Rozprawy doktorskie na temat „Smart charging system”

<p> This research presents cyber-physical systems (CPS) modeling of the smart charging process to both identify and analyze potential vulnerabilities that may exist during the interaction and integration between an Electric Vehicle (EV) and the Electric Vehicle Service Equipment (EVSE). As EVSEs are increasingly being integrated into building energy management systems and interfaced with electric vehicles, safe and secure integration of these systems is of paramount importance for the safety and security of the nation's critical infrastructure and people. Both the charging station and electric vehicles have electro-mechanical components built from 3rd party providers, and there is no mechanism to check for safe and secure integration of EVs and EVSEs. The overall goal of the proposed research is to apply formal methods to verify and validate the cyber-physical interactions between the EV and EVSE to gain insight into vulnerable system states and their impacts. To that end, each component (EV and EVSE) was considered its own cyber-physical system and then separately broken down into individual states of operation. The states of each system were compared to determine how the EV and EVSE interacted on a fundamental level, with one system's state becoming the catalyst for change within the other system. These individual models were completed and subsequently integrated using the open-source software Ptolemy II. Upon successfully completing the interactions, the model was scrutinized using linear temporal logic (LTL) operators to test its veracity and projectability. The initial EV/EVSE model was then altered to emphasize previously determined vulnerabilities within the integrated system in order to verify their existence and potential for harming the system. Two such vulnerabilities were demonstrated in this research to confirm integrity of the model, which will be a valuable asset going forward to ensure the future safety of both operators and consumers regarding EV and EVSE interaction.</p><p>

Controlling the balance of production and consumption of electricity will become increasingly challenging as the transport sector gradually converts to electric vehicles along with a growing share of wind power in the Swedish electric power system. This puts greater demand on resources that maintain the balance to ensure stable grid operation. The balancing act is called frequency regulation which historically has been performed almost entirely by hydropower. As the power production becomes more intermittent with renewable energy sources, frequency regulation will need to be performed in higher volumes on the demand side by having a more flexible consumption. In this report, the electrification of 17 buses Svealandstrafiken bus depot in Västerås has been studied. The aim has been to assess different charging strategies to efficiently utilize the available time and power but also to investigate if Svealandstrafiken can participate in frequency regulation. A smart charging model was created that demonstrated how smart charging can be implemented to optimize the charging in four different cases. The simulated cases were: charging with load balancing, reduced charging power, frequency regulation, and electrifying more buses. The results show that the power capacity limit will be exceeded if the buses are being charged directly as they arrive at the depot and without scheduling the charging session. By implementing smart charging, Svealandstrafiken can fully charge the 17 buses within the power capacity limit of the depot with 82 minutes to spare. By utilizing this 82-minute margin in the four different charging strategies, it was found that Svealandstrafiken can save 88 200SEK per year by load balancing, save 30 000 SEK per year by reducing the charging power by 10 %, earn 111 900 SEK per year by frequency regulation or electrify five more buses. Reducing the charging power may also increase the lifetime of the batteries but quantifying this needs further studies. Conclusively, there is economic potential for Svealandstrafiken for implementing smart charging.

Véhicules électriques (EV) présente les avantages de zéro émission directe et d'un rendement élevé de conversion de l'énergie électrique. Toutefois, les installations de charge des véhicules électriques restent largement rares en raison des coûts d'investissement et d’exploitation élevés. Dans le but d’améliorer le taux de pénétration des installations de charge de véhicules électriques, cette thèse étudie le contrôle du système et l’optimisation de l’activité économique des stations de charge de véhicules électriques (EVCS).Premièrement, en tant que principes de contrôle du système de gestion de l’énergie de niveau supérieur, les techniques de contrôle principales sont étudiées pour le fonctionnement en temps réel d’un système EVCS. Afin de garantir la stabilité et la capacité dynamique du système de micro-réseau de chargement de véhicules électriques, ce travail a porté sur les techniques de contrôle coordonnées d'un système EVCS avec un système photovoltaïque local et un système de stockage.Deuxièmement, afin de réduire les coûts de fonctionnement de l’EVCS, un EMS basé sur la programmation dynamique approximative (ADP) est proposé pour l’EVCS équipé de plusieurs types de chargeurs (EVCS-MTC). Plusieurs véhicules électriques peuvent acquérir le service de charge via un chargeur commun dans l’EVCS-MTC. Dans l'EMS proposé, l'ADP et l'algorithme d'évolution (EA) sont combinés pour déterminer le temps de début de charge optimal pour chaque EV.Enfin, afin d'intégrer les énergies renouvelables dans l'EVCS, une formulation de processus de décision de Markov (MDP) à horizon fini est proposée pour le fonctionnement optimal d'un EVCS assisté par PV sur un campus universitaire, utilisant la technologie de véhicule à réseau (V2G). fournir des services auxiliaires et prendre en compte le prix dynamique de l'électricité et les comportements incertains des propriétaires de EV<br>Electric vehicles (EV) have the advantages of zero direct emissions and high electrical energy conversion efficiency. However, EV charging facilities remain largely scarce due to the high investment and operation costs. In order to improve the penetration rate of EV charging facilities, the system control and economic operation optimization of EV charging stations (EVCS) are studied in this thesis.Firstly, as the control fundamentals of upper-level energy management system (EMS), the primary control techniques are studied for the real-time operation of an EVCS. In order to ensure the stability, dynamic capability of the EV charging micro grid system, this work investigated the coordinated control techniques of an EVCS with a local PV system and ESS.Secondly, in order to reduce the operation costs of the EVCS, an approximate dynamic programming (ADP) based EMS is proposed for the EVCS equipped with multiple types of chargers (EVCS-MTC). Multiple EVs can acquire the charging service through a common charger in the EVCS-MTC. In the proposed EMS, the ADP and the evolution algorithm (EA) are combined to determine the optimal charging start time for each EV.Lastly, in order to integrate the renewable energy into EVCS, a finite-horizon Markov Decision Process (MDP) formulation is proposed for the optimal operation of a PV assisted EVCS in a university campus, employing the vehicle-to-grid (V2G) technology to provide ancillary services and taking dynamic electricity price and uncertain behaviors of EV owners into considerations

