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.

Cette thèse traite un problème inverse en astronomie. L’objectif est de reconstruire un objet 2D+λ, ayant une distribution spatiale et spectrale, à partir d’un ensemble de données multispectrales de basse résolution fournies par l’imageur MIRI (Mid-InfraRed Instrument), qui est à bord du prochain télescope spatial James Webb Space Telescope (JWST). Les données multispectrales observées souffrent d’un flou spatial qui dépend de la longueur d’onde. Cet effet est dû à la convolution par la réponse optique (PSF). De plus, les données multi-spectrales souffrent également d’une sévère dégradation spectrale en raison du filtrage spectral et de l’intégration par le détecteur sur de larges bandes. La reconstruction de l’objet original est un problème mal posé en raison du manque important d’informations spectrales dans l’ensemble de données multispectrales. La difficulté se pose alors dans le choix d’une représentation de l’objet permettant la reconstruction de l’information spectrale. Un modèle classique utilisé jusqu’à présent considère une PSF invariante spectralement par bande, ce qui néglige la variation spectrale de la PSF. Cependant, ce modèle simpliste convient que dans le cas d’instrument à une bande spectrale très étroite, ce qui n’est pas le cas pour l’imageur de MIRI. Notre approche consiste à développer une méthode pour l’inversion qui se résume en quatre étapes : (1) concevoir un modèle de l’instrument reproduisant les données multispectrales observées, (2) proposer un modèle adapté pour représenter l’objet à reconstruire, (3) exploiter conjointement l’ensemble des données multispectrales, et enfin (4) développer une méthode de reconstruction basée sur la régularisation en introduisant des priori à la solution. Les résultats de reconstruction d’objets spatio-spectral à partir de neuf images multispectrales simulées de l’imageur de MIRI montrent une augmentation significative des résolutions spatiale et spectrale de l’objet par rapport à des méthodes conventionnelles. L’objet reconstruit montre l’effet de débruitage et de déconvolution des données multispectrales. Nous avons obtenu une erreur relative n’excédant pas 5% à 30 dB et un temps d’exécution de 1 seconde pour l’algorithme de norm-l₂ et 20 secondes avec 50 itérations pour l’algorithme norm-l₂/l₁. C’est 10 fois plus rapide que la solution itérative calculée par l’algorithme de gradient conjugué. / This thesis deals with an inverse problem in astronomy. The objective is to reconstruct a spatio-spectral object, having spatial and spectral distributions, from a set of low-resolution multispectral data taken by the imager MIRI (Mid-InfraRed Instrument), which is on board the next space telescope James Webb Space Telescope (JWST). The observed multispectral data suffers from a spatial blur that varies according to the wavelength due to the spatial convolution with a shift-variant optical response (PSF). In addition the multispectral data also suffers from severe spectral degradations because of the spectral filtering and the integration by the detector over broad bands. The reconstruction of the original object is an ill-posed problem because of the severe lack of spectral information in the multispectral dataset. The difficulty then arises in choosing a representation of the object that allows the reconstruction of this spectral information. A common model used so far considers a spectral shift-invariant PSF per band, which neglects the spectral variation of the PSF. This simplistic model is only suitable for instruments with a narrow spectral band, which is not the case for the imager of MIRI. Our approach consists of developing an inverse problem framework that is summarized in four steps: (1) designing an instrument model that reproduces the observed multispectral data, (2) proposing an adapted model to represent the sought object, (3) exploiting all multispectral dataset jointly, and finally (4) developing a reconstruction method based on regularization methods by enforcing prior information to the solution. The overall reconstruction results obtained on simulated data of the JWST/MIRI imager show a significant increase of spatial and spectral resolutions of the reconstructed object compared to conventional methods. The reconstructed object shows a clear denoising and deconvolution of the multispectral data. We obtained a relative error below 5% at 30 dB, and an execution time of 1 second for the l₂-norm algorithm and 20 seconds (with 50 iterations) for the l₂/l₁-norm algorithm. This is 10 times faster than the iterative solution computed by conjugate gradients.

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

Indiana University-Purdue University Indianapolis (IUPUI) / This thesis proposes an artificial neural network (NN) model to predict fuel consumption in heavy vehicles. The model uses predictors derived from vehicle speed, mass, and road grade. These variables are readily available from telematics devices that are becoming an integral part of connected vehicles. The model predictors are aggregated over a fixed distance traveled (i.e., window) instead of fixed time interval. It was found that 1km windows is most appropriate for the vocations studied in this thesis. Two vocations were studied, refuse and delivery trucks. The proposed NN model was compared to two traditional models. The first is a parametric model similar to one found in the literature. The second is a linear regression model that uses the same features developed for the NN model. The confidence level of the models using these three methods were calculated in order to evaluate the models variances. It was found that the NN models produce lower point-wise error. However, the stability of the models are not as high as regression models. In order to improve the variance of the NN models, an ensemble based on the average of 5-fold models was created. Finally, the confidence level of each model is analyzed in order to understand how much error is expected from each model. The mean training error was used to correct the ensemble predictions for five K-Fold models. The ensemble K-fold model predictions are more reliable than the single NN and has lower confidence interval than both the parametric and regression models.

