Abstract
An electric power supply is the backbone of development in advanced as well as in developing economies. An integral part of ensuring a secure power supply system is a power communication system. Due to the high and sustained performance requirements of power communication systems, electric companies prefer to construct their own communication networks privately rather than relying solely on a public communication system. The focus of this paper is on the optimal topological design of a power communication network. Based on advanced optimization models in public communication networks, and taking into account the specific Quality of Service, as demanded by various applications, such as protection, SCADA, voice, etc., an optimization model (PC/ISO) has been developed. The PC/ISO requires tedious numerical processing. Hence, a Genetic Algorithm (GA) is proposed to solve the optimization problem. In order to demonstrate the application of the proposed model for a power system communication network design and in order to evaluate GA solver results, a case study on designing the optimal communication network topology of one of the Iranian Regional Electric Companies has been conducted. The results suggest that the PC/ISO model and its GA solver are entirely viable and offer a simple, accurate, and cost effective solution.
Abstract
An electric power supply is the backbone of development in advanced as well as in developing economies. An integral part of ensuring a secure power supply system is a power communication system. Due to the high and sustained performance requirements of power communication systems, [...]
Abstract
Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid.Abstract
Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization [...]Abstract
Many countries have a large dependence on imported fossil fuels whose prices increase almost every day. Knowing that much of this consumption is for transportation systems, it becomes essential to seek for alternatives. The natural bet is the electric mobility, namely through Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs). However, the wide spread utilization of these vehicles has consequences on the electrical power grid, mainly in terms of load management and electric power quality, which are associated to the batteries charging systems. In this scenario, this chapter assesses the electric mobility integration in Smart Grid context, focusing different approaches to the operation of EVs and PHEVs charging processes and the specifications of the chargers, as well as different topologies of charging systems and their features, modes of operation, typical waveforms, and impact in the electrical power grid in terms of power quality. It is also presented a laboratory prototype of a bidirectional EV charger and shown some experimental results. This prototype was developed to charge the batteries aiming to preserve their lifespan, and to contribute to mitigate the degradation of the power quality. The experimental results show the operation of this prototype during the batteries charging process (G2V â Grid-to-Vehicle operation), and during the delivering of stored energy back to the electrical power grid (V2G â Vehicle-to-Grid operation). FEDER Funds - Operational Program for Competitiveness Factors â COMPETE Fundação para a Ciência e a Tecnologia (FCT) - FCOMP-01-0124-FEDER-022674, MITPT/ EDAM-SMS/0030/2008Abstract
Many countries have a large dependence on imported fossil fuels whose prices increase almost every day. Knowing that much of this consumption is for transportation systems, it becomes essential to seek for alternatives. The natural bet is the electric mobility, namely through Electric [...]Abstract
International audience; The production of PhotoVoltaic (PV) energy depends on the solar irradiance level. The PV power plant fluctuations may have a significant impact on the frequency regulation in sufficiently small power systems, such as islands. The objective of this paper is to present a method using cooperative multi-agent systems to reduce the frequency fluctuations due to the unpredicted fluctuations of the PV production using electric vehicles as electricity storage units in an isolated power system.Abstract
International audience; The production of PhotoVoltaic (PV) energy depends on the solar irradiance level. The PV power plant fluctuations may have a significant impact on the frequency regulation in sufficiently small power systems, such as islands. The objective of this paper is [...]Abstract