In a smart city, it is vital to provide a clean and green environment by curbing air pollution and greenhouse gas emissions (GHGs) from transportation. As a recent action from many governments aiming to minimize transportation’s pollution upon the climate, new plans have been announced to ban cars with gas engines throughout the world. Therefore, it is anticipated that the presence of electric vehicles (EVs) will grow very fast globally. Consequently, the necessity to establish electric vehicle supply equipment (EVSE) in the smart city through public charging stations is growing incrementally year by year. However, the EV charging process via EVSE which is primarily connected to the power grid will put high pressure upon the centralized power grid, especially during peak demand periods. Increasing the power production of power grid will increase the environmental impact. Therefore, it is fundamental for the smart city to be equipped with a modern power grid to cope with the traditional power grid’s drawbacks. In this thesis, we conduct an in-depth analysis of the problem of EVs’ interaction with the modern power grid in a smart city to manage and control EV charging and discharging processes. We also present various approaches and mechanisms toward identifying and investigating these challenges and requirements to manage the power demand. We propose novel solutions, namely Decentralized-EVSE (D-EVSE), for EVs’ charging and discharging processes based on Renewable Energy Sources (RESs) and an energy storage system. We present two algorithms to manage the interaction between EVs and D-EVSE while maximizing EV drivers’ satisfaction in terms of reducing the waiting time for charging or discharging services and minimizing the stress placed on D-EVSE. We propose an optimization model based on Game Theory (GT) to manage the interaction between EVs and D-EVSE. We name this the decentralized-GT (D-GT) model. This model aims to find the optimal solution for EVs and D-EVSE based on the concept of win-win. We design a decentralized profit maximization algorithm to help D-EVSE take profit from the electricity price variation during the day when selling or buying electricity respectively to EVs or from the grid or EVs as discharging processes. We implement different scenarios to these models and show through analytical and simulation results that our proposed models help to minimize the D-EVSE stress level, increase the D-EVSE sustainability, maximize the D-EVSE profit, as well as maximize EV drivers’ satisfaction and reduce EVs’ waiting time.

