Using hourly data, we show that the convergence of German and French electricity spot prices depends on the employed generation mix structure, on the trade (export/import) capacity between the two countries, and on characteristics of neighbouring markets. Only when German and French electricity markets employ "similar" generation mixes price spreads vanish, and the likelihood for congestion of electricity flows is significantly reduced. This implies that, at least, a part of the convergence that was documented in recent literature is spurious, because it is not (only) driven by the forces of arbitrage, but by the similarity of the Generation structures. The direction of congestion matters in this regard. Furthermore, we document consistent evidence for the most important predictions of trade theory if markets are characterized by increasing marginal cost (i.e. supply) curves and limited cross-border capacities. (authors' abstract) / Series: Department of Economics Working Paper Series

When wind power and other intermittent renewable energy (IRE) sources begin to supply a significant part of the load, concerns are often raised about the inherent intermittency and unpredictability of these sources. In order to study the impact from higher IRE penetration levels on the power system, integration studies are regularly performed. The model package presented and evaluated in Papers I–IV provides a comprehensive methodology for simulating realistic time series of wind generation and forecasts for such studies. The most important conclusion from these papers is that models based on coarse meteorological datasets give very accurate results, especially in combination with statistical post-processing. Advantages with our approach include a physical coupling to the weather and wind farm characteristics, over 30 year long, 5-minute resolution time series, freely and globally available input data and computational times in the order of minutes. In this thesis, I make the argument that our approach is generally preferable to using purely statistical models or linear scaling of historical measurements. In the variability studies in Papers V–VII, several IRE sources were considered. An important conclusion is that these sources and the load have very different variability characteristics in different frequency bands. Depending on the magnitudes and correlations of these fluctuation, different time scales will become more or less challenging to balance. With a suitable mix of renewables, there will be little or no increase in the needs for balancing on the seasonal and diurnal timescales, even for a fully renewable Nordic power system. Fluctuations with periods between a few days and a few months are dominant for wind power and net load fluctuations of this type will increase strongly for high penetrations of IRE, no matter how the sources are combined. According to our studies, higher capacity factors, more offshore wind power and overproduction/curtailment would be beneficial for the power system.

Reliable electricity supply remains a major problem in rural India nowadays. Renewable off-grid solutions have been applied in the last decades to increase power supply reliability but often failed to be feasible due to their high energy costs compared to the national grid. Grid Integrated Mini-grids with Storage (GIMS) can provide reliable power supply at an affordable price by combining mini-grids and national grid facilities. However, research on the techno-economic feasibility of these systems in the country is very limited and unavailable in the public sphere. This research project analysed three different aspects of the GIMS feasibility. First, the feasibility of the use of hybrid wind and solar Photovoltaic (PV) systems in GIMS was analysed by comparing the Levelised Cost of Electricity (LCOE) and Net Present Cost (NPC) of solar PV and hybrid PV/Wind GIMS systems. Second, the potential savings GIMS can offer due to the possibility of selling power to the grid were quantified by comparing the LCOE and NPC of the system with and without grid export. Lastly, the cost of reliability of the power supply was represented by the influence of the allowed percentage of capacity shortage on the total cost of the system. The analysis was carried out by means of the software HOMER and was based on three case studies in India. The results of this analysis showed that the use of hybrid systems could generate savings of up to 17% of the LCOE of the GIMS system in comparison to solar mini-grids. Moreover, power sales to the grid enabled LCOE savings up to 35% with respect to mini-grid without power sell-back possibility. In addition, the LCOE could be reduced in between 28% and 40% in all cases by enabling up to a 5% of capacity shortage in the system. / En tillförlitlig elförsörjning är ett stort problem på landsbygden i Indien. Elnätslösningar baserade på förnybara energikällor har undersökts under de senaste decennierna för att öka tillförlitligheten men har ofta misslyckats i genomförandefasen på grund av höga energikostnader jämfört med i det nationella nätet. Nätintegrerade mini-grids med energilagring (GIMS) kan ge tillförlitlig strömförsörjning till ett överkomligt pris genom att kombinera mini-grids och nationella elnätsanläggningar. Forskningen om den tekniskekonomiska genomförbarheten av dessa system i landet är emellertid mycket begränsad och otillgänglig inom den offentliga sfären. I den här studien analyseras tre olika aspekter av GIMS-genomförbarheten. För det första analyserades genomförbarheten av att använda hybrida vind- och solcellssystem i GIMS genom att jämföra ”Levelised Cost of Electricity” (LCOE) nivån och nuvärdeskostnaden (NPC) för solcellssystem (PV) och hybrid PV/Vind GIMS-system. För det andra kan de potentiella besparingar GIMS erbjuder, genom möjligheten att sälja elenergi till nätet, kvantifieras genom att jämföra LCOE och NPC i systemet med och utan ”nätexport”. Slutligen studeras kostnaden för tillförlitligheten hos strömförsörjningen i förhållande till accepterad kapacitetsbrist med avseende på systemets totala kostnad. Analysen har utförts med hjälp av mjukvaran HOMER och grundas på tre fallstudier i Indien. Resultaten av denna analys visar att användningen av hybridsystem skulle kunna generera besparingar på upp till 17% av LCOE i GIMS-systemet i jämförelse med enbart PV-baserade mini-grids. Försäljning av elenergi till nätet möjliggör LCOE-besparingar på upp till 35% med i förhållande till mini-grids utan möjlighet till export. Slutligen: LCOE kunde reduceras mellan 28% och 40% i samtliga fall genom att tillåta upp till 5% kapacitetsbrist i systemet.