A new era of transportation has experienced electrification and undergoes notable changes in the last few decades. The concern about environmental friendly technology carries almost a huge expansion prospect to electric vehicles (EVs). Whereas plug-in hybrid electric vehicles (PHEVs) are recognized as a feasible term in the line of vehicular technology in the smart electric grid to lessen the dependency on fossil fuels and greenhouse gas (GHG) emissions related to conventional vehicles (CVs). The development of vehicle-to-grid (V2G) strategies establishes win?win situations for the PHEV participation without additional infrastructure cost, reduction of generation, operational and PHEV user cost, reduction of environmental pollution. Together with the expansion of the smart grid technologies, the V2G power allocation problems need to be addressed. More originally, this chapter measures substantial, though often overlooked, social barriers to the wider use of PHEVs (a likely precursor to V2G) and implementation of a V2G transition. This chapter has given an idea that the only important barriers facing the greater use of PHEVs and V2G systems are technical. Instead, it provides a broader assessment situating such ?technical? barriers alongside more subtle impediments relating to social and cultural values, business practices, and political interests. Thus, this research study recognizes probable socio-technical obstacles towards widespread adoption of V2G in smart grid and governs that if sustainability problems affect consumer decision to adopt V2G to charge their PHEVs. The current study delivers valuable understanding about the perception among technology fanatics associated with knowledge expansion and improved fortified to sort out the numerous alterations among V2G and PHEVs. Finally, the outcomes of this chapter can guide policy makers to implement V2G technology successfully. Moreover, the chapter illuminates the policy implication of such barriers, which emphasizes what policy makers need to achieve towards V2G technology adoption in smart grid environment while integrating electric vehicles engineering with consumer preference. ? Springer International Publishing AG, part of Springer Nature 2018. ScopuAbstract
A new era of transportation has experienced electrification and undergoes notable changes in the last few decades. The concern about environmental friendly technology carries almost a huge expansion prospect to electric vehicles (EVs). Whereas plug-in hybrid electric vehicles (PHEVs) [...]Abstract
With the increased environmental concerns related to carbon emission, and rapid drop in battery prices (e.g., 35% drop in 2017), the market share of Electric Vehicles (EVs) is rapidly growing. The growing number of EVs along with the unprecedented advances in battery capacity and technology results in drastic increase in the total energy demand of EVs. This large charging demand makes the EV charging scheduling problem challenging. The critical challenge is the need for online solution design since in practical scenario the scheduler has no information of future arrivals of EVs in a time-coupled underlying problem. This thesis studies online EV scheduling problem and provides three main contributions. First, we demonstrate that the classical problem of online scheduling of deadlinesensitive jobs with partial values is similar to the EV scheduling problem and study the extension to EV charging scheduling by taking into account the processing rate limit of jobs as an additional constraint to the original problem. The problem lies in the category of time-coupled online scheduling problems without availability of future information. Using competitive ratio, as a well-established performance metric, two online algorithms, both of which are shown to be (2 − 1/U)-competitive are proposed, where U is the maximum scarcity level, a parameter that indicates demand-to-supply ratio. Second, we formulate a social welfare maximization problem for EV charging scheduling with charging capacity constraint. We devise charging scheduling algorithms that not only work in online scenario, but also they address the following two key challenges: (i) to provide on-arrival commitment; respecting the capacity constraint may hinder fulfilling charging requirement of deadline-constrained EVs entirely. Therefore, committing a guaranteed charging amount upon arrival of each EV is highly required; (ii) to guarantee (group)-strategy-proofness as a salient feature to promote EVs to reveal their true type and do not collude with other EVs. Third, we tackle online scheduling of EVs in an adaptive charging network (ACN) with local and global peak constraints. Two alternatives in resource-limited scenarios are to maximize the social welfare by partially charging the EVs (fractional model) or selecting a subset of EVs and fully charge them (integral model). For the fractional model, both offline and online algorithms are devised. We prove that the offline algorithm is optimal. We prove the online algorithm achieves a competitive ratio of 2. The integral model, however, is more challenging since the underlying problem is NP-hard due to 0/1 selection criteria of EVs. Hence, efficient solution design is challenging even in offline setting. We devise a