Neben der Verringerung von Verkehrsunfällen und Staus ist ein wichtiges Ziel der Verkehrspsychologie, die Luftverschmutzung durch den Verkehr zu reduzieren. Elektrofahrzeuge (BEVs) könnten die CO2-Emissionen deutlich reduzieren. Der weltweite BEV-Bestand nimmt zwar stetig zu, aber die Marktanteile in den meisten EU-Ländern lag 2016 dennoch nur bei rund 1% (International Energy Agency, 2016). Eine weitreichende Verbreitung von Elektrofahrzeugen birgt nicht nur Vorteile in sich, sondern kann auch zur Belastung der Stromnetze führen. ‚Intelligente Ladesysteme‘, die den Ladeprozess an die Netzbelastung und Nutzeranforderungen (z.B. Ladestand bei Abfahrtszeit) anpassen, gelten als vielversprechende Lösung. Vor dem Hintergrund der bisher geringen Verbreitung von Elektrofahrzeugen und der mit einem Erfolg der Elektromobilität steigenden Relevanz intelligenter Ladesysteme entsteht die Notwendigkeit psychologische Faktoren zu identifizieren, die die Evaluation und Akzeptanz von Komponenten des Elektromobilitätssystems beeinflussen. An dieser Stelle knüpft die vorliegende Dissertation an. Der (praktische) Erfahrungshorizont vieler Menschen in Bezug auf Elektrofahrzeuge und intelligente Ladesysteme ist sehr limitiert. Unerfahrene Nutzer solch neuer Systeme begegnen bisher unbekannten Herausforderungen in der Mensch-Maschine-Interaktion. Beispielsweise geht das elektrische Fahren, im Vergleich zum Fahren herkömmlicher Fahrzeuge, mit einer wesentlich niedrigeren Reichweite, einer geringeren Geräuschkulisse, neuen „Nachtankprozessen“ und Fahrfunktionen wie der Rekuperation (d.h. regeneratives Bremsen bei dem kinetische in elektrische Energie umgewandelt wird) einher. Dieses Thema wird ebenfalls in der vorliegenden Dissertation aufgegriffen. Das erste Forschungsziel fokussierte die allgemeine Bewertung und Akzeptanz von Elektrofahrzeugen sowie den Einfluss von praktischer Erfahrung. Im Rahmen einer Feldstudie mit zwei 6-monatigen Studienphasen (Artikel II), einer Onlinestudie (Studie I von Artikel III) sowie einer 24-Stunden Testfahrt (Studie II von Artikel III) wurde dieses Ziel untersucht. Für die verschiedenen Arten von Erfahrung (langzeitig mit gleichem Fahrzeug vs. unkontrolliert vs. kurzzeitig mit gleichem Fahrzeug) zeigten sich unterschiedliche Effekte auf die Akzeptanz von Elektrofahrzeugen, die detailliert diskutiert werden. Die Berichte der Feldstudienteilnehmer (langzeitige Erfahrung) zu Vor- und Nachteilen von Elektrofahrzeugen zeigten, dass sich die Salienz bestimmter Vor- und Nachteile über die Nutzungszeit hinweg ändert. Vor allem die Vorteile, die beim Alltagstest direkt erlebt werden können (z.B. das angenehme Fahrgefühl, die geringe Geräuschkulisse), waren in ihrer Salienz gestiegen. Es gibt erlebbare Barrieren, wie die Ladedauer, die innerhalb der Feldstudie an Prägnanz verloren, aber auch andere, wie die Reichweite, die in ihrer Bedeutsamkeit konstant blieben. Die Vorher-Nachher-Studien (Artikel II & Studie II von Artikel III) zeigten, dass die Erwartungen der Tester an solch ein Fahrzeug im Alltagstest insgesamt erfüllt werden und die Einstellung gegenüber Elektrofahrzeugen positiv bleibt. Im Rahmen der 24-Stunden-Testfahrt (kurzzeitige Erfahrung) zeigte sich zudem ein Anstieg in der Zufriedenheit mit Elektrofahrzeugen. Dem gegenüber stehen die geringen Kaufabsichten der Befragten. Der Alltagstest mit einem Elektrofahrzeug, egal ob kurz- oder langzeitig, zeigte keine Effekte auf die Kaufintention. Allerdings wiesen die Ergebnisse der Onlinebefragung darauf hin, dass Personen, die bereits ein Elektrofahrzeug gefahren sind, gegenüber dem Kauf eines Elektrofahrzeugs nicht so stark abgeneigt sind wie Unerfahrene, aber dennoch keine klare Intention zeigen. Das zweite Forschungsziel bestand in der Untersuchung wie praktische Erfahrung mit dem Nutzerverhalten und der Evaluation bezüglich der Elektrofahrzeugcharakteristika zusammenspielt. Am Beispiel der Rekuperation wurde untersucht wie sich die Menschen im Rahmen einer 6-monatigen Feldstudie an solch eine Funktion gewöhnen, ihre Nutzung erlernen und ob sich dies in der Bewertung der Funktion widerspiegelt (Artikel I). Die Ergebnisse aus den Fahrzeugdaten weisen darauf hin, dass die Adaption an diese Funktion recht zügig abgeschlossen ist und dem Power Law of Practice (Newell & Rosenbloom, 1981) folgt. Die Rekuperationsfunktion wird durch die Nutzer positiv bewertet und die Zufriedenheit mit der Rekuperation steigt mit der Nutzungszeit. In zwei weiteren Studien wurde die Bewertung von Elektrofahrzeugcharakteristika zwischen Elektrofahrzeug-Erfahrenen und –Unerfahrenen verglichen. In der Onlinestudie (Studie I in Artikel III) mit dem unkontrollierten Erfahrungsfaktor zeigten sich kaum Unterschiede. Lediglich ‚Reichweite und Laden‘ bewerteten die Erfahrenen positiver. Kontrollierte, kurzfristige Erfahrung (Studie II in Artikel III) führte zu einer positiveren Bewertung von Beschleunigung und Fahrspaß, Geräuschlosigkeit, Sicherheit und Reliabilität, Umweltfreundlichkeit sowie des Rufs von Elektrofahrzeugen. Die Bewertung von Reichweite und Laden blieb unverändert. Das dritte, übergeordnete Ziel dieser Dissertation bestand darin, akzeptanzbeeinflussende Faktoren zu identifizieren, die als Ansatzpunkte für zukünftige Weiterentwicklungen und Strategien zur Erhöhung der Akzeptanz genutzt werden können. Dazu wurde das Potential der Bewertung verschiedener Elektrofahrzeugattribute, der Faktoren der Theorie des geplanten Verhaltens (Ajzen, 1991) sowie der Erfahrung mit Elektrofahrzeugen zur Vorhersage der Akzeptanz im Rahmen der beiden Studien in Artikel III untersucht. Der soziale Faktor (subjektive Norm) und die Bewertung von ‚Reichweite und Laden‘ wirkten sich am stärksten auf die Vorhersage von Einstellungs- und Verhaltensakzeptanz aus. In der Onlinestudie mit between-subjekt Design, zeigte sich zudem ein starker Erfahrungseffekt auf die Kaufabsicht. Zudem erwies sich auch der Faktor ‚Beschleunigung und Fahrspaß‘ als relevante Größe für die Akzeptanz. Vor dem Hintergrund der aktuellen Entwicklungen, im Detail den sinkenden Batteriekosten und damit günstiger werdenden Reichweiteressourcen, eröffnen die Ergebnisse Ansatzpunkte, um die Akzeptanz zu steigern. Die Bewertung der Performanz und das angenehme Fahrgefühl beim elektrischen Fragen weisen einen nicht zu vernachlässigbaren Einfluss auf die Akzeptanz von Elektrofahrzeugen auf und konnten durch ein kurzzeitiges Erfahrungserlebnis positiv beeinflusst werden. Das letzte Forschungsziel dieser Dissertation fokussierte das intelligente Laden. Die Ergebnisse der 5-monatigen Feldstudie (Artikel IV) zeigten, dass ein intelligentes Ladesystem (mit aktiver Nutzerbeteiligung) nutzbar und akzeptabel ist. Allerdings zeigten die Ergebnisse auch, dass eine positive Kosten-Nutzen-Bilanz für die Nutzer von hoher Relevanz ist. Der zusätzliche Aufwand beim Laden erwies sich als signifikant höher und die finanziellen Anreize durch die Nutzung des Systems als niedriger als erwartet. Zudem fühlten sich die Nutzer durch das System zusätzlich in ihrer Mobilität eingeschränkt. Demnach sollten zukünftige, intelligente Ladesysteme sorgfältig gestaltet werden, so dass der Aufwand und die Reduzierung von Flexibilität und Mobilität nicht so hoch sind, dass die Barriere "Reichweite und Laden" für die Akzeptanz von Elektrofahrzeugen erhöht wird. Basierend auf den Ergebnissen wurden verschiedene Implikationen abgeleitet. Die Weiterentwicklung des Elektromobilitätssystems sollte sich darauf konzentrieren, die Barrieren bezüglich Reichweite und Laden zu reduzieren sowie die positiven Aspekte des elektrischen Fahrens zu vermitteln. Zudem sollten zukünftige Akzeptanzmodelle, vor allem für bisher eher unbekannte Objekte oder Technologien, einen Erfahrungsfaktor und die Bewertung verschiedener, objekt-/technologie-spezifischer Attribute enthalten, da dadurch wichtige Aspekte zur Verbesserung des Forschungsobjektes identifiziert werden können. Die Ergebnisse zeigten außerdem, dass der soziale Einfluss in zukünftigen Strategien zur Akzeptanzförderung von Elektrofahrzeugen adressiert werden sollte und eine Testfahrt mit einem Elektrofahrzeug, das dem aktuellen Entwicklungsstand entspricht, ein strategisches Werkzeug zur Akzeptanzsteigerung darstellt.

