Energy Systems and Technologies for the Coming Century ...

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6.2 Results and Performance MetricsThe scenarios described in the previous subsection are simulated to obtain the meanwaiting time for each service class. This is presented in Table III and IV.The mean waiting time is the time the appliance has to wait before it is granted power. Inthe system described, high priority appliances are always granted power so their meanwaiting time should be zero. However, due to the fact that the RFS algorithm does notpause class 2 appliances when a class 1 appliances request is received the mean waitingtime for class 1 is not zero. The CS is responsible for discriminating the classes inpriorities, as described in section 3. Nevertheless, after measuring the mean waiting timefor each service class, it can be calculated how much time the low priority classes will bedelayed. This is the sum of the mean waiting time of class 1 and class 2.Table III and Table IV present the simulation results for 750 watts maximumconsumption and 1000 watts maximum consumption, respectively.ClassesClass 1High PriorityClass 2Low PriorityMean Waiting TimeRFS algorithmMean Waiting TimeScheduling algorithm6,74 min 0 min29,36 min 36,1 minTable III: RFS Algorithm Results for 750 watts maximum consumptionClassesClass 1High PriorityClass 2Low PriorityMean Waiting TimeRFS algorithmMean Waiting TimeScheduling algorithm1,08 min 0 min11,28 min 12,36 minTable IV: RFS Algorithm Results for 1000 watts maximum consumptionBy setting the maximum consumption to 750 watts the low priority appliances will inaverage take 36,1 minutes longer to finish their tasks than if there was no maximumconsumption limit. On the other hand, if the maximum consumption is set to 1000 wattsthe delay of low priority appliances is only of 12,36 minutes. As stated before, highpriority appliances will not be affected by setting a consumption limit and will neverhave to wait for consuming electricity. Considering that low priority appliances taskstake around 120 minutes to finish, setting a consumption limit to 750 watts willincrement their task time a 30,1% and 10,3% when the consumption limit is set to 1000watts.7 ConclusionIn this paper, an event driven scheduling algorithm for regulating electricity demandpeak for home appliances is presented. The objective of the system is to provide a toolfor scheduling the operation of daily use home devices, guaranteeing that a maximumlimit of power consumption is never exceeded during peak demand hours. The latter canbe beneficial for both users and energy companies, as explained throughout this paper.To analyze the proposed event scheduling algorithm, Reversible Fair Scheduling (RFS)is used. RFS is a bandwidth allocation algorithm and originates from teletraffic theory.The parameters of RFS algorithm have been adjusted to the home appliancescharacteristics and users’ appliance usage.The scenario presented in this paper considers some of the appliances found in a modernhousehold, where the electrical devices are classified in low and high priority groups.Risø International Energy Conference 2011 Proceedings Page 162
The high priority appliances are always granted power and are never paused. On thecontrary, the low priority appliances have to pause their operation, when the schedulingalgorithm dictates it, and resume later on. The effectiveness is verified by the RFSalgorithm with data obtained from real appliances and studies about users’ appliancesusage. Two scenarios with different maximum power limits have been simulated, 750watts and 1000 watt. For a consumption limit of 750 watts, the low priority applianceswill have a delay of approximately 36 minutes, which supposes a 30% increment in theirtask time. However, if the consumption limit is 1000 watts the delay is reduced toapproximately 12 minutes, which supposes only an increment of a 10% in their tasktime.8 References[1] Iversen, V.B., “Teletraffic Theory and Network Planning”, Technical University ofDenmark, 2010 Textbook. Available: http://oldwww.com.dtu.dk/teletraffic/handbook/telenook.pdf[2] Iversen, V.B., “Reversible Fair Scheduling: the teletraffic revisited”, 20thInternational Teletraffic Congress, Ottawa, Canada 2007.[not used] M. Chanbari, C.J. Hughes, M.C. Sinclair, J. P. Eade, “Principles ofPerformance Engineering for telecommunication and information systems” (IEEEelecommunications Series) 1997.