low-complexity primal-dual scheduling algorithm that achieves a bounded approximation ratio. Built upon the offline approximate algorithm, we propose an online algorithm and analyze its competitive ratio in special cases; Avec les préoccupations environnementales croissantes liées aux émissions de carbone et la chute rapide des prix des batteries, la part de marché des véhicules électriques (EV) augmente rapidement. Le nombre croissant de EV ainsi que les progrès sans précédent dans la capacité de la batterie et de la technologie entraîne une augmentation drastique de la demande totale d'énergie destinée aux véhicules électriques. Cette forte demande de charge rend complexe le problème de planification de la charge. Même en prenant avantage de la propriété reportable des demandes de charge et d'une planification adéquate, la demande globale pourrait dépasser le taux de charge tolérable des stations, étant donné les contraintes physiques des dispositifs de charge et des transformateurs. Le principal défi est la nécessité de concevoir des solutions en ligne puisque, dans la pratique, l'ordonnanceur ne dispose d'aucune information sur les arrivées futures d'EV. Cette thèse étudie le problème d'ordonnancement des EV en ligne et fournit trois contributions principales. Premièrement, nous démontrons que le problème classique de la programmation en ligne des tâches sensibles aux échéances avec des valeurs partielles est similaire au problème d'ordonnancement EV et étudions l'extension de la programmation des charges EV en prenant en compte de la limite de traitement des travaux. Le problème réside dans la catégorie des problèmes d'ordonnancement en ligne couplés dans le temps sans disponibilité d'informations futures. Le premier algorithme proposé est déterministe, tandis que le second est randomisé et bénéficie d'une complexité de calcul plus faible. Deuxièmement, nous formulons un problème de maximisation du bien-être social pour la planification de la charge des EV avec une contrainte de capacité de charge. Nous avons conçu des algorithmes d'ordonnancement de charge qui non seulement fonctionnent dans un scénario en ligne, mais aussi qui répondent aux deux principaux défis suivants : (i) fournir un engagement à l'arrivée ; (ii) garantir la résistance aux stratégies (de groupe). Des simulations approfondies utilisant des traces réelles démontrent l'efficacité de nos algorithmes d'ordonnancement en ligne par rapport à la solution hors-ligne optimale non-engagée. La troisième contribution concerne la planification en ligne des véhicules électriques dans un réseau de recharge adaptatif (ACN) avec des contraintes de pics locaux et globaux. Nous avons conçu un algorithme d'ordonnancement primal-dual de faible complexité qui atteint un rapport d'approximation borné. Des résultats expérimentaux détaillés basés sur des traces montrent que les performances des algorithmes en ligne proposés sont proches de l'optimum hors ligne et surpassent les solutions existanteAbstract
With the increased environmental concerns related to carbon emission, and rapid drop in battery prices (e.g., 35% drop in 2017), the market share of Electric Vehicles (EVs) is rapidly growing. The growing number of EVs along with the unprecedented advances in battery capacity and [...]Abstract
The number of plug-in electric vehicles (PEVs) on the road is growing significantly, which allows to reduce the consumption of greenhouse gas emitting fossil fuels, such as gasoline and diesel. This is due to the increased primary energy efficiency of electrically powered vehicles compared to conventional vehicles on the one hand, and the primary fuel flexibility for electricity generation on the other hand. The absence of tailpipe emissions reduces the local concentrations of harmful pollutants, which is benefits human health. PEVs are able to charge at every location that offers a suitable grid connection opportunity, e.g., at home and the workplace. The typical long standstill times at these locations and the low average daily driven distances allow low-power charging to fulfill the majority of the mobility needs, thereby keeping the charging infrastructure investments low. As the number of PEVs on the road increases, the grid impact of PEV charging is observed more widely, e.g., altered grid load profiles, increased peak power, and increased voltage magnitude deviations. Therefore, an extensive amount of research is conducted on coordinated charging strategies that have the objective to mitigate the grid impact of PEV charging. Typically, large-scale coordination mechanisms are being investigated, which require a sufficiently high large-scale PEV penetration rate to be effective. However, due to the clustering of PEV users, high local concentrations may occur prior to a high widespread PEV penetration. Therefore, certain distribution grids will already be impacted in the near-term future. More