Currently, the proliferation of electrified vehicles (EV) has increased rapidly. Considering EV users’ point of view, the duration of charging, and the place to charge their car are essential factors. Increase of EV penetration gives also impact on the electrical network such as overloading, and power quality issues. IEC 61851 and ISO 15118 are the two primary standards to provide requirements for electric vehicle supply equipment (EVSE) to ensure the process of charging can be adequately conducted without disrupting the electric system in general. Following standards and considering the user’s preference in charging place, a new charging method that can draw higher energy than existing technique should be developed. A three-phase grid connected home system is modeled in this study to see the impact of unbalance household load to a three-phase charging. The load modeling covers the variation level of load in summer, spring/fall, and winter. Specific usages of electricity are distributed in a three-phase home system which consists of phase 1: cold appliance, cooking, standby appliances, and other loads; phase 2: heat pumps, audiovisual (Television and sound system) and computer size; and phase 3: Lightning and washing. Two methods of charging are defined in this model, which are symmetrical (existing standard) and asymmetrical (proposed). In symmetrical technique, the On-board Charger (OBC) will draw equal phase current independent of home loads connected in each phase of three phase system. The three phase system will not balanced completely in this method. Meanwhile, in asymmetrical method, the OBC will draw the leftover of current in each phase according to its real-time availability by balancing all three phase in the home. The asymmetrical method is expected to achieve faster charging duration than symmetrical charging due to higher energy availability. There three main cases defined in this study: theoretical case (the EV is charged from hour 00:00), 0-100% SOC case, and the user case (the distance targeted determines Car Demand). The result of simulation reveals that Asymmetrical charging method can provide higher energy available than asymmetrical technique. Fuse-rating level influences a lot on this result. If the higher fuse rating applied in the same load profile, the gap of energy availability between symmetrical and asymmetrical will be reduced. But still the symmetrical method never perform better energy availability than the asymmetrical method, either with 16 A fuse and 20 A fuse. This result of energy availability becomes an indication for 3 the theoretical case, in which asymmetrical method can provide more charging cycles than the symmetrical method, especially for 16 A fuse system. For all cases that have been simulated, the asymmetrical method shows benefits in terms of reduction in time and cost reduction. In a year, the saving of hours of charging duration which could be achieved by new charging method in a 16 A fuse system is as high as 8 hours and 4 hours for 0-100% SOC cases and partial charging user cases respectively (less than 50% approx.). In a three-year cost comparison, the money that could be saved by the asymmetrical method in a 16 A fuse system are as high as 35 Euro for 0-100% case and 23,405 Euro in the user case. After simulations result obtained, asymmetrical method demonstrates a promising performance of the new charging technique in terms of duration and saving. There is a need to push a new standard to realize the implementation of this charging activity. A communication scheme between energy meter, EVSE, and OBC should be established to exchange real-time current availability information. New AC information sequences could be adapted from the DC charging communication standard, IEC 61851-24.<br>För närvarande har spridningen av elektrifierade fordon (EV) ökat snabbt. Att ta hänsyn till EVanvändarnas synvinkel, laddningstiden och platsen att ladda sin bil är väsentliga faktorer. Ökning av EVpenetration ger också inverkan på det elektriska nätverket, såsom överbelastning och problem med kraftkvalitet. IEC 61851 och ISO 15118 är de två primära standarderna för att tillhandahålla krav på elfordonsförsörjningsutrustning (EVSE) för att säkerställa att laddningsprocessen kan genomföras på ett adekvat sätt utan att störa det elektriska systemet i allmänhet. Efter standarder och med tanke på användarens preferens på laddningsplats bör en ny laddningsmetod som kan dra högre energi än befintlig teknik utvecklas. Ett tre-fas nätanslutet hemsystem modelleras i denna studie för att se effekterna av obalanserad hushållsbelastning på en trefasladdning. Lastmodelleringen täcker variationen i lasten på sommaren, våren / hösten och vintern. Specifika användningsområden för elektricitet distribueras i ett trefas hemsystem som består av fas 1: kallapparat, matlagning, standbylagare och andra laster; fas 2: värmepumpar, audiovisuella (TV- och ljudsystem) och datorstorlek; och fas 3: Blixt och tvätt. Två laddningsmetoder definieras i denna modell, som är symmetriska (befintlig standard) och asymmetriska (föreslagna). I symmetrisk teknik drar ombordladdaren (OBC) lika fasström oberoende av hembelastningar anslutna i varje fas i trefassystemet. Trefassystemet kommer inte att balansera helt i denna metod. Under tiden, i asymmetrisk metod, kommer OBC att dra återstoden av strömmen i varje fas enligt dess realtids tillgänglighet genom att balansera alla tre faserna i hemmet. Den asymmetriska metoden förväntas uppnå snabbare laddningstid än symmetrisk laddning på grund av högre energitillgänglighet. Det finns tre huvudfall definierade i denna studie: teoretiskt fall (EV debiteras från timme 00:00), 0-100% SOC-fall och användarfallet (avståndsinriktningen avgör bilfrågan). Resultatet av simulering avslöjar att asymmetrisk laddningsmetod kan ge högre tillgänglig energi än asymmetrisk teknik. Säkringsgraden påverkar mycket på detta resultat. Om den högre säkringsgraden som tillämpas i samma belastningsprofil kommer energiförbrukningen mellan symmetrisk och asymmetrisk att minska. Men fortfarande har den symmetriska metoden aldrig bättre energitillgänglighet än den asymmetriska metoden, varken med 16 A-säkring och 20 A-säkring. Detta resultat av energitillgänglighet blir en indikation för det teoretiska fallet, i vilket asymmetrisk metod kan ge fler laddningscykler än den symmetriska metoden, särskilt för 16 A-säkringssystem. För alla fall som har simulerats visar den asymmetriska metoden fördelar när det gäller minskning av tid och kostnadsminskning. På ett år är besparingen av timmar med laddningstid som kan uppnås genom en ny laddningsmetod i ett säkringssystem på 16 A så hög som 8 timmar och 4 timmar för 0-100% SOC-fall respektive partiell laddning av användarfall (mindre än 50% ungefär). I en kostnadsjämförelse på tre år är de pengar som kan sparas med den asymmetriska metoden i ett säkringssystem på 16 A så höga som 35 Euro för 0-100% fall och 23 405 Euro i användarfallet. Efter erhållna simuleringsresultat visar den asymmetriska metoden en lovande prestanda för den nya laddningstekniken när det gäller varaktighet och sparande. Det finns ett behov att driva en ny standard för att realisera genomförandet av denna avgiftsaktivitet. Ett kommunikationsschema mellan energimätare, EVSE och OBC bör inrättas för att utbyta information om aktuell tillgänglighet i realtid. Nya ACinformationssekvenser kan anpassas från DC-laddningskommunikationsstandarden, IEC 61851-24.

