Nuclear [20] Uranium 2.81 7.7 55.5 0.37The focus is on diesel vehicles, diesel PHEVs, and BEVs, the latter two with varyingbattery sizes. The electric efficiency today is approx. 5 km/kWh [21], [22], [23]. Basedon these efficiencies and assumed evolution, the efficiency is believed to reach approx. 7km/kWh by 2030. Based on [24], the battery size by 2030 will provide a driving range of50 km for PHEVs and 200 km for BEVs.The vehicles are assumed to be plugged-in when parked, making the batteries availableto the transmission system operator. Driving patterns are derived from the investigationof transport habits in Denmark [25]. Driving habits are assumed to be the same for all theNordic countries. Grid capacity is set to 6.9 kW (3 phase 10 Amp with a 230V cable).Risø International Energy Conference 2011 Proceedings Page 418
3.2 ScenariosThe battery evolution is uncertain, both in terms of capacities (density) and batteryprices. Expectations used in this article are based on the technology roadmap from IEA[24] (Table 3). For the PHEVs, the battery capacity is expected to support a drivingrange from 20km to 100km, corresponding to a battery capacity from 3kWh to 15kWh.For the BEVs the driving range is from 100km to 500km, a battery capacity from 15kWhto 72kWh.Table 3 Vehicle battery range options (based on [24]and [14])Type ofvehicleBattery max costs(€/kWh)Battery min costs(€/kWh)Electric storagecap. max (km)Electric storagecap. min (km)BEV 400 100 500 100PHEV 600 150 100 20Depending on the size of the battery, one could argue that the weight is increasing withincreasing power capacity. Considerations on varying the battery weight and vehicleefficiencies have been made based on [14]. It is decided not to include the battery weightboth because of the high uncertainty and because of the belief that the size of the batterywill be negatively correlated with the weight. That is, the lighter the battery per kWh, thelarger the capacity is incorporated in the EDV – approx. reaching the same drivingefficiency. Thus, the final weight of the vehicle is believed to end up more or less thesame.Two analyses are made:1. Analysis of the influence of the battery capacity. In this analysis it is assumedthat 25 % of the vehicle fleet is BEVs and 75% PHEVs. These assumptions arebased on data from DST where the share of 2nd, 3rd, etc. vehicle in thehousehold sums up to 25%.2. Analysis of the influence of battery pricing. This is done by changing the pricefor different battery capacities. The model invests in the most optimal vehiclefleet as well as the optimal heat and power system.An overview of the scenarios tested for analysis 1 is shown in Table 4. The table leavesout unrealistic combinations, i.e., small batteries in the BEVs and large batteries in thePHEVs.Table 4 Scenarios run for analysing the influence of the battery capacityType BEV BEV BEV BEV BEVkWh 15 29 43 58 72PHEV 3 xPHEV 4.5 x xPHEV 6 x xPHEV 7.5 x x x xPHEV 9 x x x xPHEV 11.5 x x x xPHEV 15 x x xIn order to analyse the influence of the battery prices many scenarios are run as shown inTable 5.Table 5 Annual vehicle price depending on the battery price (€/year)Battery Price kWh €150/kWh €250/kWh €300/kWh €500/kWh €600/kWhPHEV 3 1122 1150 1177 1219 1247PHEV 4.5 1143 1184 1226 1288 1330PHEV 6 1164 1219 1274 1357 1413PHEV 7.5 1184 1253 1323 1426 1496PHEV 9 1205 1288 1371 1496 1579PHEV 11.5 1240 1346 1452 1611 1717PHEV 15 1288 1426 1496 1772 1911Risø International Energy Conference 2011 Proceedings Page
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Energy Systems and Technologies for
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ContentsSessions overview 1Programm
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sessions overview08:00-09:00Coffee
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11:00 - 12:30 session 6A - Bioenerg
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ContactSustainable Energy, Technica
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Penetration of new energy technolog
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how decisions are made and by whom
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(9) is the logaritimic expansion of
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(16)we may finally write Eq(14) in
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Table 1: Fast track cases for new r
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Peterka V. Macrodynamics of technol
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Growth in clean and reliable energy
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Conclusion - an ambitious vision an
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"Spurring investments in renewable
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Integrating climate change adaptati
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transport, and finance. Energy prov
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northern South America, the Caribbe
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Table 1: Energy system adaptation s
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More generally, a number of no- or
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6 ReferencesADB, 2005. Climate proo
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Sailor, D.J., Smith, M., Hart, M.,
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Factors affecting stakeholder perce
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Another study conducted in Japan wa
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4 The effect of information on stak
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Furthermore, communication to stake
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Shackley S, McLachlan C, Gough C (2
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Figure 1: Potential CO 2 storage si
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The Upper Jurassic - Lower Cretaceo
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The majority of the individual stru
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Development. Project no. ENK6-CT-19
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Section 5 summarises the key issue
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Table 1. Efficiencies for new large
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In addition, district heating syste
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6.4 Model results from EFDA-TIMESIn
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Maisonnier, D., et al. (2007), Powe
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1Efficiency and effectiveness of pr
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3Stromerzeugung [TWh/a]250200150100
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54 Country-specific Lessons learned
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7100%90%80%quota fullfilment (%)70%
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[5] Haas R., et al: Efficiency and
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The development and diffusion of re