Over the last few decades, the complexity and variety of automation systems have increased dramatically. Commissioning has grown more and more critical for the entire industry. Conventional commissioning is time-consuming and expensive. It's always been a challenge in manufacturing to put new designs into production or implement new technologies, control codes, or tactics. In Virtual Commissioning (VC), control programs of the physical system's Digital Twin (DT) can be validated in Software-in-the-Loop (SIL) before the actual commissioning. The emergence of new VC tools and methods has become a tremendous advantage, bringing the values of shorter duration, flexibility, and lower risks to the commissioning process. In this thesis, advanced process control was developed using the software Matlab and Simulink in conjunction with the engineering tools S7-PLCSIM Advanced and STEP 7 TIA Portal to conduct VC. A VC approach with four key steps is taken to evaluate the possibility of validating advanced process control. The steps are modeling DT of a rolling mill, model-based control design, simulation model development in Simulink, communication between the simulation model and the PLC program using S-7 TIA Portal, and PLCSIM Advanced. Also, a simulated Human-Machine Interface was designed to operate and visualize the process. VC of the rolling mill process was verified and validated by Model-in-the-Loop (MIL) and SIL simulation. The simulation gives satisfactory results as both MIL and SIL show identical outputs of the process.

The need for ancillary services is on the rise due to the increasing share of weather-dependent power sources in the electric power system. This master thesis focuses on the Swedish FCR-D Up market. It is a national balancing market for transmission system operator’s procurement of the ancillary service called FCR-D Up, that is the up-regulating frequency containment reserve in case of system disturbances. The FCR-D Up market is undergoing significant changes to adapt to the changing electric power system, which may affect the current market dominance of hydropower suppliers due to the emergence of new suppliers and regulatory changes by the Swedish transmission system operator. This master thesis establishes a conceptual qualitative market development system model for price formation on the FCR-D Up market. The research question addressed is: "What FCR-D Up market developments and regulatory market changes on the supply and demand side respectively are expected in Sweden in the upcoming years, 2024-2026, and how will they affect the market prices?" The research was based on the theoretical concepts of system modeling and price formation, using Soft Systems Methodology. Data was collected from various sources and analysed using CATWOE analysis, Casual Loop Diagram, as well as supply and demand curve model theory. It was concluded that price-influencing market development and regulatory changes are focused on the supply side of the market. These include the market entry of new suppliers, transition to marginal pricing, new technical requirements for market participation and increasing value stacking opportunities for FCR-D Up suppliers on Nord Pool’s electricity markets and the other balancing markets. / Behovet av stödtjänster ökar på grund av den ökande andelen väderberoende kraftkällor i elkraftsystemet. Denna masteruppsats fokuserar på den svenska FCR-D Upp-marknaden. Det är en nationell balansmarknad för transmissionsnätsoperatörens upphandling av den stödtjänst som kallas FCR-D Upp, som är den uppreglerande frekvenskontrollreserven vid störningar i systemet. FCR-D Uppmarknaden genomgår betydande förändringar för att anpassas till det föränderliga elkraftsystemet, vilket kan påverka den nuvarande marknadsdominansen av vattenkraftsleverantörer på grund av tillkomst av nya leverantörer och regulativa marknadsförändringar av transmissionsnätsoperatören. Denna masteruppsats etablerar en konceptuell kvalitativ systemmodell för marknadsutveckling avseende prisbildning på FCR-D Upp-marknaden. Forskningsfrågan är: "Vilken utveckling av FCR-D Upp-marknaden och vilka regulatoriska marknadsförändringar på utbuds- respektive efterfrågesidan förväntas i Sverige under de kommande åren, 2024-2026, och hur kommer de att påverka marknadspriset?". Arbetet baserades på teoretiska koncept kring systemmodellering och prisbildning, med fokus på Soft Systems Methodology. Data samlades in från olika källor och analyserades med hjälp av CATWOE-analys, Casual Loop Diagram samt modellteori för utbuds- och efterfrågekurvor. Slutsatsen var att prisinfluerande marknadsutvecklingar och regulatoriska marknadsförändringar är inriktade på marknadens utbudssida. Det handlar bland annat om nya leverantörers inträde på marknaden, övergången till marginalprissättning, nya tekniska krav för marknadsdeltagande och ökande möjligheter till värdestapling för FCR-D Upp leverantörerpå Nord Pools elmarknader och de andra balansmarknaderna.