Les réseaux électriques subissent deux changements majeurs : le taux croissant de générateurs d’énergie distribuée (GED) intermittents et la dérégulation du système électrique. Les réseaux de distribution et leurs gestionnaires (GRD) sont plus particulièrement touchés. La planification, construction et exploitation des réseaux de la plupart des GRD doivent évoluer face à ces change- ments. Les réseaux actifs de distribution et la gestion intelligente de associée est une solution potentielle. Les GRD pourront ainsi adopter de nouveaux rôles, interagir avec de nouveaux acteurs et proposer de nouveaux services. Ils pourront aussi utiliser la flexibilité de manière optimale au travers, entre autres, d’outils intelligents pour la gestion prévisionnelle de leurs réseaux de moyenne tension (HTA). Développer ces outils est un défi, car les réseaux de distribution ont des spécificités techniques. Ces spécificités sont la présence d’éléments discrets comme les régleurs en charge et la reconfiguration, les flexibilités exogènes, la non-linéarité des calculs de répartition de charge, et l’incertitude liée aux prévisions des GED intermittents. Dans cette thèse, une analyse économique des flexibilités permet d’établir une référence commune pour une utilisation rentable et sans biais dans la gestion prévisionnelle. Des modèles linéaires des flexibilités sont développés en utilisant des reformulations mathématiques exactes. Le calcul de répartition de charge est “convexifié” à travers des reformulations. L’optimalité globale des solutions obtenues, avec ce modèle d’optimisation exact et convexe de gestion prévisionnelle, sont ainsi garanties. Les tests sur deux réseaux permettent d’en valider la performance. L’incertitude des prévisions de GED peut pourtant remettre en cause les solutions obtenues. Afin de résoudre ce problème, trois formulations différentes pour traiter cette incertitude sont développées. Leurs performances sont testées et comparées à travers des simulations. Une analyse permet d’identifier les formulations les plus adaptées pour la gestion prévisionnelle sous incertitude. / Power systems are faced by the rising shares of distributed renewable energy sources (DRES) and the deregulation of the electricity system. Distribution networks and their operators (DSO) are particularly at the front-line. The passive operational practives of many DSOs today have to evolve to overcome these challenges. Active Distribution Networks (ADN), and Active Network Management (ANM) have been touted as a potential solution. In this context, DSOs will streamline investment and operational decisions, creating a cost-effective framework of operations. They will evolve and take up new roles and optimally use flexibility to perform, for example, short-term op- erational planning of their networks. However, the development of such methods poses particular challenges. They are related to the presence of discrete elements (OLTCs and reconfiguration), the use of exogenous (external) flexibilities in these networks, the non-linear nature of optimal power flow (OPF) calculations, and uncertainties present in forecasts. The work leading to this thesis deals with and overcomes these challenges. First, a short-term economic analysis is done to ascertain the utilisation costs of flexibilities. This provides a common reference for different flexibilities. Then, exact linear flexibility models are developed using mathematical reformulation techniques. The OPF equations in operational planning are then convexified using reformulation techniques as well. The mixed-integer convex optimisation model thus developed, called the novel OP formulation, is exact and can guarantee globally optimal solutions. Simulations on two test networks allow us to evaluate the performance of this formulation. The uncertainty in DRES forecasts is then handled via three different formulations developed in this thesis. The best performing formulations under uncertainty are determined via comparison framework developed to test their performance.