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a. Offshore wind in DenmarkDenmark
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applicants are invited to submit a
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nies that provide upstream and down
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for both technology users and produ
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Trade Disputes over Renewable Energ
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treatment to imported renewable ene
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In Canada, the federal government i
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grid access, subsidies and land off
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In 2010, China’s total wind insta
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Source: Renewables 2010 Global Stat
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Source: REN 21, Renewables 2010 Glo
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Source: adapted from REN21, 2010It
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their precise scope and nature diff
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60 daysBy 2 nd DSBmeetingConsultati
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discriminatory manner on domestic a
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the European Union, the North Ameri
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ended. China lost this case because
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As most countries in the world are
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Session 3A - Energy SystemsRisø In
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1 IntroductionWith the introduction
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occur. This is an undesirably burea
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This curve could be used as a new t
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ut for the total consumption, and i
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This gives the LBR an opportunity t
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concludes that the subsurface conta
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to constrain the evaluation. In add
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Fig. 2 SW-NE trending seismic profi
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Fig. 5. Petrophysical evaluation of
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ConclusionsThe Danish subsurface co
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Performance of Space Heating in aMo
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[5],[10],[11],[16],[18],[20],[26].
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2/3 Sun1 Coal1/3 ElPower plantHP1 H
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25002000Surplus(min(wind,prod-cons)
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160CO 2 emission per unit heat prod
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The calculations have been based on
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Session 3B - smart gridsRisø Inter
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2 Myopic Investments2.1 The Balmore
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Moreover, this model is formulated
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Reducing Electricity Demand Peaks b
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3 Event Driven Scheduling Algorithm
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5 Mapping Teletraffic Theory to Ene
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6.2 Results and Performance Metrics
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Energy Efficient Refrigeration and
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Virtual Power PlantAggregatorSuperm
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C p,rC p,fT rT fW cφ sT a(UA) raHe
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Total PowerP.G. #1P.G. #2C.R. #1201
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the availability payment.Simulation
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The constraint in Eq. (16) has the
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The FlexControl concept - a vision,
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can react on requests for power reg
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3 ControlThe concept is based solel
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one hour to the next - correspondin
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4 ProtectionThe protection of the p
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Session 4 - Efficiency Improvements
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the product portfolio point of view
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Figure 4: Principle flow sheet of t
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process information needed are seld
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AIRFINE®(Reference)MEROS®Ca(OH)2M
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4 Conclusion & DiscussionThe Eco-Ca
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1 Energy policy and EU directivesTh
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iomass CHP, heat pumps, electric bo
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Fig. 1: How to supply a growing hea
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Session 5A - Wind Energy IRisø Int
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The average cumulative growth rate
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turbines is expected to create a st
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O&MGridWindturbineSubstructureFigur
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Another idea is to harvest energy f
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9. Shimon Awerbuch, Determining the
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engaged in wind energy assessment,
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treated in such a way to make them
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Figure 5: Map showing the estimated
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Figure 9: The annual mean power den
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mix is required. For example diurna
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Session 5B - Wind Energy IIRisø In
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TABLE ISOME OF THE WIND TURBINE MAN
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China, has prompted all parties, in
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to the high shaft speed. Furthermor
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Superconductors must be kept cold b
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an annual increase in demand of 6%,
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Improved High Temperature Supercond
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our study to a single set of deposi