The voltage profile of the catenary between traction substations (TSSs) is affected by the trolleybus current intake and by its position with respect to the TSSs: the higher the current requested by the bus and the further the bus from the TSSs, the deeper the voltage drop. When the voltage drops below 500V, the trolleybus is forced to decrease its consumption by reducing its input current. This thesis deals with the analysis of the improvements that the installation of an BESS produces in the operation of a particularly loaded FS of the DC trolleybus network of the city of Bologna. The stationary BESS is charged by the TSSs during off-peak times and delivers the stored energy when the catenary is overloaded alleviating the load on the TSSs and reducing the voltage drops. Only IMC buses are considered in the prospect of a future disposal of all internal combustion engine vehicles. These trolleybuses cause deeper voltage drops because they absorb enough current to power their traction motor and recharge the on board battery. The control of the BESS aims to keep the catenary voltage within the admissible voltage range and makes sure that all physical limitations are met. A model of FS Marconi Trento Trieste is implemented in Simulink environment to simulate its daily operation and compare the behavior of the trolleybus network with and without BESS. From the simulation without BESS, the best location of the energy storage system is deduced, and the battery control is tuned. Furthermore, from the knowledge of the load curve and the battery control trans-characteristic, it is formulated a prediction of the voltage distribution at BESS connection point. The prediction is then compared with the simulation results to validate the Simulink model. The BESS allows to decrease the voltage drops along the catenary, the Joule losses and the current delivered by the TSSs, indicating that the BESS can be a solution to improve the operation of the trolleybus network.

The world is now in a transition towards a more sustainable future. Actions to reduce the green-house gases (GHG) emissions have been promoted and implemented globally, including switching to electric vehicles (EVs) and renewable energy technologies, such as solar photovoltaics (PV). This has led to a massive increase of EVs and PV adoption worldwide in the recent decade. However, large integration of EVs and PV in buildings and electricity distribution systems pose new challenges such as increased peak loads, power mismatch, component overloading, and voltage violations, etc. Improved synergy between EVs, PV and other building electricity load can overcome these challenges. Coordinated charging of EVs, or so-called EV smart charging, is believed to a promising solution to improve the synergy. This licentiate thesis investigates the synergy between residential EV charging and PV generation with the application of EV smart charging schemes. The investigation in this thesis was carried out on the individual building, community and distribution grid levels. Smart charging models with an objective to reduce the net-load (load - generation) variability in residential buildings were developed and simulated. Reducing the net-load variability implies both reducing the peak loads and increasing the self-consumption of local generation, which will also lead to improved power grid performance. Combined PV-EV grid hosting capacity was also assessed.       Results show that smart charging schemes could improve the PV self-consumption and reduce the peak loads in buildings with EVs and PV systems. The PV self-consumption could be increased up to 8.7% and the peak load could be reduced down to 50%. The limited improvement on self-consumption was due to low EV availability at homes during midday when the solar power peaks. Results also show that EV smart charging could improve the grid performance such as reduce the grid losses and voltage violation occurrences. The smart charging schemes improve the grid hosting capacity for EVs significantly and for PV slightly. It can also be concluded that there was a slight positive correlation between PV and EV hosting capacity in the case of residential electricity distribution grids.

Transportsektorn står inför en omställning från förbränningsfordon till eldrivna fordon. Detta är en åtgärd för att minska koldioxidutsläppet inom transportsektorn och därmed reducera klimatpåverkan. Syftet med studien är att undersöka hur en ökad effektanvändning i form av elbilsladdning påverkar Gävles lokala elnät samt hur olika laddtekniker påverkar elnätet. Bakgrunden till studien grundar sig att elnätsföretaget vill öka medvetenheten om hur elnätets beredskap ser ut för en ökad elbilsladdning. Att undersöka elbilsladdningens påverkan på elnätet är av stor nytta för elnätsföretaget, men även andra som undersöker elbilsladdnings påverkan i elnätet kan ha användning för studien. Ämnet elbilsladdning är mycket aktuellt och många studier undersöker olika delar som berör elbilsladdning. Tidigare studier undersöker även olika typer av laddtekniker och hur smart laddning minska påverkan i elnätet. Smart laddning kan anpassa elbilsladdningen genom att styra den efter olika styrsignaler och sammankoppla hela elnätet. Denna studie undersöker delar av Gävles lokala elnät genom att simulera befintliga mätvärden lågspänningsnätet samt olika typer av elbilsladdning. Studien analyserar effektanvändningen av befintliga mätdata samt belastningsström och spänningsfall i elnätet med varierande lastprofiler i fyra olika områden. Resultatet för denna studie visar att elbilsladdning påverkar elnätet, vilket beror på vilken typ av laddteknik som används samt dimensioneringen av elnätet. Studien visar att elanvändningen i området idag har effekttoppar på eftermiddag och kväll när kunderna består av villakunder men att effekttoppen kan vara mitt på dagen där det finns industrier. Med elbilsladdning ökar belastningen samt spänningsfallet i nätet och en del av säkringarna i nätet löser ut. Laddning med 11 kW mellan kl. 16:00-19:00 samt laddning med effektvakt på 13,8 kW ger störst belastning och spänningsfall. Laddning utan styrning är den laddteknik som påverkar elnätet mest men laddning med effektvakt orsakar också problem. Laddning med 5,5 kW mellan kl. 23:00-06:00 samt när endast 50% av alla kunder laddar med 11 kW mellan kl. 16:00-19:00 är de scenarion som påverkar elnätet minst. Laddning med en låg effekt under natten när grundlasten är som lägst är den laddteknik som är mest gynnsam för elnätet. Studien visar även att nätet klarar en högre belastning av elbilsladdning inom en snar framtid om endast en del av kunderna i nätet använder elfordon.<br>The transport sector is facing a transition from combustion engine vehicles to electric vehicles. Through this action the carbon dioxide emissions in the transport sector can be reduced. The purpose of this study is to observe how an increased power use from electric vehicle charging (EVC) affects the local electricity grid in Gävle. The study also addresses how different charging techniques affect the electricity grid. The background of this study is to the increase awareness of the capacity of the electricity grid. There is a need from the electricity grid company to look over the impact on the grid from EVC. This could also be useful for others looking over the impact on the electricity grid from EVC. This is a hot topic and lots of other studies look over the different aspects of EVC. Previous studies also examine different types of charging techniques and how smart charging reduces the negative impact on the electricity grid. Smart charging is a way to adjust the EVC by regulating it after different parameters and connecting the entire electrical grid. This study simulates existing measured values of the low-voltage grid in Gävle and various types of EVC. This study examines the power use of existing measurement data as well as load current and voltage drops in the electricity grid with different load profiles in four different areas. Results from this study shot that EVC affects the electricity grid, to what extent depends on the type of charging technology used and the dimensions of the electricity grid. The study shows that electricity use in the area has power peaks in the afternoon and evening with residential customers, but power peaks tend to be in the middle of the day if there are industries in the area. EVC increase the load on the electricity grid, causes voltage drops and a few fuses in the grid to be triggered. Charging with 11 kW between 16:00-19:00 and charging with a power monitor of 13.8 kW create the greatest voltage drops and highest load on the grid. Charging without means of control affects the electricity grid the most but charging with a power monitor also creates problems. Charging with 5.5 kW between 23:00-06:00 as well as when only 50 % of all customers charge with 11 kW between 16:00-19:00 impacts the grid the least. Charging with low power during the night when the base load is at its lowest is the charging technology that is most favorable for the electricity grid. Results also show that the grid can handle a higher load of EVC in the near future if only some of the customers in the network start using electric vehicles.