specifically, the residential low voltage (LV) grid impact may be challenging, due to the simultaneity between PEV charging and residential electricity consumption. This dissertation investigates several local PEV charging strategies that have the objective to mitigate the distribution grid impact with a minimal amount of external input. Two active power control strategies for PEV charging are assessed separately and in combination: voltage-dependent charging and standstill time-based charging. The former strategy does not need require any input, as the voltage magnitude is measured anyway within the onboard charger. The latter strategy only requires the next departure time, so that the charging power rating can be reduced as much as possible, while still being fully charged for the next trip. Besides the abovementioned active power control strategies, reactive power control is also investigated, i.e., reactive power current injections during PEV charging. Certain PEV charger topologies allow for the injection of reactive power flows into the grid, so this capability could be enabled. The advantage compared to the active power control strategies is that, given an appropriate sizing of the PEV charger, this grid-supportive measure does not impact the user comfort, because the active power flow is not altered. Reactive current injection does not require any external inputs, because it is merely a power factor set point of the onboard PEV charger. Finally, the distribution grid impact and sizing requirements of fast charging infrastructure is assessed. Opposed to plug-in hybrid electric vehicles (PHEVs), all of the required propulsion energy for battery electric vehicles (BEVs) must be delivered by the onboard battery. Therefore, fast charging is indispensable for long-distance driving, so that recharging does not take excessively long. Because slow and fast charging are complementary charging options, different slow charging strategies are taken into account when the fast charge requirements are assessed. Furthermore, different representative LV grid topologies are taken into account, as well as the medium voltage (MV) grid topology to which the different LV grids and the fast charging infrastructure are connected. The proposed local active and reactive power control strategies allow to substantially mitigate the distribution grid impact of PEV charging, with limited adaptations compared to their current implementation. The active power control strategies could be implemented on all of the currently used onboard PEV chargers. The reactive power control strategies can be implemented on onboard PEV chargers with a full-bridge IGBT rectifier topologies, as used for several PEVs. The distribution grid impact of the slow charging control strategies is more significant than the presence of fast charging infrastructure. Therefore, it the limited additional distribution grid impact of fast charging infrastructure can even be compensated for by implementing the proposed control strategies for slow charging. Abstract i Samenvatting iii List of abbreviations v List of symbols vii Contents xi List of figures xv List of tables xix 1. Introduction 1 1.1 Context and motivation 1 1.2 Scope and objectives 2 1.3 Outline 3 1.4 Contributions 6 2. Plug-in electric vehicle charging 7 2.1 Electric vehicle types 7 2.1.1 Battery electric vehicles 7 2.1.2 (Plug-in) hybrid electric vehicles 8 2.2 Plug-in electric vehicle batteries 11 2.2.1 Cell types 12 2.2.2 Battery pack 13 2.2.3 Battery charger 15 2.3 Charging infrastructure 17 2.3.1 Charging cases 17 2.3.2 Charging modes 18 2.3.3 Connection types 20 2.3.4 Grid connection 22 2.4 Distribution grid 23 2.4.1 LV grid layout 23 2.4.2 MV grid layout 25 2.4.3 Distribution grid constraints 26 2.5 Conclusions on PEV charging 30 3. Vehicle and fleet modeling 31 3.1 Mobility behavior 31 3.1.1 Mobility modeling 31 3.1.2 Fleet mobility behavior 32 3.2 Fleet segmentation 35 3.3 Energy efficiency modeling 38 3.3.1 Calculations 38 3.3.2 General parameters 41 3.3.3 Driving cycle 42 3.3.4 Results 44 3.3.5 Sensitivity analysis 45 3.4 Fleet power consumption 48 3.4.1 Daily power consumption 48 3.4.2 Grid impact parameters 49 3.4.3 Results 51 3.5 Conclusions 62 4. Coordinated charging 65 4.1 Background 65 4.1.1 Impact and scenario analysis 66 4.1.2 Grid planning and benchmarking 66 4.1.3 Coordination systems 67 4.2 Layers 67 4.2.1 Planning layers 69 4.2.2 Implementation layer 71 4.2.3 Operational layers 72 4.3 Objectives 73 4.3.1 Technical objectives 73 4.3.2 Economic objectives 73 4.3.3 Coupled techno economic objectives 74 4.4 Methods 75 4.4.1 Centralized methods 75 4.4.2 Distributed methods 75 4.4.3 Hierarchical methods 76 4.5 Scale of coordination 76 4.6 Correlation mapping 77 4.6.1 Research category vs. coordination objective 77 4.6.2 Research category vs. scale of coordination 78 4.6.3 Scale of coordination vs. coordination objective 79 4.6.4 