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3.2 Yttrium-enriched YBCO thin film
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Fig. 5. AC-susceptibility dependenc
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The j C (B) dependence at 50 K for
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Session 6A - Bioenergy IRisø Inter
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The European politicians are faced
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The fast growing demand for biomass
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Figure 2: Avedøre Power Plant in C
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Figure 5: Concept for a sustainable
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The role of biomass and CCS in Chin
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2.2.1 CCS Potential for ChinaCCS is
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80%70%60%China's share ofglobal CO
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In general, if the CCS technology d
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with high implementation of CCS Chi
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The European Biofuels Policy: from
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aimed to promote agriculture-based
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(EC, 2009b), and internationally vi
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Session 6B - Bio Energy IIRisø Int
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The commercial scale production of
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the production process parameters,
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NutrientWaterAlgal cultureproductio
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Schenk, P.M., Thomas-Hall, S.R., St
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Liquid biofuels from blue biomassZs
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Even though final ethanol yields we
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Integrated Gasification SOFC Plant
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2.1 Modelling of SOFCThe SOFC model
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where g 0 , R an T are the specific
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hand side y-axis corresponds to eff
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The moister content for these three
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Use of Methanation for Optimization
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power production from utilizing the
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2.1 Model DescriptionThe developed
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Figure 3: Flow sheet of methanation
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efficiency and turbine inlet temper
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[14] DNA - A Thermal Energy System
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On the effectiveness of standards v
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educing new car emissions to 120 g
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In addition energy consumption E an
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coefficient γ for the impact of fu
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400200Change in energy (PJ)01980 19
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Figure 9 depict scenarios for the f
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What are customers willing to pay f
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Randomly, continuous up to ±50%Acc
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The likelihood for the model is giv
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eally means that this factor and no
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Table 5-1 Parameter estimates from
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Table 6-2 Willingness to pay for 10
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Session 12 - Energy for Developing
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Risø International Energy Conferen
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existing renewable energy technolog
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useful energyend energysecondary en
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parts or the means of enforcing war
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The development of micro-hydro proj
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Table 1. Electric power generation
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5 ReferencesBajgain, S., Shakya, I.
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IntroductionElectricity has become
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of 2008, 43.6% of the total populat
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Hilmand provinces have comparativel
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….. eq. 5LCOE is the net present
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case of Nepal, it is 5% (Trading ec
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Page 374 and 375: 3.3 Serving the rural areas with na
Page 376 and 377: The levelized costs of electricity
Page 378 and 379: Figure 4. Variation in LCOE with si
Page 380 and 381: The analysis reveals that fuel cost
Page 382 and 383: In case of DG, we have looked with
Page 384 and 385: Gross, R., Blyth, W., Heptonstall,
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Page 398 and 399: increases, individuals acquire more
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Page 402 and 403: into CO 2 . For all oil and oil pro
Page 404 and 405: impact. In general, income is found
Page 406 and 407: 7 ReferenceAlperovich, G., Deutsch,
Page 408 and 409: Table 1: Definitions of Variables a
Page 410 and 411: Session 13 - Energy StorageRisø In
Page 412 and 413: 2 Storage demand and resulting stor
Page 414 and 415: compressed air storages, demand sit
Page 416 and 417: Fig. 3: Options for underground sto
Page 418 and 419: 3.5 Geological potential in EuropeF
Page 420 and 421: Sensitivity on Battery Prices and C
Page 424 and 425: 4 ResultsThe model is run on a comp
Page 426 and 427: Furthermore, a slight decrease in t
Page 428 and 429: Night time charging increases with
Page 430 and 431: Lithuanian Energy Institute, PSE In
Page 432 and 433: atteries, Compressed Air Energy Sto
Page 434 and 435: negative net load, can be expected
Page 436 and 437: 25%Pct. of the year20%15%10%5%0.5-0
Page 438 and 439: 800006000040000MWh200000Netload-200
Page 440 and 441: [4] B. V. Mathiesen and H. Lund, "C
Page 442 and 443: Compressed Air Energy Storage in Of
Page 444 and 445: compressed air caverns, corrosion-r
Page 446 and 447: Figure 3: Distribution of salt depo
Page 448 and 449: Figure 6: EWEA's 20 year Offshore N
Page 450 and 451: spinning reserves can be provided b
Page 452 and 453: 7 Discussion and conclusionsThis pa
Page 454: Risø DTU is the National Laborator
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