[3] Evangelos Iliakis, Georgios Kardaras, “Resource Allocation in Next GenerationInternet: Provisioning QoS for Future Networks based on Teletraffic Theory”, 2010.[4] “The Smart Grid: An Introduction”, sponsored by DOE’s Office of ElectricityDelivery and Energy Reliability, U.S Department of Energy, 2008.[5] LG 32LE4900, Specifications, ECO, accessed 10 March 2011,http://www.lg.com/uk/tv-audio-video/televisions/LG-led-tv-42LE4900.jsp[6] LG DVX550, Specifications, POWER, accessed 10 March 2011,http://www.lg.com/uk/tv-audio-video/video/LG-dvd-player-DVX550.jsp[7] Pioneer S-HS111US, Specifications, accessed 10 March 2011,http://www.pioneerelectronics.com/PUSA/Home/Home-Theater-Systems/S-HS111US[8] HP Pavilion Slimline s5670t series, Specs, accessed 10 March 2011,http://www.shopping.hp.com/webapp/shopping/store_access.do?template_type=series_detail&category=desktops&series_name=s5670t_series&jumpid=in_R329_prodexp/hhoslp/psg/desktops/promo_tile/3/dt_promo_tile3_s5670t_113[9] Samsung BX2340, accessed 10 March 2011, http://www.samsung.com/uk/consumer/pcperipherals/monitors/professional/LS23CBUMBV/EN/index.idx?pagetype=prd_detail&tab=specification[10] Siemens WM12S32XEE, Ficha tecnica, accessed 10 March 2011,http://www.siemens-home.es/WM12S32XEE.html[11] Bosch WTW8658XEE, Ficha tecnica, accessed 10 March 2011, http://www.boschhome.es/WTW8658XEE.html[12] Bosch SMS69T25EU, Ficha tecnica, accessed 10 March 2011,http://www.boschhome.es/SMS69T25EU.html[13] U.S. Energy Information Administration, Independent Statistics and Analysis.Available: http://www.eia.doe.govRisø International Energy Conference 2011 Proceedings Page 163
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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
Page 115: ended. China lost this case because
Page 118 and 119: As most countries in the world are
Page 120 and 121: Session 3A - Energy SystemsRisø In
Page 122 and 123: 1 IntroductionWith the introduction
Page 124 and 125: occur. This is an undesirably burea
Page 126 and 127: This curve could be used as a new t
Page 128 and 129: ut for the total consumption, and i
Page 130 and 131: This gives the LBR an opportunity t
Page 132 and 133: concludes that the subsurface conta
Page 134 and 135: to constrain the evaluation. In add
Page 136 and 137: Fig. 2 SW-NE trending seismic profi
Page 138 and 139: Fig. 5. Petrophysical evaluation of
Page 140 and 141: ConclusionsThe Danish subsurface co
Page 142 and 143: Performance of Space Heating in aMo
Page 144 and 145: [5],[10],[11],[16],[18],[20],[26].
Page 146 and 147: 2/3 Sun1 Coal1/3 ElPower plantHP1 H
Page 148 and 149: 25002000Surplus(min(wind,prod-cons)
Page 150 and 151: 160CO 2 emission per unit heat prod
Page 152 and 153: The calculations have been based on
Page 154 and 155: Session 3B - smart gridsRisø Inter
Page 156 and 157: 2 Myopic Investments2.1 The Balmore
Page 158 and 159: Moreover, this model is formulated
Page 160 and 161: Reducing Electricity Demand Peaks b
Page 162 and 163: 3 Event Driven Scheduling Algorithm
Page 164 and 165: 5 Mapping Teletraffic Theory to Ene
Page 168 and 169: Energy Efficient Refrigeration and
Page 170 and 171: Virtual Power PlantAggregatorSuperm
Page 172 and 173: C p,rC p,fT rT fW cφ sT a(UA) raHe
Page 174 and 175: Total PowerP.G. #1P.G. #2C.R. #1201
Page 176 and 177: the availability payment.Simulation
Page 178 and 179: The constraint in Eq. (16) has the
Page 180 and 181: The FlexControl concept - a vision,
Page 182 and 183: can react on requests for power reg
Page 184 and 185: 3 ControlThe concept is based solel
Page 186 and 187: one hour to the next - correspondin
Page 188 and 189: 4 ProtectionThe protection of the p
Page 190 and 191: Session 4 - Efficiency Improvements
Page 192 and 193: the product portfolio point of view
Page 194 and 195: Figure 4: Principle flow sheet of t
Page 196 and 197: process information needed are seld
Page 198 and 199: AIRFINE®(Reference)MEROS®Ca(OH)2M
Page 200 and 201: 4 Conclusion & DiscussionThe Eco-Ca
Page 202 and 203: 1 Energy policy and EU directivesTh
Page 204 and 205: iomass CHP, heat pumps, electric bo
Page 206 and 207: Fig. 1: How to supply a growing hea
Page 208 and 209: Session 5A - Wind Energy IRisø Int
Page 210 and 211: The average cumulative growth rate
Page 212 and 213: turbines is expected to create a st
Page 214 and 215: 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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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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