Research category vs. coordination method 79 4.6.5 Scale of coordination vs. coordination method 80 4.6.6 Coordination method vs. coordination objective 81 4.7 Conclusion 81 5. Active power control 83 5.1 Background 83 5.2 Materials and methods 86 5.2.1 Distribution grid data 86 5.2.2 Residential load and generation 87 5.2.3 PEV charging load 88 5.2.4 Charging cases 88 5.2.5 Simulation approach 91 5.3 Results and discussion 91 5.3.1 Charging behavior 91 5.3.2 Voltage droop charging behavior 93 5.3.3 Power profile 94 5.3.4 Voltage magnitude profile 96 5.3.5 Voltage unbalance factor 97 5.4 Conclusions 97 6. Reactive power control 99 6.1 Background 99 6.2 Materials and methods 101 6.2.1 Distribution grid data 101 6.2.2 Residential load and generation 102 6.2.3 PEV charging behavior 104 6.2.4 Simulation approach 106 6.3 Results and discussion 107 6.3.1 User impact 107 6.3.2 Charging behavior 108 6.3.3 Grid voltages 111 6.3.4 Transformer peak load 114 6.3.5 Grid losses 115 6.4 Grid topology sensitivity 116 6.5 Conclusions 120 7. Fast charging 123 7.1 Background 123 7.1.1 Complementarity of slow and fast charging 123 7.1.2 Research on fast charging infrastructure 124 7.1.3 Scope 125 7.2 Materials and methods 125 7.2.1 Distribution grid data 125 7.2.2 Residential load and generation 128 7.2.3 PEV charging behavior 128 7.2.4 Simulation approach 130 7.3 Results and discussion 131 7.3.1 User impact 131 7.3.2 Charging behavior 132 7.3.3 PEV hosting capacity 135 7.3.4 Fast charging requirements 137 7.3.5 Peak load 138 7.4 Conclusions 139 8. Summary, conclusions, and future work 141 8.1 Summary & conclusions 141 8.2 Future work 143 Appendix A North-American grid layout 147 Appendix B Availability analysis 149 B.1 Flemish travel behavior data 149 B.2 Commute trips 152 B.3 Other trips 154 Appendix C Fast charging scenario 159 Bibliography 161 Curriculum Vitae 179 List of publications 181 nrpages: 183 status: publishedAbstract
The number of plug-in electric vehicles (PEVs) on the road is growing significantly, which allows to reduce the consumption of greenhouse gas emitting fossil fuels, such as gasoline and diesel. This is due to the increased primary energy efficiency of electrically powered vehicles [...]Abstract
2014 - 2015 One of the mega trends over the past century has been humanity’s move towards cities. Public Administration and Municipalities are facing a challenging task, to harmonize a sustainable urban development offering to people in city the best living conditions. Smart cities are now considered a winning urban strategy able to increase the quality of life by using technology in urban space, both improving the environmental quality and delivering better services to the citizens. Mobility is a key element to support this new approach in the growth of the cities. In fact, transport produces several negative impacts and problems for the quality of life in cities, such as, pollution, traffic and congestion. Therefore, Sustainable Mobility is one of the most promising topics in smart city, as it could produce high benefits for the quality of life of almost all the city stakeholders. The boldest and imminent challenge awaiting mobility in smart cities is the introduction of the electricity as energy vector instead of fossil fuels, concerning both the collective and the private transports. Electric public transport include electric city buses, trolleybuses, trams (or light rail), passenger trains and rapid transit (metro/subways/undergrounds, etc.). Even though railway systems are the most energy efficient than other transport modes, the enhancement of energy efficiency is an important issue to reduce their contributions to climate change further as well as to save and enlarge competition advantages involved. One key means for improving energy efficiency is to deploy advanced systems and innovative technologies. Additionally, electrification of the private road transport has emerged as a trend to support energy efficiency and CO2 emissions reduction targets. According to the International Energy Agency, in order to limit average global temperature increases to 2°C - the critical threshold that scientists say will prevent dangerous climate change -, by 2050, 21% of carbon reductions must come from the transport sector. Full electric vehicles (EVs) use electric motor and battery energy for propulsion, which has higher efficiency and lower operating cost compared to the conventional internal combustion engine vehicle. Today, there are more than 20 models offered by different brands covering different range of sizes, styles, prices and powertrains to suit the wider range of consumers as possible. The continuous development of lithium ion battery and of fast charging technology will be the major facilitators for EVs roll out in the very near future. However, the present EVs industry meets many technical limitations, such as high initial price, long