Energy Systems and Technologies for the Coming Century ...

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What are customers willing to pay for futuretechnology vehicles.Jørgen Jordal-Jørgensen, COWIAbstractIn the energy sector there is a growing need to understand what customers want. Statedpreference is the perfect technique for doing so, particularly where there is no historicalprecedence. It was originally introduced for use in the transportation sector, but is nowused across a very wide variety of sectors including, amongst others: energy, finance,communications and health.Its strengths lie in the fact that it is a particularly robust means of prioritising product orservice features, determining the relative values of the different potential attributes of aproduct of service and showing what people would be willing to pay for differentproducts and services. The reasons for it being more robust than other techniques arebecause it places respondents in a more “realistic” choice scenario by presenting apackage of features for them to choose from (as would be the case for products andservices in a real choice environment), rather than asking them to comment on individualfeatures in isolation and because the resultant data much more clearly distinguishesrelative priorities than standard questions (such as the use of importance ratings) can do.In the energy sector the stated preference technique is increasingly used to determinewhat customers would be willing to pay for investments in infrastructure and service andto provide robust data in response to regulatory requirements. It has also been used toexplore the premium that customers would pay for green energy and to look at the likelychurn between products and suppliers as prices and product specifications change.The current paper presents main findings from a Stated Preference survey of Danish carpurchasers' preferences for future technology vehicles with alternative (green) fuels.1 BackgroundThe transport sector accounts for 24% of Danish CO, emissions. One way to reduceCO2-emissions is to increase use of renewable energy like for instance wind energy, inthe transport sector. Wind energy may be transformed to hydrogen - or be used to chargebatteries for electric vehicles. But the question is, are the consumers willing to purchasethe new technologies. This is the issue in the current survey.In the absence of actual choice observations on new vehicle technologies, known asrevealed preferences (RP), researchers resort to innovative methods of data collectionusing hypothetical options, referred to as stated preferences. In such stated preferencesurveys, data can be obtained from the implementation of choice experiments, in whichattributes of hypothetical vehicles and their values are presented to households/respondents,who are asked to select their most preferred alternative.The main attributes in this survey are: Monetary cost (purchase price, fuel and maintenance cost) Fuel availability, the range between refuelling or recharging Vehicle performance like acceleration and interior space. Environmental attributes.Page 1 of 12Risø International Energy Conference 2011 Proceedings Page 322
2 MethodCar choice gamesThe objective of this stage is to obtain household preferences for alternative fuelledvehicles and to identify trade-offs and incentives for households to switch to cleanervehicle technologies. Vehicle options are labelled based on the fuel-type and class/sizeof the vehicle. The fuel-type label includes five options:Conventional gasoline and conventional dieselHydrogenhybrid-electricHydrogenElectricEach respondent gets 3 sets of choice situations. In each of the 3 sets, the choice sets forthe respondents were selected randomly.There are 10 different combinations of technologies.Choice set 1 Choice set 2 Choice set 3Conventional vs Hydrogen Hydrogen vs Hybrid Bio fuel vs Plug-inConventional vs Hybrid Hydrogen vs Biofuel Bio fuel vs HybridConventional vs Biofuel Hydrogen vs Plug-in Plug-in vs. HybridConventional vs Plug-in2.1 Choice DesignDuring each choice set, the reference technology and the alternative technology are keptconstant. Thus, in game 1 each respondent is asked to choose between the conventionalvehicle with unchanged characteristics and an alternative technology with varyingcharacteristics.As mentioned above, the design consists of three sets of games with four choices in eachgame for each respondent.The general idea is that the left-hand vehicle (the reference vehicle) is a vehicle of thesame size and price as the vehicle recently purchased by the respondent. The right-handvehicle (the alternative) has varying characteristics in each game.The table below shows how the characteristics for the alternative vehicle are variedduring the games.Table 2-1Attributes and levelsItemAlternatives/LevelsPurchase price Randomly, continuous up to ±50%Annual fuel cost and maintenance Randomly, continuous up to ±25%Range, Hydrogen-vehicles randomlyonce a monthonce every three weeksfortnightlyOnce a weektwice a weekevery other dayevery dayRange otherAverage (20% from empty of car bought)Page 2 of 12Risø International Energy Conference 2011 Proceedings Page 323
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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
Page 276 and 277: (EC, 2009b), and internationally vi
Page 278 and 279: Session 6B - Bio Energy IIRisø Int
Page 280 and 281: The commercial scale production of
Page 282 and 283: the production process parameters,
Page 284 and 285: NutrientWaterAlgal cultureproductio
Page 286 and 287: Schenk, P.M., Thomas-Hall, S.R., St
