Energy Systems and Technologies for the Coming Century ...

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4 SummaryThe penetration of new energy technologies in the techno-socio-economic frame wasinvestigated. A review of different models was provided. In the analyses, an empiricaldiffusion type of energy growth model was employed (but subject to imposed limitationscontrary to epidemic type of models).Our results shows that renewable electricity could reach a 60% share of all electricity in2050 if just assuming the same kind of growth for the new technologies as for the oldones in the past. The new renewables would stand for 43% of all electricity, i.e. a majorpart of the growth would come from the new technologies indeed.We also investigated fast-track cases in which the new technologies are allowed to growas oil did in the past. Now RES-E could reach very high shares, even close to 100%.However, several constraints for such scenario beyond traditional cost or integrationissues could be identified: high RES-E shares would require replacement of existingtraditional capacity before their end of life-time, and if electricity demand growth is notstabilized, the total amount of RES vis-à-vis existing infrastructures may be in mismatch.Therefore, in case of fast-track strategies energy efficiency and RES need to be linkedstronger together.Finally, industries’ capability to generate revenues for further investments and volumegrowth was studied. Analyzing top companies, a self-financeable capacity expansionpotential of 14-99%yr (2008) in wind power industry and 60% in average in PV(plunged to 20% in 2009) were found which could facilitate a sustained growth path.However, a decreasing trend was found in all RES which may indicate lowering profitmargins explained by harder competition, larger investments in manufacturing lines andR&D needs with raising volumes that may eventually lead to decreasing annual growth.5 LiteratureBarreto L, Kemp R. Inclusion of technology diffusion in energy-systems models: somegaps and needs. Journal of Cleaner Production 2008; 16S1: S95-S104.Churchill NC, Mullins JW. How fast can your company afford to grow? HarvardBusiness Review, May 2001, 135-142.Fisher JC, Pry RH. A simple substitution model for technological change.TechnolForecast Soc Change 1971; 3: 75–88.Geroski PA. Models of technology diffusion. Research Policy 2000; 29:603-625.Henderson R, Newell RG. Accelerating innovation in energy: insights from multiplesectors. Harvard Business School, Working Paper 10-067, 2010.Kramer GJ, Haigh M. No quick switch to low-carbon energy. Nature 2009: 462; 568-569.Lund PD. Fast market penetration in retrospect with application to clean energy futures.Applied Energy 2010; 87: 3575–3583.Lund PD. Exploring past energy changes and their implications for the pace ofpenetration of new energy technologies. Energy 2010;35:647–56.Mahajan V, Muller E, Bass F. New product diffusion models in marketing: a review anddirections for research. J Mark 1990;54:1–26.Malyshkina N, Niemeir D, Future of sustainability forecasting by exchange markets:basic theory and an application. Environ.Sci.Technol. 2010;44:9134-9142.Risø International Energy Conference 2011 Proceedings Page 16
Peterka V. Macrodynamics of technological change: market penetration by newtechnologies. International Institute for Applied System Analysis, IIASA Report RR-77-22, Laxenburg, Austria, 1977.Peterka V, Fleck F. The dynamics of energy systems and the logistic substitution model.Volume 2: Theoretical part. International Institute for Applied System Analysis, IIASAReport AR-78-1C, Laxenburg, Austria, 1978.Polgreen PM, Nelson FD, Neumann GR. Use of prediction markets to forecast infectiousdisease activity. Healthcare Epidemiology 2007;44: 272-278.Rao UK, Kishore VVN. A review of technology diffusion models with special referenceto renewable energy technologies. Renewable and Sustainable Energy Reviews 2010;14:1070-1078.Rogers EM. Diffusion of innovations. Forth Edition. The Free Press, New York, 1995.Spinrad BI. Market substitution models and economic parameters. International Institutefor Applied System Analysis, IIASA Report RR-80-28, Laxenburg, Austria, 1980.Sterman JD, Henderson R, Beinhocker ED, Newman LI. Getting big too fast: strategicdynamics with increasing returns and bounded rationality. Management Science 2007;53: 683-696.Stoneman P. Handbook of the economics of innovation and technological change. UK:Blackwell Publishers Ltd; 1995ediction markets. Journal of Economic Perspectives2004; 18: 107-126..Risø International Energy Conference 2011 Proceedings Page 17
Page 1 and 2: Energy Systems and Technologies for
Page 3 and 4: ContentsSessions overview 1Programm
Page 5 and 6: sessions overview08:00-09:00Coffee
Page 7 and 8: 11:00 - 12:30 session 6A - Bioenerg
Page 9 and 10: ContactSustainable Energy, Technica
Page 11 and 12: Penetration of new energy technolog
Page 13 and 14: how decisions are made and by whom
Page 15 and 16: (9) is the logaritimic expansion of
Page 17 and 18: (16)we may finally write Eq(14) in
Page 19: Table 1: Fast track cases for new r
Page 23 and 24: Growth in clean and reliable energy
Page 25 and 26: Conclusion - an ambitious vision an
Page 27 and 28: "Spurring investments in renewable
Page 29 and 30: Integrating climate change adaptati
Page 31 and 32: transport, and finance. Energy prov
Page 33 and 34: northern South America, the Caribbe
Page 35 and 36: Table 1: Energy system adaptation s
Page 37 and 38: More generally, a number of no- or
Page 39 and 40: 6 ReferencesADB, 2005. Climate proo
Page 41 and 42: Sailor, D.J., Smith, M., Hart, M.,
Page 43 and 44: Factors affecting stakeholder perce
Page 45 and 46: Another study conducted in Japan wa
Page 47 and 48: 4 The effect of information on stak
Page 49 and 50: Furthermore, communication to stake
Page 51 and 52: Shackley S, McLachlan C, Gough C (2
Page 53 and 54: Figure 1: Potential CO 2 storage si
Page 55 and 56: The Upper Jurassic - Lower Cretaceo
Page 57 and 58: The majority of the individual stru
Page 59 and 60: Development. Project no. ENK6-CT-19
Page 61 and 62: Section 5 summarises the key issue
Page 63 and 64: Table 1. Efficiencies for new large
Page 65 and 66: In addition, district heating syste
Page 67 and 68: 6.4 Model results from EFDA-TIMESIn
Page 69 and 70: 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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Page 344 and 345:
Page 346 and 347:
Page 348 and 349:
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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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ing down the cost of solar PV modul
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3.3 Serving the rural areas with na
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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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