The increase in electric vehicles and photovoltaic power production may introduce problems to the low-voltage distribution grid. With a higher number of electric vehicles, their accumulated charging power might breach the lowest allowed voltage level of the grid. Photovoltaic-modules can on the other hand exceed the highest allowed voltage level, by producing high accumulated power when the solar irradiance is high. Normally, electric distribution companies in Sweden reinforce the existing grid with more resilient infrastructure, such as stronger and larger cables or transformer stations. This is however a costly and time-consuming solution, which could be solved by using alternative means such as already existing resources. This Master's Thesis investigates how smart charging of batteries can support the low-voltage electrical grid with the increase in electric vehicles and photovoltaic power production. To do this, an optimization tool has been developed in Matlab. An existing model of a low-voltage grid is combined with the developed tool, where controllable batteries and photovoltaic-modules can be placed at specific households in the grid. The controllable batteries belong to either electric vehicles or stationary battery systems, and are intended to support the grid by the means of either reducing peak load powers, voltage variations, or a trade-off between them. Furthermore, this thesis investigates the maximum electric vehicle capability for a specific low-voltage electrical grid in Sweden. From the results, it can be concluded that smart charging of batteries can reduce the peak loads as well as voltage variations. The reduction of voltage variations for the entire low-voltage grid is greatest during the summer, when photovoltaic production generally is at its highest. The results also show that a stationary battery system can reduce the voltage variations to a greater extent, compared to an electric vehicle. Also, the introduction of multiple controllable batteries allows further support of the low-voltage grid. Regarding the maximum electric vehicle capability, the results show that the placement of the vehicles and the charging power strongly affect the maximum number of electric vehicles the low-voltage grid can manage.<br>Ökningen av elbilar och elproduktion från solceller kan ge problem i lågspänningsnätet. Med ett ökat antal elbilar kan den sammanlagrade effekten vid laddning underskrida den minsta tillåtna spänningsnivån i nätet. Solpaneler kan däremot leda till att den högsta tillåtna spänningsnivån överskrids, genom att producera en hög sammanlagrad effekt när solstrålningen är som högst. Vanligtvis förstärker elnätsbolag i Sverige det befintliga nätet med motståndskraftigare infrastruktur, såsom kraftigare och större kablar eller transformatorstationer. Detta är dock en kostsam och tidskrävande lösning, som skulle kunna lösas med alternativa medel, till exempel redan existerande resurser. Detta examensarbete undersöker hur smart laddning av batterier kan ge stöd till lågspänningsnätet, med en ökning av elbilar samt solcellsproduktion. För att undersöka detta har ett optimeringsverktyg utvecklats i Matlab. En befintlig modell av ett lågspänningsnät har kombinerats med det utvecklade optimeringsverktyget, där styrbara batterier samt solcellsproduktion kan placeras vid specifika hushåll i elnätet. De styrbara batterierna är antingen elbilar eller stationära batterisystem, och är ämnade till att stödja lågspänningsnätet genom att antingen reducera effekttoppar, spänningsvariationer eller en kompromiss av båda. Vidare undersöker detta examensarbete det maximala antalet elbilar som ett specifikt lågspänningsnät i Sverige kan hantera. Resultaten visar att smart laddning av batterier kan reducera effekttoppar samt spänningsvariationer. Reduceringen av spänningsvariationerna för hela lågspänningsnätet visar sig vara högst under sommaren, vilket är då solcellsproduktionen generellt är som högst. Resultaten visar även att stationära batterisystem kan reducera spänningsvariationer ytterligare, jämfört med en elbil. Att introducera flera styrbara batterier tillåter ett ännu större stöd till lågspänningsnätet. Angående det maximala antalet av elbilar som ett lågspänningsnät kan hantera visade resultaten att placeringen av elbilarna samt laddningseffekten har en stor påverkan.

Les ventes de Véhicules Electriques ont été en constante augmentation ces dix dernières années, stimulées par l’adoption de politique publique favorisant la décarbonation du secteur automobile. Dans un contexte d’accroissement des énergies renouvelables dans le mix énergétique, entraînant des besoins plus important en flexibilité, la diffusion massive des véhicules électriques pourrait constituer une nouvelle source de contrainte pour les gestionnaire de réseaux d'électricité si la recharge n’est pas gérée de manière intelligente.La gestion de la recharge des flottes de Véhicules Electriques peut aussi constituer une opportunité pour apporter cette flexibilité, en particulier si les véhicules sont équipés de chargeurs bidirectionnels, capables de réinjecter de l’électricité dans le système pour équilibrer les réseaux.La recherche s’est principalement intéressée à la conception d’algorithmes permettant cette recharge « intelligente », qui prennent en compte les besoins en mobilité des utilisateurs, tout en fournissant différents services de flexibilité.Cette thèse s’attache à aller au-delà de l’aspect algorithmique, en balayant l’ensemble des aspects qui permettraient d’aboutir à un modèle d’affaire viable, et en se focalisant sur la fourniture d’un type de service : la réserve primaire (Frequency Containment Reserve), qui constitue le service identifié comme ayant la plus forte valeur pour des flottes de Véhicules équipés de chargeurs bidirectionnels<br>Transport industry being one the first CO2 emitters, there is an urgent need to decarbonize this sector, which could be achieved by the conjunction of the electrification of the vehicles and decarbonization of the electricity generation mix. In conjunction with increasing flexibility needs to support the introduction of Renewable Energy Sources, the development of Electric Vehicles could add new constraints for System Operators if charging process is not managed in a smart way.However, considering mobility requirements, there is a flexibility in the charging pattern of the vehicles, which could be used to offer flexibility services to System Operators, using smart-charging algorithms. Moreover, this flexibility could increase with the possibility to have reverse flow from the battery to the grid.Research focused mainly, during last years, on the design of algorithms to provide services with electric vehicles, taking into account mobility needs of users. In this thesis, we try to go beyond this design of algorithms, going through the different steps to elaborate a viable business model. We focus on the provision of one service – Frequency Containment Reserve – identified as the most valuable for Electric Vehicles equipped with bidirectional chargers

