Energy Systems and Technologies for the Coming Century ...

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3 Event Driven Scheduling AlgorithmIn order to keep the total consumption of the household under the determined limit, anevent driven scheduling algorithm is used. The flow of the algorithm is determined bytwo events. Arrival event occurs when an appliance is switched on and requests to useelectricity. Departure event occurs when an appliance has finished its task and stopsconsuming electricity. The algorithm the CS uses is shown in Fig. 2.Figure 2: Event Driven Scheduling AlgorithmIn order for the appliance to be able to send the request message to the CS, the applianceneeds to consume some power. However, this consumption is not considered in thispaper as a simplified model is used. In the same way, when an appliance is paused it hasto be able to listen for the resume message from the CS. This consumption is also nottaken into consideration in this simplified model.When the user turns on an appliance, the CS will receive a request from that appliance toconsume power. The CS will then calculate if there is enough power to turn on thatappliance without exceeding the maximum consumption:1max_ consumption x i xNi1where max_consumption is the defined maximum electricity consumption, N 1 is thenumber of appliances turned on, x i is the consumption of the appliance i and x new is theconsumption of the appliance the user just switched on. If equation (1) stands then theappliance requesting to consume electricity is turned on as the total consumption doesnot exceed the limit. On the other hand, if equation (1) does not stand, the CS proceedsto examine the priorities of the appliances. The CS will try to find a set of N 2 appliances,which are already turned on (N 2 N 1 ), and which have lower priority than the appliancerequesting to consume. So the following equation is fulfilled:newN 2 N 1new x j (max_ consumption xi)j1i1(1)x (2)where x j is the consumption of the appliance j and the term in between brackets is theavailable consumption before the limit consumption is reached. If the CS can find a setN 2 that verifies equation (2), these appliances will be paused and added to the pausedappliances list. The CS will send the command pause to the N 2 appliances and it willgrant access to the new appliance, as the maximum consumption is not exceeded. On thecontrary if the CS cannot find a set of N 2 appliances that fulfill equation (2), theappliances requesting power will be added to the paused appliances list.Risø International Energy Conference 2011 Proceedings Page 158
When an appliance is turned off or it has finished its task, the CS will detect this as adeparture event. If the paused appliances list is not empty, the CS will evaluate thefollowing equation:1max_ consumption x i xNi1pausedwhere x paused is the power consumption of the paused appliance found in the pausedappliances list. If equation (3) stands, this paused appliance will receive a resumecommand from the CS and will be removed from the paused appliances list.Furthermore, if the paused appliances list still contains paused appliances, the CS willevaluate equation (3) again until there are no more appliances left in the pausedappliances list or the maximum consumption is reached. The CS evaluates theappliances in the paused appliances list in input order, FIFO (first-in-first-out), as theywill all have the same priority, low priority.(3)4 Teletraffic Theory RevisedTeletraffic engineering is the application of probability theory and stochasticmathematical modeling for solving problems concerning network planning, evaluatingnetwork performance and deriving the relationship between grade-of-service and systemcapacity [1]. The aim is to dimension the network accordingly and establish theappropriate traffic controls. In case of different services, traffic classes are used toaggregate the services according to their grade-of-service requirements. The user flows,or the data to be transmitted by the users, are divided in classes. This division is used asthe basis for differentiated processing and service.The Reversible Fair Scheduling (RFS) algorithm presented and used in this paper has itsorigin in teletraffic engineering. It is a bandwidth allocation scheduling algorithm and itsaim is to allocate resources dynamically to networks supporting multiple services. Theresources are allocated depending on the type of user request.Therefore, the service requiring the highest amount of resources will be served, as longas, the total capacity or defined limit of the system is not exceeded. As shown in Figure3, a communication link consists of n channels and k buffers. The total number ofsupported services classes is N, which occupy the resources of the communication link.The system will receive requests from these N classes to use some of the n channels incommunication link. When a request is received for one of the classes that requires lesschannels than the available number in the link, it can be served immediately [1, 2].Fig. 1: Resource allocation in a network communication link [3].Risø International Energy Conference 2011 Proceedings Page 159
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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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Page 113 and 114: 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 164 and 165: 5 Mapping Teletraffic Theory to Ene
Page 166 and 167: 6.2 Results and Performance Metrics
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
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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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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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