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Demand Side Management in Deutschland zur Systemintegration erneuerbarer EnergienLadwig, Theresa 10 July 2018 (has links) (PDF)
Durch den Ausbau an Wind- und PV-Anlagen in Deutschland wird der Flexibilitätsbedarf im Stromsystem steigen. Der Flexibilitätsbedarf kann zum einen durch verschiedene Technologien, z.B. Speicher oder Netze, und zum anderen durch die Stromnachfrage bereitgestellt werden. Eine gezielte Steuerung der Stromnachfrage wird als Demand Side Management (DSM) bezeichnet. Der zunehmend wetterabhängigen und fluktuierenden Stromerzeugung in Deutschland steht jedoch eine bis heute weitgehend unelastische Nachfrage gegenüber.
In der Literatur sind verschiedene Arbeiten zu finden, die das Potential zur Lastabschaltung und verschiebung in Deutschland untersuchen. Hierbei liegt der Fokus auf absoluten Werten. Saisonale oder tageszeitliche Unterschiede bleiben dabei häufig unberücksichtigt. Die vorliegende Dissertation greift an dieser Stelle an und untersucht das Potential ausgewählter DSM-Anwendungen in stündlicher Auflösung. Die Ergebnisse zeigen, dass das verfügbare Potential starken saisonalen und tageszeitlichen Schwankungen unterliegt. Dementsprechend wird das DSM-Potential überschätzt, wenn nur absolute Werte betrachtet werden. Darüber hinaus zeigt die Autorin, welche Entwicklungen in den nächsten Jahren hinsichtlich der Verfügbarkeit des DSM-Potentials zu erwarten sind.
Basierend auf der Potentialermittlung wird in der Dissertation die Rolle von DSM in einem EE-geprägten Stromsystem modellbasiert untersucht. Hierfür wird das lineare Optimierungsmodell ELTRAMOD, das den deutschen und europäischen Strommarkt abbildet, weiterentwickelt. Anhand verschiedener Szenarien wird zum einen der Beitrag von DSM zur Systemintegration von erneuerbaren Energien in Deutschland und zum anderen die Wechselwirkungen mit anderen Flexibilitätsoptionen (z.B. Speicher) untersucht. Die Ergebnisse zeigen, dass die DSM-Kategorien Lastabschaltung und verschiebung nur kurzzeitig auftretende Schwankungen der Einspeisung aus erneuerbaren Energien ausgleichen können. Zum Ausgleich großer Überschussmengen aus erneuerbaren Energien sind hingegen Power-to-X-Technologien, z.B. Power-to-Heat, besser geeignet.
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Flexibility Options in Energy Systems: The influence of Wind - PV ratios and sector coupling on optimal combinations of flexible technologies in a European electricity systemZöphel, Christoph 01 March 2022 (has links)
Within the present work, the main objective is to identify interactions between flexibility demand and flexibility supply. Therefore, three research fields regarding the future transformation of the European energy system are addressed. First, an expansion of intermittent renewable energy sources (iRES) is discussed taking the potentials of wind and PV technologies into account. The analysis is based on fundamental considerations of generation characteristics as well as available potentials across 17 countries in central-western Europe. To emphasis the differences in electricity generation between wind and PV, an iRES expansion model is developed coping for geographically highly resolved weather data as well as for limitations of iRES potentials due to land-use restrictions and for energy-policy constraints. Three scenarios with varying Wind-PV ratio in total iRES electricity generation are evaluated. Second, the options to provide flexibility to balance the flexibility demand are introduced and mathematically implemented in ELTRAMOD. Therefore, the model was adjusted to represent multiple flexible technologies for upward, downward and shifting flexibility provision to cover the residual load. In a system perspective and a greenfield approach, the linear electricity market model enables the analysis of cost-optimal combinations of flexibility options against the background of scenarios with different flexibility demands. In addition, the third research field addresses the emerging developments of sector coupling by including selected Power-to-X technologies. A second scenario dimension analyses the role of energy storages in the energy end-use sectors for a more flexible sector coupling. The results underline the importance of the Wind-PV ratios in electricity generation when assessing flexibility demand and flexibility supply in model-based energy system analysis. Due to the higher seasonality of PV, the residual load parameter indicate higher iRES integration challenges in terms of flexible capacity requirements. Particularly the provision of spatial and temporal balancing flexibility is significantly influenced by a higher wind or a higher PV share in the iRES mix. With sector coupling, the value of temporal shifting is increasing. Hourly storages are not only highly sensitive to the Wind-PV ratio, but in addition strongly impacted by sector coupling. In both dimensions, a higher PV share is increasing the value for short-term shifting. Furthermore, sector coupling increases the need for additional electricity generation. Thereby, for peak-load capacity provision gas-fuelled power plant are optimal in the present work increasing the total emissions especially with higher PV shares. The sensitivity analysis shows the value of additional iRES capacities as well as of storage cost reductions to further reduce emissions.