Elektrifieringen av bilflottan sker i rasande takt. Även andra samhällssektorers efterfrågan på el väntas öka drastiskt under kommande decennier, vilket i kombination med en växande andel intermittenta energikällor trappar upp påfrestningarna på elnätet och ställer krav på anpassningar. En föreslagen dellösning till kraftsystemets kommande utmaningar är att utnyttja efterfrågeflexibiliteten i laddande elbilar genom att en aggregator styr ett stort antal elbilsladdare och säljer den sammanlagda kapaciteten på till exempel Svenska kraftnäts stödtjänstmarknader.  För att avgöra hur mycket flexibilitet som elbilsladdning kan bidra med behöver aggregatorn upprätta prognoser över hur mycket effekt som mest sannolikt finns tillgänglig vid en viss tidpunkt – en punktprognos – men också en uppskattning av vilken effektnivå man kan vara nästan säker på att utfallet överstiger – en kvantilprognos. I den här studien har en undersökning gjorts av hur prognosfelet förändras om gruppen av aggregerade elbilsladdare ökas, och hur mycket en aggregator på så sätt kan sänka sina marginaler vid försäljning av efterfrågeflexibiliteten för att med säkerhet kunna uppfylla sitt bud. Det gjordes genom att kvantifiera flexibiliteten för 1 000 destinationsladdare belägna vid huvudsakligen arbetsplatser, och genom att skala upp och ner datamängden genom slumpmässiga urval. För dessa grupper gjordes sedan probabilistiska prognoser av flexibiliteten med en rullande medelvärdes- och en ARIMA-modell. Utifrån prognoserna simulerades slutligen potentiella intäkter om aggregatorn skulle använda den flexibla kapaciteten för uppreglering till stödtjänsten FCR-D upp, vilket är en frekvensreserv som aktiveras vid störningar av nätfrekvensen.  Resultaten visar att en tiodubbling av antalet aggregerade elbilsladdare mer än halverar det relativa prognosfelet. De båda prognosmodellerna visade sig ha jämförbar precision, vilket talar för att använda sig av den rullande medelvärdesmetoden på grund av dess lägre komplexitet. Den ökade säkerheten i prognosen resulterade dessutom i högre intäkter per laddare.  De genomsnittliga intäkterna av att leverera flexibilitet från 1 000 aggregerade elbilsladdare till FCR-D uppgick till 6 900 kr per månad, eller 0,8 kr per session – siffror som troligen hade varit högre utan coronapandemins ökade hemarbete. En 99-procentig konfidensgrad för kvantilprognosen resulterade i en säkerhetsmarginal med varierande storlek, som i genomsnitt var runt 90 procent för 100 laddpunkter, 60 procent för 1 000 laddpunkter samt 30 procent för 10 000 laddpunkter. Mest flexibilitet fanns tillgänglig under vardagsförmiddagar då ungefär 600 kW fanns tillgängligt som mest för 1 000 laddpunkter.  Att döma av tio års nätfrekvensdata är den sammanlagda sannolikheten för att över 50 procent aktivering av FCR-D-budet skulle sammanfalla med att utfallet för den tillgängliga kapaciteten är en-på-hundra-låg i princip obefintlig – en gång på drygt 511 år. Att aggregatorn lägger sina bud utifrån en 99-procentig konfidensgrad kan alltså anses säkert.<br>The electrification of the car fleet is taking place at a frenetic pace. Additionally, demand for electricity from other sectors of the Swedish society is expected to grow considerably in the coming decades, which in combination with an increasing proportion of intermittent energy sources puts increasing pressure on the electrical grid and prompts a need to adapt to these changes. A proposed solution to part of the power system's upcoming challenges is to utilize the flexibility available from charging electric vehicles (EVs) by letting an aggregator control a large number of EV chargers and sell the extra capacity to, for example, Svenska kraftnät's balancing markets. To quantify how much flexibility charging EVs can contribute with, the aggregator needs to make forecasts of how much power that is most likely available at a given time – a point forecast – but also an estimate of what power level the aggregator almost certainly will exceed – a quantile forecast. In this study, an investigation has been made of how the forecast error changes if the amount of aggregated EV chargers is increased, and how much an aggregator can lower their margins when selling the flexibility to be able to deliver according to the bid with certainty. This was done by quantifying the flexibility of 1000 EV chargers located at mainly workplaces, and by scaling up and down the data through random sampling. For these groups, probabilistic forecasts of the flexibility were then made with a moving average forecast as well as an ARIMA model. Based on the forecasts, potential revenues were finally simulated for the case where the aggregator uses the available flexibility for up-regulation to the balancing market FCR-D up, which is a frequency containment reserve that is activated in the event of disturbances. The results show that a tenfold increase in the number of aggregated EV chargers more than halves the forecast error. The two forecast models proved to have comparable precision, which suggests that the moving average forecast is recommended due to its lower complexity compared to the ARIMA model. The increased precision in the forecasts also resulted in higher revenues per charger. The average income from delivering flexibility from 1000 aggregated electric car chargers to FCR-D amounted to SEK 6900 per month, or SEK 0.8 per session – figures that would probably have been higher without the corona pandemic's increased share of work done from home. A 99 percent confidence level for the quantile forecast resulted in a safety margin of varying size, which on average was around 90 percent for 100 chargers, 60 percent for 1000 chargers and 30 percent for 10,000 chargers. Most flexibility was shown to be available on weekday mornings when approximately 600 kW was available at most for 1000 chargers. By examining frequency data for the Nordic power grid from the past ten years, the joint probability that a more than 50 percent activation of the FCR-D bid would coincide with the outcome for the available capacity being one-in-a-hundred-low, was concluded to be nearly non-existent – likely only once in about 511 years. For the aggregator to place bids based on a 99 percent confidence level can thus be considered safe.