Indiana University-Purdue University Indianapolis (IUPUI) / The harvested energy of wind can be transferred to the generators either through a gearbox or through an intermediate medium such as hydraulic fluids. In this method, high-pressure hydraulic fluids are utilized to collect the energy of single or multiple wind turbines and transfer it to a central generation unit. In this unit, the mechanical energy of the hydraulic fluid is transformed into electric energy. The prime mover of hydraulic energy transfer unit, the wind turbine, experiences the intermittent characteristics of wind. This energy variation imposes fluctuations on generator outputs and drifts their angular velocity from desired frequencies. Nonlinearities exist in hydraulic wind power transfer and are originated from discrete elements such as check valves, proportional and directional valves, and leakage factors of hydraulic pumps and motors. A thorough understanding of hydraulic wind energy transfer system requires mathematical expression of the system. This can also be used to analyze, design, and predict the behavior of large-scale hydraulic-interconnected wind power plants. This thesis introduces the mathematical modeling and controls of the hydraulic wind energy transfer system. The obtained models of hydraulic energy transfer system are experimentally validated with the results from a prototype. This research is classified into three categories. 1) A complete mathematical model of the hydraulic energy transfer system is illustrated in both ordinary differential equations and state-space representation. 2) An experimental prototype of the energy transfer system is built and used to study the behavior of the system in different operating configurations, and 3) Controllers are designed to address the problems associated with the wind speed fluctuation and reference angular velocity tracking. The mathematical models of hydraulic energy transfer system are also validated with the simulation results from a SimHydraulics Toolbox of MATLAB/Simulink®. The models are also compared with the experimental data from the system prototype. The models provided in this thesis do consider the improved assessment of the hydraulic system operation and efficiency analysis for industrial level wind power application.

No description available.

<p dir="ltr">Distributed energy resources (DERs), such as rooftop solar generation and energy storage systems, are becoming more prevalent in distribution systems. DERs are connected to the distribution system via power electronic converters, introducing faster dynamics in the system. Understanding the system dynamics under a high penetration of inverter-based DERs is critical for power system researchers and practitioners, driving the development of modeling techniques and simulation software. Aiming to reduce computational complexity, existing tools and techniques often employ various approximations. Meanwhile, modern advancements in computational hardware capabilities provide opportunities to include the faster time-scale dynamics. To address this, the primary objective of this thesis is to develop an open-source Python simulation package, Dynamic Simulation using Sparse Tableau Approach in Python, DynaSTPy (pronounced “dynasty”), capable of capturing the dynamics of all components in a distribution feeder. The distribution feeder is modeled as a system of Differential-Algebraic Equations (DAEs). Further, each component in the feeder is modeled based on the Sparse Tableau Approach (STA), which involves the representation of component model equations using sparse matrices, facilitating a systematic procedure to model the components and construct the system DAEs. In sinusoidal steady state, the DAEs can be represented in phasor form, extending the approach to perform power flow analysis of distribution feeders.</p>

Voltage instability is a major concern in operation of power systems and it is well known that voltage instability and collapse have led to blackout or abnormally low voltages in a significant part of the power system. Consequently, tracking the proximity of the power system to an insecure voltage condition has become an important element of any protection and control scheme. The expected time until instability is a critical aspect. There are a few energy management systems including voltage stability analysis function in the real-time environment of control centres, these are based on assumptions (such as off-line models of the system loads) that may lead the system to an insecure operation and/or poor utilization of the resources. Voltage instability is driven by the load dynamics, and investigations have shown that load restoration due to the on-load tap changer (OLTC) action is the main cause of the voltage instability. However, the aggregate loads seen from bulk power delivery transformers are still the most uncertain power system components, due to the uncertainty of the participation of individual loads and shortcomings of the present approaches in the load modeling. In order to develop and implement a true on-line voltage stability analysis method, the on-line accurate modeling of the higher voltage (supply system) and the lower voltage level (aggregate load) based on the local measurements is required. In this research, using the changes in the load bus measured voltage and current, novel methods are developed to estimate the supply system equivalent and to identify load parameters. Random changes in the load voltage and current are processed to estimate the supply system Thevenin impedance and the composite load components are identified in a peeling process using the load bus data changes during a large disturbance in the system. The results are then used to anticipate a possible long-term voltage instability caused by the on-load tap changer operation following the disturbance. Work on the standard test system is provided to validate the proposed methods. The findings in this research are expected to provide a better understanding of the load dynamics role in the voltage stability, and improve the reliability and economy of the system operation by making it possible to decrease uncertainty in security margins and determine accurately the transfer limits.