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Demand Side Management in Deutschland zur Systemintegration erneuerbarer EnergienLadwig, Theresa 10 July 2018 (has links)
Durch den Ausbau an Wind- und PV-Anlagen in Deutschland wird der Flexibilitätsbedarf im Stromsystem steigen. Der Flexibilitätsbedarf kann zum einen durch verschiedene Technologien, z.B. Speicher oder Netze, und zum anderen durch die Stromnachfrage bereitgestellt werden. Eine gezielte Steuerung der Stromnachfrage wird als Demand Side Management (DSM) bezeichnet. Der zunehmend wetterabhängigen und fluktuierenden Stromerzeugung in Deutschland steht jedoch eine bis heute weitgehend unelastische Nachfrage gegenüber.
In der Literatur sind verschiedene Arbeiten zu finden, die das Potential zur Lastabschaltung und verschiebung in Deutschland untersuchen. Hierbei liegt der Fokus auf absoluten Werten. Saisonale oder tageszeitliche Unterschiede bleiben dabei häufig unberücksichtigt. Die vorliegende Dissertation greift an dieser Stelle an und untersucht das Potential ausgewählter DSM-Anwendungen in stündlicher Auflösung. Die Ergebnisse zeigen, dass das verfügbare Potential starken saisonalen und tageszeitlichen Schwankungen unterliegt. Dementsprechend wird das DSM-Potential überschätzt, wenn nur absolute Werte betrachtet werden. Darüber hinaus zeigt die Autorin, welche Entwicklungen in den nächsten Jahren hinsichtlich der Verfügbarkeit des DSM-Potentials zu erwarten sind.
Basierend auf der Potentialermittlung wird in der Dissertation die Rolle von DSM in einem EE-geprägten Stromsystem modellbasiert untersucht. Hierfür wird das lineare Optimierungsmodell ELTRAMOD, das den deutschen und europäischen Strommarkt abbildet, weiterentwickelt. Anhand verschiedener Szenarien wird zum einen der Beitrag von DSM zur Systemintegration von erneuerbaren Energien in Deutschland und zum anderen die Wechselwirkungen mit anderen Flexibilitätsoptionen (z.B. Speicher) untersucht. Die Ergebnisse zeigen, dass die DSM-Kategorien Lastabschaltung und verschiebung nur kurzzeitig auftretende Schwankungen der Einspeisung aus erneuerbaren Energien ausgleichen können. Zum Ausgleich großer Überschussmengen aus erneuerbaren Energien sind hingegen Power-to-X-Technologien, z.B. Power-to-Heat, besser geeignet.
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Renewable energy in North AfricaKost, Christoph Philipp 26 August 2015 (has links) (PDF)
The transition of the North African electricity system towards renewable energy technologies is analyzed in this thesis. Large potentials of photovoltaics (PV), concentrating solar power (CSP) and onshore wind power provide the opportunity to achieve a long-term shift from conventional power sources to a highly interconnected and sustainable electricity system based on renewable energy sources (RES). A multi-dimensional analysis evaluates the economic and technical effects on the electricity market as well as the socio-economic impact on manufacturing and employment caused by the large deployment of renewable energy technologies.
The integration of renewable energy (RE) into the electricity system is modeled in a linear optimization model RESlion which minimizes total system costs of the long-term expansion planning and the hourly generation dispatch problem. With this model, the long-term portfolio mix of technologies, their site selection, required transmission capacities and the hourly operation are analyzed. The focus is set on the integration of renewable energy in the electricity systems of Morocco, Algeria, Tunisia, Libya and Egypt with the option to export electricity to Southern European countries. The model results of RESlion show that a very equal portfolio mix consisting of PV, CSP and onshore wind power is optimal in long-term scenarios for the electricity system. Until the year 2050, renewable energy sources dominate with over 70% the electricity generation due to their cost competiveness to conventional power sources. In the case of flexible and dispatchable electricity exports to Europe, all three RE technologies are used by the model at a medium cost perspective.