碩士<br>國立彰化師範大學<br>電子工程學系<br>104<br>This article is based on the concept of travel charger as a basis for the use of a Microchip PIC16 (L) F1936 wafer analogy signals into digital signals, via a 16x2 LCD display module shows the battery voltage, current, temperature, and also monitor the voltage, current, ,temperature. Preventing the battery voltage is too high because the current is too large, abnormal temperature rises beyond the setpoint range it off to protect the lithium battery, to avoid damage to the battery, so that in the shortest time to reach fully charge the battery. And establish a connection with the computer through a USB to RS232, using Microsoft Visual Studio draw a relationship between voltage, current, temperature of the curve.

碩士<br>明新科技大學<br>電機工程系碩士班<br>107<br>The main cause of climate change is global warming, which has many negative consequences on biological and human systems. In order to reduce the use of fossil fuels, many countries have begun to develop green energy technologies. Using electric vehicles to replace internal combustion engine vehicles to reduce greenhouse gas emissions is a key issue. How to build effective charging system is the first priority for the development of electric vehicles. This thesis proposes a smart selection charging management system for electric vehicles. Before charging, the charging system selects an electric vehicle with higher priority to charge according to the load condition, sate of charge of electric vehicles and the priority settings. In order to avoid frequently switching between electric vehicles, the system is designed to have a charging cycle time of 10 minutes. After 10 minutes operation, the charging system will reselect the electric vehicle with higher priority to charge. This process is repeated until all electric vehicles are fully charged. The feasibility of the developed smart selection charging management system for electric vehicles is demonstrated by the case studies, and the research results can be used as a reference for the development of electric vehicle charging system in the future.

碩士<br>國立中山大學<br>電機電力工程國際碩士學程<br>104<br>A procedure for implementing smart charging and network reconfiguration is formulated in this thesis. This technique aims to mitigate the negative impact in the operating cost that may occur due to the presence of large number of electric vehicles connected into power distribution systems. Price-based demand response is implemented for smart charging, where the electric vehicles are charged based on their availability and the energy price. A day-ahead market is considered, from where the forecasted energy price and initial load profile is collected. Linear programming optimization model is used to determine the hourly charging level of each electric vehicle with the goal of minimizing the charging costs. After the smart charging is carried out, the total scheduled charging load is added to the forecasted initial load profile of the distribution system. Network reconfiguration considering the switching cost is then performed to reduce the operating cost of the distribution system resulting from power losses and the switching operation. Genetic algorithm technique is adopted to determine the hourly configuration of the system. The proposed procedure is tested in a modified IEEE system under smart grid framework. Simulations results are provided to validate the effectiveness of the proposed method.

abstract: Currently, one of the biggest limiting factors for long-term deployment of autonomous systems is the power constraints of a platform. In particular, for aerial robots such as unmanned aerial vehicles (UAVs), the energy resource is the main driver of mission planning and operation definitions, as everything revolved around flight time. The focus of this work is to develop a new method of energy storage and charging for autonomous UAV systems, for use during long-term deployments in a constrained environment. We developed a charging solution that allows pre-equipped UAV system to land on top of designated charging pads and rapidly replenish their battery reserves, using a contact charging point. This system is designed to work with all types of rechargeable batteries, focusing on Lithium Polymer (LiPo) packs, that incorporate a battery management system for increased reliability. The project also explores optimization methods for fleets of UAV systems, to increase charging efficiency and extend battery lifespans. Each component of this project was first designed and tested in computer simulation. Following positive feedback and results, prototypes for each part of this system were developed and rigorously tested. Results show that the contact charging method is able to charge LiPo batteries at a 1-C rate, which is the industry standard rate, maintaining the same safety and efficiency standards as modern day direct connection chargers. Control software for these base stations was also created, to be integrated with a fleet management system, and optimizes UAV charge levels and distribution to extend LiPo battery lifetimes while still meeting expected mission demand. Each component of this project (hardware/software) was designed for manufacturing and implementation using industry standard tools, making it ideal for large-scale implementations. This system has been successfully tested with a fleet of UAV systems at Arizona State University, and is currently being integrated into an Arizona smart city environment for deployment.<br>Dissertation/Thesis<br>Masters Thesis Computer Engineering 2018

abstract: A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in real-time wireless systems, with the focus on the deadline-aware scheduling for real-time traffic. The optimal solution to such scheduling problems requires to explicitly taking into account the coupling in the deadline-aware transmissions and stochastic characteristics of the traffic, which involves a dynamic program that is traditionally known to be intractable or computationally expensive to implement. First, real-time scheduling with adaptive network coding over memoryless channels is studied, and a polynomial-time complexity algorithm is developed to characterize the optimal real-time scheduling. Then, real-time scheduling over Markovian channels is investigated, where channel conditions are time-varying and online channel learning is necessary, and the optimal scheduling policies in different traffic regimes are studied. The second part focuses on the stochastic optimization and real-time scheduling involved in energy systems. First, risk-aware scheduling and dispatch for plug-in electric vehicles (EVs) are studied, aiming to jointly optimize the EV charging cost and the risk of the load mismatch between the forecasted and the actual EV loads, due to the random driving activities of EVs. Then, the integration of wind generation at high penetration levels into bulk power grids is considered. Joint optimization of economic dispatch and interruptible load management is investigated using short-term wind farm generation forecast. The third part studies stochastic optimization in distributed control systems under different network environments. First, distributed spectrum access in cognitive radio networks is investigated by using pricing approach, where primary users (PUs) sell the temporarily unused spectrum and secondary users compete via random access for such spectrum opportunities. The optimal pricing strategy for PUs and the corresponding distributed implementation of spectrum access control are developed to maximize the PU's revenue. Then, a systematic study of the nonconvex utility-based power control problem is presented under the physical interference model in ad-hoc networks. Distributed power control schemes are devised to maximize the system utility, by leveraging the extended duality theory and simulated annealing.<br>Dissertation/Thesis<br>Ph.D. Electrical Engineering 2012