ATLANTIS – Simulationsmodell der europäischen Elektrizitätswirtschaft bis 2030

Gutschi, Christoph; Bachhiesl, Udo; Huber, Christoph; Nischler, Gernot; Jagl, Alexander; Süßenbacher, Wilhelm; Stigler, Heinrich

doi:10.1007/s00502-009-0703-8

Cited by 5 publications

(8 citation statements)

References 2 publications

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“…A similarly low total exergy efficiency of 21% can be found in Gutschi et al [3]. This study dealt with exergy flows in Austria in 1956 and 2005.…”

supporting

confidence: 63%

“…The amount of wood, wood products, wood waste, and black liquor is available per province was spatially resolved by using the forest area, the number of people working in the wood processing industry as well as the number of people working in the pulp and paper industry per municipality (Table 6). [144,146], 3 calculated with the actual share of the different tree species in Austria [145] and the higher heating value (water content 0%) as well as the specific density for each tree species [144].…”

Section: Biomassmentioning

confidence: 99%

“…[151], the total corn acreage of 2026 km 2 [139] and a fruit-straw-ratio of 1 [144], 5 calculated with a mean yield of 280 t rapeseed per km 2 [151], the total rapeseed acreage of 540 km 2 [139] and a mean fruit-straw-ratio of 2.8 [144], 6 calculated with a mean yield of 7320 t sugar beet per km 2 [151], the total sugar beet acreage of 448 km 2 [139] and a mean fruit-straw-ratio of 1.7 [144]. [156] as well as with the lower heating value of the biogas of 6.4 kWh/Nm 3 [157], 3 calculated with the amount of excrement per animal and year as well as the specific gas yield.…”

Section: Biomassmentioning

confidence: 99%

“…Current production of bio fuels and biogas using biomass from Austria. 3 In 2017, biogas plants in Austria produced a total of 565 GWh of electricity (mean efficiency of power units: 36.5% [154]) and 149 GWh of gas were fed into the public gas grid [158].…”

Section: Biomassmentioning

confidence: 99%

“…Exergy analyses of countries help to locate the sectors with the greatest potential for savings (Section 3.1). Such analyses have already been made for various countries, including Austria [3]. However, this study about Austria is not spatially resolved.…”

Section: Introductionmentioning

confidence: 99%

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Exergy as Criteria for Efficient Energy Systems—A Spatially Resolved Comparison of the Current Exergy Consumption, the Current Useful Exergy Demand and Renewable Exergy Potential

Sejkora

Kühberger

Radner³

et al. 2020

Energies

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The energy transition from fossil-based energy sources to renewable energy sources of an industrialized country is a big challenge and needs major systemic changes to the energy supply. Such changes require a holistic view of the energy system, which includes both renewable potentials and consumption. Thereby exergy, which describes the quality of energy, must also be considered. In this work, the determination and analysis of such a holistic view of a country are presented, using Austria as an example. The methodology enables the calculation of the spatially resolved current exergy consumption, the spatially resolved current useful exergy demand and the spatially resolved technical potential of renewable energy sources (RES). Top-down and bottom-up approaches are combined in order to increase accuracy. We found that, currently, Austria cannot self-supply with exergy using only RES. Therefore, Austria should increase the efficiency of its energy system, since the overall exergy efficiency is only at 34%. The spatially resolved analysis shows that in Austria the exergy potential of RES is rather evenly distributed. In contrast, the exergy consumption is concentrated in urban and industrial areas. Therefore, the future energy infrastructure must compensate for these spatial discrepancies.

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“…A similarly low total exergy efficiency of 21% can be found in Gutschi et al [3]. This study dealt with exergy flows in Austria in 1956 and 2005.…”

supporting

confidence: 63%

Section: Biomassmentioning

confidence: 99%

Section: Biomassmentioning

confidence: 99%

Section: Biomassmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Exergy as Criteria for Efficient Energy Systems—A Spatially Resolved Comparison of the Current Exergy Consumption, the Current Useful Exergy Demand and Renewable Exergy Potential

Sejkora

Kühberger

Radner³

et al. 2020

Energies

View full text Add to dashboard Cite

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ATLANTIS – Simulationsmodell der europäischen Elektrizitätswirtschaft bis 2030

Gutschi

Bachhiesl

Huber

et al. 2009

Elektrotech. Inftech.