battery recharge time, limited charging facilities and driving range. Although it is desirable a fast development from the start of electric mobility, its impact on the existing power grid must be assessed beforehand to see if it is necessary prior an adjustment of power infrastructure or/and the introduction of new services in the power grid. In fact, the interconnection of EVs on the power grid for charging their batteries potentially introduces negative impacts on grid operation: uncontrolled charging can significantly increase average load in the existing power systems, with problems in terms of reliability and overloads. If uncontrolled EV charging is added to the system, this can have effects both at the distribution and at the generation level. Controlled or smart charging will allow a much greater number of cars in the cities, avoiding local overload and allowing a faster EVs penetration without requiring an imminent improvement of the electricity generating and grid capacity. Smart charging might also allow load balancing both at sub-station and at the grid level, particularly with charging at peak wind supply times. This kind of use of EV battery capacity for storing electric energy may ease the integration of large scale intermittent electricity sources such as renewable energy sources. The proposed PhD Dissertation is developed in the context just described, mainly focusing the attention on the impact that electric mobility will have on the power systems and the effectiveness of solutions aimed to increase the reliability and resilience in the smart grid. In particular, it is addressed a scenario analysis regarding the electric vehicles charging management and some innovative solutions to increase energy efficiency in electrified transport systems. The first chapter emphasizes on the key aspects related to the sustainable mobility in the smart cities of the future. It provides a brief overview on the transport sector energy consumption expected in the next years. In particular, the chapter shows the significant contribution that the electrification of urban transport may provide to the sustainable mobility, and the serious concerns related to its impact on existing power systems. Chapter 2 proposes a solution method for an optimal generation rescheduling and load-shedding (GRLS) problem in microgrids in order to determine a stable equilibrium state following unexpected outages of generation or sudden increase in demand. The chapter mainly focuses on the mathematical formulation of the GRLS problem and the proposed solution algorithm. Finally, simulations results carried out by using a real case study data are presented and discussed. In Chapter 3, a simple and effective methodology is proposed to analyze data acquired during the fulfillment of the COSMO research project, and to identify typical load pattern for the EVs charging. The chapter also presents a novel scheduling problem formulation, flattening the demand load profile and minimizing the EVs charging costs, according to the electricity prices during the day. Finally, some simulations results are discussed, showing the effectiveness of the proposed methodology. Chapter 4 introduces some innovative solutions for energy efficiency in urban railway systems focusing, in particular, on energy storage systems and eco-drive operations in metro networks. The mathematical formulation of these optimization problems and the proposed solution algorithms are illustrated and discussed. The obtained results are part of the activity carried out in the SFERE research project. Finally, Chapter 5 ends the Dissertation with some concluding remarks and further developments of the proposed research activity. [edited by author] Una delle grandi tendenze nel corso del secolo scorso è stata la concentrazione della popolazione nelle città. Attualmente, le Pubbliche Amministrazioni e i Comuni si trovano ad affrontare un compito impegnativo per armonizzare uno sviluppo urbano sostenibile e offrire agli abitanti delle città le migliori condizioni di vita. Le smart cities sono ormai considerate una strategia urbana vincente in grado di aumentare la qualità della vita utilizzando la tecnologia, sia per il miglioramento della qualità ambientale che per fornire servizi migliori ai cittadini. A tale scopo, la mobilità risulta essere un elemento chiave per sostenere questo nuovo approccio nella crescita delle città. Infatti, i sistemi di trasporto urbano producono diversi effetti negativi sulla qualità della vita urbana, come ad esempio, inquinamento, traffico e congestione. Pertanto, la mobilità sostenibile è uno degli argomenti più interessanti per le smart cities, in quanto in grado produrre elevati benefici per la qualità della vita di quasi tutte le parti interessate degli agglomerati urbani. La sfida più audace e imminente per la mobilità nelle smart cities del futuro è l'introduzione dell'elettricità come