Energy Systems and Technologies for the Coming Century ...

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Energy Efficient Refrigeration and Flexible PowerConsumption in a Smart GridTobias Gybel Hovgaard, Rasmus Halvgaard, Lars F. S. Larsen and John Bagterp JørgensenAbstractRefrigeration and heating systems consume substantial amounts of energy worldwide.However, due to the thermal capacity there is a potential for storing “coldness” or heatin the system. This feature allows for implementation of different load shifting and sheddingstrategies in order to optimize the operation energywise, but without compromising theoriginal cooling and indoor climate quality. In this work we investigate the potential of sucha strategy and its ability to significantly lower the cost related to operating systems suchas supermarket refrigeration and heat pumps for residential houses. With modern EconomicModel Predictive Control (MPC) methods we make use of weather forecasts and predictionsof varying electricity prices to apply more load to the system when the thermodynamic cycleis most efficient, and to consume larger shares of the electricity when the demand and therebythe prices are low. The ability to adjust power consumption according to the demands on thepower grid is a highly wanted feature in a future Smart Grid. Efficient utilization of greateramounts of renewable energy calls for solutions to control the power consumption such thatit increases when an energy surplus is available and decreases when there is a shortage. Thisshould happen almost instantly to accommodate intermittent energy sources as e.g. windturbines. We expect our power management solution to render systems with thermal storagecapabilities suitable for flexible power consumption. The aggregation of several units willcontribute significantly to the shedding of total electricity demand. Using small case studieswe demonstrate the potential for utilizing daily variations to deliver a power efficient coolingor heating and for the implementation of Virtual Power Plants in Smart Grid scenarios.1 IntroductionThe energy policies in the Nordic countries stipulate that 50% of the energy consumedby 2025 should come from renewable and CO 2 -free energy sources. By 2050 the Nordiccountries should be independent of fossil fuels. This transformation of the energy systemis needed to reduce CO 2 emissions and global warming as well as to protect the Nordiceconomies from the consequences of sharply rising prices of fossil fuels due to an increasingworld population and depletion of fossil fuel resources [1]. To obtain an increasing amount ofelectricity from intermittent energy sources such as solar and wind, we must not only controlthe production of electricity but also the consumption of electricity in an efficient, agile andproactive manner. In contrast to the current rather centralized power generation system, thefuture electricity grid is going to be a network of a very large number of independent powergenerators. The Smart Grid is the future intelligent electricity grid and is intended to be thesmart electrical infrastructure required to increase the amount of green energy significantly.The Danish transmission system operator (TSO) has the following definition of Smart Gridswhich we adopt in this work: ”Intelligent electrical systems that can integrate the behaviorand actions of all connected users - those who produce, those who consume and thosewho do both - in order to provide a sustainable, economical and reliable electricity supplyefficiently” [2]. In this paper we utilize the flexibility of the refrigeration system to offerancillary demand response to the power grid as regulating power. Different means of utilizingdemand response have been investigated in an increasing number of publications e.g. [3]–[6]for plug-in electrical vehicles and heat pumps and in general concerning price elasticity in [7].In this paper we consider two utilizations of a vapor compression cycle. One for supermarketrefrigeration and one for heating residential buildings using heat pumps. Buildings accountfor approximately 40% of the total energy use in the Nordic countries and in Denmarkaround 4500 supermarkets consume more than 550 GWh annually. As heat pumps areT. G. Hovgaard and L. F. S. Larsen are with Danfoss Refrigeration and A/C Controls, DK-6430 Nordborg,Denmark. {tgh,lars.larsen}@danfoss.comR. Halvgaard and J. B. Jørgensen are with DTU Informatics, Technical University of Denmark, DK-2800 Lyngby,Denmark. {rhal,jbj}@imm.dtu.dkRisø International Energy Conference 2011 Proceedings Page 164
driven by electricity and connected to house floors with large thermal capacities, they havea large potential to shift the electricity consumption and adapt to the stochastic electricityproduction from wind turbines. The same holds for refrigeration systems where the thermalcapacity in the refrigerated goods can be used to store ”coldness” and thereby shift the loadin time while keeping the temperatures within certain bounds. These bounds are chosensuch that they have no impact on food quality and indoor comfort. We exploit that thedynamics of the temperature in the cold room and residential buildings are rather slow whilethe power consumption can be changed rapidly.Simple weather conditions such as outdoor temperature and solar radiation are includedin our simulation models. By including forecasts of prices and weather conditions energyconsumption is made flexible. It is thus possible to predict where to place the energyconsumption and minimize the electricity cost of operating the systems without violatingthe constraints such as indoor temperature comfort intervals and food storage conditions.The thermal capacities determine how much of the electricity consumption that can beshifted to times with cheap electricity. We investigate different scenarios spanning from acase study with total collaboration between producers and consumers to decoupling throughprice signals from the NordPool electricity spot market. Utilizing load shifting capabilitiesto reduce total energy consumption has also been described in e.g. [8], [9].Our proposed control strategy is an economic optimizing model predictive controller,Economic MPC. Predictive control for constrained systems has emerged during the last 30years as one of the most successful methodologies for control of industrial processes [10]and is increasingly being considered for both refrigeration and power systems control [11],[12]. MPC based on optimizing economic objectives has only recently emerged as a generalmethodology with efficient numerical implementations and provable stability properties [13].This paper is organized as follows. In section 2 we discuss different control architecturesfor enabling flexible consumption from many distributed units in a Smart Grid. Section 3describes the models used in our case studies as well as the formulation of our EconomicMPC strategy. In section 4 the simulations and results for three cases are illustrated. Thefirst two cases demonstrate direct control and price signal based control with rather simplemodels while the third case uses more advanced nonlinear models verified with data fromreal supermarkets and a combination of price and frequency based control. In section 5 meansfor handling uncertainties in the framework of our proposed strategy are presented. We giveconclusions in 6.2 Control Architectures for Virtual Power PlantsA way of creating flexibility in the power grid is Virtual Power Plants (VPP). The conceptpools several, otherwise too small, production and consumption units, such as multiplesmaller power plants, wind turbines and heat pumps, and make them behave as one unit.The VPP concept enables a huge amount of possibilities for load balancing since it allowsactive control of the consumer [14].In this paper we consider individual thermal storage units such as refrigeration systems andhouses with heat pumps that are to be aggregated in the VPP framework (see Fig. 1). Thecontrol within the aggregated units can rely on different strategies. The following controlstrategies have been suggested for load balancing and load shifting in electrical grids [15].1) Direct control. In this case producers and consumers are assumed to collaborate on acommon goal of minimizing the total cost of operation. Given that the communicationinfrastructure required for sending control signals to the consumers to raise or reducethe demand is established, the producers are allowed a more direct control of thedemand. Furthermore, it allows the controller in the consumer to be quite simple as itonly sends information and receives commands from the VPP. The drawback of courseis that the VPP must solve large-scale optimization problems to coordinate a largenumber of units. The result might not be optimal for the consumer alone and the VPPdecides the consumption schedule entirely.Risø International Energy Conference 2011 Proceedings Page 165
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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
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
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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 166 and 167: 6.2 Results and Performance Metrics
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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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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