Page 288 and 289: Liquid biofuels from blue biomassZs
Page 290 and 291: Even though final ethanol yields we
Page 292 and 293: Integrated Gasification SOFC Plant
Page 294 and 295: 2.1 Modelling of SOFCThe SOFC model
Page 296 and 297: where g 0 , R an T are the specific
Page 298 and 299: hand side y-axis corresponds to eff
Page 300 and 301: The moister content for these three
Page 302 and 303: Use of Methanation for Optimization
Page 304 and 305: power production from utilizing the
Page 306 and 307: 2.1 Model DescriptionThe developed
Page 308 and 309: Figure 3: Flow sheet of methanation
Page 310 and 311: efficiency and turbine inlet temper
Page 312 and 313: [14] DNA - A Thermal Energy System
Page 314 and 315: On the effectiveness of standards v
Page 316 and 317: educing new car emissions to 120 g
Page 318 and 319: In addition energy consumption E an
Page 320 and 321: coefficient γ for the impact of fu
Page 322 and 323: 400200Change in energy (PJ)01980 19
Page 324 and 325: Figure 9 depict scenarios for the f
Page 328 and 329: Randomly, continuous up to ±50%Acc
Page 330 and 331: The likelihood for the model is giv
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Page 334 and 335: Table 5-1 Parameter estimates from
Page 336 and 337: Table 6-2 Willingness to pay for 10
Page 338 and 339: Session 12 - Energy for Developing
Page 340 and 341: Risø International Energy Conferen
Page 350 and 351: existing renewable energy technolog
Page 352 and 353: useful energyend energysecondary en
Page 354 and 355: parts or the means of enforcing war
Page 356 and 357: The development of micro-hydro proj
Page 358 and 359: Table 1. Electric power generation
Page 360 and 361: 5 ReferencesBajgain, S., Shakya, I.
Page 362 and 363: IntroductionElectricity has become
Page 364 and 365: of 2008, 43.6% of the total populat
Page 366 and 367: Hilmand provinces have comparativel
Page 368 and 369: ….. eq. 5LCOE is the net present
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Page 372 and 373: ing down the cost of solar PV modul
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The levelized costs of electricity
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Figure 4. Variation in LCOE with si
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The analysis reveals that fuel cost
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In case of DG, we have looked with
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Gross, R., Blyth, W., Heptonstall,
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Mode of Transport to Work, Car Owne
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power parity (PPP) basis, GDP per c
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83,385 to 109,108 while the number
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other purposes so that reduced fare
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emissions studies is that they were
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where I (·) is the indicator funct
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increases, individuals acquire more
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while that of other means of transp
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into CO 2 . For all oil and oil pro
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impact. In general, income is found
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7 ReferenceAlperovich, G., Deutsch,
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Table 1: Definitions of Variables a
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Session 13 - Energy StorageRisø In
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2 Storage demand and resulting stor
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compressed air storages, demand sit
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Fig. 3: Options for underground sto
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3.5 Geological potential in EuropeF
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Sensitivity on Battery Prices and C
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3.1 Base caseA northern European en
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4 ResultsThe model is run on a comp
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Furthermore, a slight decrease in t
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Night time charging increases with
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Lithuanian Energy Institute, PSE In
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atteries, Compressed Air Energy Sto
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negative net load, can be expected
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25%Pct. of the year20%15%10%5%0.5-0
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800006000040000MWh200000Netload-200
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[4] B. V. Mathiesen and H. Lund, "C
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Compressed Air Energy Storage in Of
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compressed air caverns, corrosion-r
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Figure 3: Distribution of salt depo
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Figure 6: EWEA's 20 year Offshore N
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spinning reserves can be provided b
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7 Discussion and conclusionsThis pa
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Risø DTU is the National Laborator
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