The socio-economic impact of the scenarios is evaluated by a decision model (RETMD) for local manufacturing and job creation in the renewable energy sector which is developed by incorporating findings from expert interviews in the RE industry sector. The electricity scenarios are assessed regarding their potential to create local economic impact and local jobs in manufacturing RE components and constructing RE power plants. With 40,000 to 100,000 new jobs in the RE sector of North African countries, scenarios with substantial RE deployment can provide enormous benefits to the labor market and lead to additional economic growth.
The deployment of renewable energy sources in North Africa is consequently accelerated and facilitated by finding a trade-off between an optimal technology portfolio from an electricity system perspective and the opportunities through local manufacturing. By developing two model approaches for evaluating the effects of renewable energy technologies in the electricity system and in the industrial sector, this thesis contributes to the literature on energy economics and energy policy for the large-scale integration of renewable energy in North Africa.
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Renewable energy in North Africa: Modeling of future electricity scenarios and the impact on manufacturing and employmentKost, Christoph Philipp 04 June 2015 (has links)
The transition of the North African electricity system towards renewable energy technologies is analyzed in this thesis. Large potentials of photovoltaics (PV), concentrating solar power (CSP) and onshore wind power provide the opportunity to achieve a long-term shift from conventional power sources to a highly interconnected and sustainable electricity system based on renewable energy sources (RES). A multi-dimensional analysis evaluates the economic and technical effects on the electricity market as well as the socio-economic impact on manufacturing and employment caused by the large deployment of renewable energy technologies.
The integration of renewable energy (RE) into the electricity system is modeled in a linear optimization model RESlion which minimizes total system costs of the long-term expansion planning and the hourly generation dispatch problem. With this model, the long-term portfolio mix of technologies, their site selection, required transmission capacities and the hourly operation are analyzed. The focus is set on the integration of renewable energy in the electricity systems of Morocco, Algeria, Tunisia, Libya and Egypt with the option to export electricity to Southern European countries. The model results of RESlion show that a very equal portfolio mix consisting of PV, CSP and onshore wind power is optimal in long-term scenarios for the electricity system. Until the year 2050, renewable energy sources dominate with over 70% the electricity generation due to their cost competiveness to conventional power sources. In the case of flexible and dispatchable electricity exports to Europe, all three RE technologies are used by the model at a medium cost perspective.
The socio-economic impact of the scenarios is evaluated by a decision model (RETMD) for local manufacturing and job creation in the renewable energy sector which is developed by incorporating findings from expert interviews in the RE industry sector. The electricity scenarios are assessed regarding their potential to create local economic impact and local jobs in manufacturing RE components and constructing RE power plants. With 40,000 to 100,000 new jobs in the RE sector of North African countries, scenarios with substantial RE deployment can provide enormous benefits to the labor market and lead to additional economic growth.
The deployment of renewable energy sources in North Africa is consequently accelerated and facilitated by finding a trade-off between an optimal technology portfolio from an electricity system perspective and the opportunities through local manufacturing. By developing two model approaches for evaluating the effects of renewable energy technologies in the electricity system and in the industrial sector, this thesis contributes to the literature on energy economics and energy policy for the large-scale integration of renewable energy in North Africa.:Abstract iii
Acknowledgement iv
Table of contents v
List of tables ix
List of figures xii
List of abbreviations xvi
1 Introduction 1
1.1 Renewable energy in North Africa 2
1.2 Research questions and aim of this thesis 3
1.2.1 Modeling of electricity systems 4
1.2.2 Modeling of manufacturing and employment impact 6
1.2.3 Optimal renewable energy scenarios 6
1.3 Related research 7
1.4 Structure of thesis 7