Self Cite

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Am Institut f€ u ur Elektrizit€ a atswirtschaft und Energieinnovation der TU Graz wurde unter eigenfinanziertem Einsatz von bisher 30 Personenjahren das Simulationsmodell ATLANTIS entwickelt. In diesem frei parametrierbaren Modell werden die komplexen Zusammenh€ a ange der Realwirtschaft (z. B. Netze und Kraftwerke) und der Nominalwirtschaft (z. B. stremb€ e ersen, Unternehmensbilanzen und Gewinn-und Verlustrechnungen) der europ€ a aischen Elektrizit€ a atswirtschaft abgebildet. Damit erm€ o oglicht ATLANTIS die Erstellung realit€ a atsnaher Entwicklungsszenarien bis 2030. Im folgenden Beitrag werden der Aufbau von ATLANTIS dargestellt und die Funktionsweise anhand einer konkreten Simulation f€ u ur die Elektrizit€ a atswirtschaft in S€ u ud-Ost-Europa sowie f€ u ur ein konkretes Unternehmen demonstriert.Schlü sselwö rter: EU-Elektrizit€ a atswirtschaft; Marktorganisationen; Verbundnetz; Unternehmensmodelle; erneuerbare Energien; CO 2 -Emissionen; S€ u ud-Ost-Europa ATLANTIS -simulation model of the European electricitiy economy until 2030.At the Institute of Electricity Economics and Energy Innovation of TU Graz the self-financed simulation model ATLANTIS has been built with an input of 30 person-years. This free adaptable model includes the nominal economical (e.g. grids and power stations) as well as the real economical (e.g. power exchanges, balance sheets of companies and income and loss statements) of the European electricity economy and allows the calculation of realistic development scenarios until 2030. The following paper shows the structure of ATLANTIS and demonstrates the functionality by means of a simulation of the South-Eastern-European electricity economy as well as by means of a concrete company. EinleitungViele verschiedene politische, € o okonomische und technische Rahmenbedingungen beeinflussen die Entscheidungsfindung in der heutigen Elektrizit€ a atswirtschaft. In Folge des Strukturbruchs durch die Liberalisierung des europ€ a aischen Elektrizit€ a atsmarktes und der fortw€ a ahrenden Weiterentwicklung dieses Binnenmarktes k€ o onnen neue Fragestellungen nicht mehr mit der Erfahrung und den Erkenntnissen der ,,alten'' Elektrizit€ a atswirtschaft beantwortet werden.Dies war die Motivation f€ u ur die Entwicklung eines Simulationsmodells der europ€ a aischen Elektrizit€ a atswirtschaft, welches in dieser Arbeit vorgestellt wird. Das Simulationsmodell ATLANTIS wird seit nunmehr sieben Jahren am Institut f€ u ur Elektrizit€ a atswirtschaft und Energieinnovation an der Technischen Universit€ a at Graz entwickelt. Bislang flossen mehr als 40 Diplomarbeiten und insgesamt f€ u unf Dissertationen in das Modell ein, und es wurden bereits € u uber 30 eigen-finanzierte Personenjahre an Forschung und Entwicklung investiert. Aktuell arbeiten vier wissenschaftliche Universit€ a atsassistenten und vier Projektmitarbeiter im Rahmen einer Habilitation, dreier Dissertationen und elf Diplomarbeiten am Modell.Die im interdisziplin€ a aren Ansatz von ATLANTIS integrierten Fachdisziplinen umfassen vor allem Elektr...

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The socio-economic impact of renewable electricity generation with prosumer activity

Kettner

Kratena²,

Sommer

2022

Elektrotech. Inftech.

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In order to meet the targets of the Paris Agreement, a rapid and far-reaching phase-out of fossil fuels is required. Against this background, Austria aims to cover 100% of its electricity generation from renewable energy sources by 2030. To meet this target in a standard scenario of final electricity demand, renewable electricity generation needs to be expanded by 27 TWh compared to 2019 (11 TWh PV, 10 TWh wind power, 5 TWh hydropower, and 1 TWh biomass). With respect to the ambitious expansion target for PV, the contribution of households, i.e., prosumers, will be of crucial importance.Depending on their background (most notably, type of building, income), the ability of different household groups to participate in the electricity market as prosumers—and hence, the possible distributive impacts of the electricity transformation—will vary substantially. Prosumers reduce the consumption of electricity from the grid and can thereby realize cost savings, increasing their consumption opportunities for other (non-energy) goods.This paper investigates the economic and distributive impact of increasing household PV electricity generation in Austria until 2030. For this purpose, the household module of the macroeconomic model DYNK is expanded, differentiating the degree to which households engage in “prosumer” activities. A set of PV support policy scenarios is then defined to simulate the increase in the number of prosumers as well as the distributive impacts on the different household types and the macroeconomic impacts with the expanded model. The simulation results show a small but positive effect of increased investment in residential photovoltaic systems on the GDP. With respect to the distributive effects, the design of the support scheme is essential. Targeting support for low-income households also has positive impacts on GDP growth.

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ATLANTIS – Simulationsmodell der europäischen Elektrizitätswirtschaft bis 2030

Cited by 5 publications

References 2 publications

Exergy as Criteria for Efficient Energy Systems—A Spatially Resolved Comparison of the Current Exergy Consumption, the Current Useful Exergy Demand and Renewable Exergy Potential

Exergy as Criteria for Efficient Energy Systems—A Spatially Resolved Comparison of the Current Exergy Consumption, the Current Useful Exergy Demand and Renewable Exergy Potential

ATLANTIS – Simulationsmodell der europäischen Elektrizitätswirtschaft bis 2030

The socio-economic impact of renewable electricity generation with prosumer activity

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