2 Modeling fundamentals for electricity systems with renewable energy sources 9
2.1 Energy system modeling 9
2.2 Electricity models 16
2.2.1 Classifications and taxonomy 17
2.2.2 Differences between operation models and planning models 20
2.2.3 Typical modeling approaches 21
2.3 Optimization models 23
2.3.1 Basic model structure 23
2.3.2 Objective functions of electricity models 24
2.3.3 Technical aspects of electricity systems as models constraints 26
2.3.4 Combining different objectives in energy scenarios 27
2.4 Models for high shares of renewable energy 28
2.5 Models for North African electricity systems 31
2.6 Conclusions for model development 34
3 Electricity system of North Africa 36
3.1 Market structure 36
3.2 National targets for renewable energy 40
3.2.1 Morocco 40
3.2.2 Algeria 41
3.2.3 Tunisia 42
3.2.4 Libya 42
3.2.5 Egypt 43
3.3 Long-term development of electricity demand 44
3.4 Electricity exports to Europe 47
3.5 Geopolitical risks for the electricity system 51
4 Development of the electricity market model RESlion 53
4.1 Model requirements and modeling goals 53
4.2 Modeling of renewable energy technologies 56
4.2.1 Onshore wind power plants and wind resources 59
4.2.2 PV power plants and solar resources 61
4.2.3 CSP plants and solar resources 63
4.2.4 Hydro power plants and energy storage systems 65
4.3 General model approach of RESlion 65
4.4 Model description of RESlion 69
4.4.1 Introduction to the model structure 69
4.4.2 Temporal coverage 70
4.4.3 Objective function 72
4.4.4 Technology independent model constraints 74
4.4.5 Regional electricity exchange: Transmission lines 76
4.4.6 Renewable energy technologies 78
4.4.7 Hydro and storage power plants 80
4.4.8 Uncertainty of input parameters and assumptions 81
4.5 Modeling of expansion planning 83
4.6 Modeling of detailed hourly generation dispatch 83
4.7 Extension options to a Mixed Integer Linear Programming model 84
4.8 Solver selection and implementation environment 85
5 Model-based analysis of future electricity scenarios for North Africa 86
5.1 Scenario assumptions 86
5.2 Scenario definition 89
5.3 Technical and economic input data 94
5.4 Model adjustment 99
5.4.1 Electricity generation in reference year 2010 99
5.4.2 Testing of results with detailed hourly generation dispatch 100
5.5 Electricity scenarios for North Africa by 2050 102
5.5.1 Development of the generation system 102
5.5.2 System and generation costs 106
5.5.3 Site selection of RES generation capacities 108
5.5.4 Regional transmission lines 114
5.5.5 Energy storage systems 118
5.5.6 Technology specific generation 119
5.5.7 CO2 emissions 126
5.6 Sensitivity analyses 126
5.6.1 Adaption of market conditions: Split of electricity markets 127
5.6.2 Technology focus 127
5.6.3 Adaption of cost trends for fossil fuels, transmission lines and storage systems 129
5.7 Technology specific findings for CSP, PV and wind power 131
5.7.1 Typical sites and locations for electricity generation from RES 131
5.7.2 Influence of wind speeds and solar irradiation 131
5.7.3 Interactions with conventional power plants 132
5.8 Electricity scenarios with export to Europe 133
5.9 Discussion of RESlion model and its results 139
6 Model development for socio-economic impact analysis 142
6.1 The idea of combining a cost-optimized electricity system with a socio-economic analysis 142
6.2 Literature review and terminology 145
6.3 Data acquisition and further studies 148
6.4 Model description of RETMD 151
6.4.1 Model objectives 151
6.4.2 Model structure and decision modeling 152
6.4.3 Model limitations and uncertainties 156
6.5 Data input of RETMD 157
6.5.1 Construction of reference power plants 157
6.5.2 Operation of reference power plants 159
6.5.3 Status quo of local manufacturing in recent RE projects 160
6.6 Sensitivity of RETMD on market size and know-how 161
6.7 Discussion of model achievements 163
7 Manufacturing and employment impact of optimized electricity scenarios 165
7.1 Demand scenarios for the RE markets from 2012 to 2030 165
7.2 Economic impact and employment creation 166
7.3 Technology specific development of local manufacturing 168
7.4 Country specific development of local manufacturing 172
7.5 Potentials of local manufacturing in each scenarios 174
7.6 Local economic impact 176
7.7 Local employment impact 177
7.8 Evaluation of scenario results 181
7.9 Electricity system analysis and RE manufacturing: Results and discussion of the combined analysis 183
8 Conclusions and outlook 186
8.1 Conclusion on model developments 186
8.2 Conclusion on renewable energy in North Africa 187
8.3 Outlook and further research 189
9 Bibliography 191
10 Appendix 210
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