vettore energetico al posto dei combustibili fossili, per quanto riguarda sia il trasporto collettivo che quello privato. I mezzi per il trasporto pubblico comprendono autobus elettrici, filobus, tram, treni passeggeri e trasporto rapido (metropolitane, etc.). Anche se i sistemi di trasporto su ferro sono più efficienti rispetto ad altri modi di trasporto, l’incremento dell'efficienza energetica è un tema importante per ridurre ulteriormente il loro contributo alle emissioni inquinanti e al consumo di energia. Le più promettenti soluzioni per migliorarne l'efficienza energetica consistono nell’implementazione di sistemi avanzati per il recupero dell’energia di frenata e tecnologie di controllo innovative. D’altro canto, l'elettrificazione del trasporto individuale su strada è emersa come una tendenza finalizzata a sostenere gli obiettivi di efficienza energetica e di riduzione delle emissioni di CO2. Secondo l'Agenzia Internazionale per l'Energia, al fine di limitare, entro il 2050, l'aumento della temperatura media globale a 2 °C - la soglia critica che gli scienziati suggeriscono di non superare per evitare pericolosi cambiamenti climatici -, il 21% delle riduzioni di biossido di carbonio deve provenire dal settore trasporti. I veicoli elettrici (EV) utilizzano un motore elettrico e l'energia accumulata nelle batterie per la propulsione, in modo da avere una maggiore efficienza e minori costi operativi rispetto ai veicoli convenzionali con motore a combustione interna. Oggi, esistono in commercio più di 20 modelli offerti da diverse case produttrici che coprono una ampia gamma di modelli che differiscono per dimensione, stile, prezzo e motorizzazione in modo da soddisfare il maggior numero di consumatori possibile. Il continuo sviluppo delle batterie al litio e delle tecnologie di ricarica rapida saranno i principali fattori abilitanti per la diffusione degli EV in un futuro molto prossimo. Tuttavia, l'attuale industria dei veicoli elettrici incontra molte limitazioni tecnico-economiche, come elevati costi, autonomia e tempi di ricarica della batteria, capillarità delle infrastrutture di ricarica. Sebbene sia auspicabile un rapido sviluppo della mobilità elettrica, il suo impatto sulla rete elettrica esistente deve essere investigato a fondo per verificare la necessità di potenziamenti delle infrastrutture e/o l'introduzione di nuovi servizi nella rete elettrica. Infatti, l'interconnessione dei veicoli elettrici con la rete di distribuzione dell’energia necessaria per la ricarica delle batterie può causare effetti negativi sul normale funzionamento del sistema elettrico: una ricarica degli EV non controllata può aumentare significativamente il carico medio negli impianti esistenti, introducendo problemi di affidabilità e sovraccarico. La ricarica intelligente o controllata degli EV consente, invece, di gestire un numero molto maggiore di autovetture elettriche nelle città, riducendo le possibilità di sovraccarico locale e di velocizzare la penetrazione della mobilità elettrica senza che rendere necessari imminenti potenziamenti dei sistemi di produzione di energia elettrica e incrementi della capacità di rete. La ricarica intelligente, inoltre, può anche influire sul bilanciamento del carico sia a livello della sottostazione elettrica che a livello di rete di distribuzione, in particolare quando si verificano molte sessioni di ricarica nelle ore di punta. Infatti, l’utilizzo della capacità della batteria degli EV per l’accumulo di energia elettrica può facilitare l'integrazione su larga scala delle fonti di energia non programmabili, come quelle rinnovabili. Il lavoro di tesi si sviluppa nel contesto di riferimento appena descritto, focalizzando l'attenzione soprattutto sull'impatto che la mobilità elettrica ha sui sistemi elettrici e sull'efficacia di nuove soluzioni finalizzate all’incremento dell'affidabilità nelle smart grids. In particolare, viene proposta un'analisi di scenario per quanto riguarda la gestione intelligente delle ricariche dei veicoli elettrici e alcune soluzioni innovative per aumentare l'efficienza energetica nei sistemi di trasporto elettrificati. Il primo capitolo sottolinea gli aspetti chiave relativi alla mobilità sostenibile nelle smart cities del futuro e fornisce una breve panoramica sul consumo energetico del settore trasporti previsto nel prossimo futuro. In particolare, vengono evidenziate da un lato il significativo contributo che l'elettrificazione dei trasporti urbani può fornire alla causa della mobilità sostenibile, e dall’altro, le gravi preoccupazioni legate all’impatto sui sistemi elettrici esistenti di un notevole incremento della domanda. Il Capitolo 2 propone un metodo per la soluzione del problema congiunto di scheduling dei generatori e load shedding (GRLS) all’interno di microgrids portando in conto l’incertezza sia sulla domanda che lato generazione. Il fine è determinare un nuovo stato di equilibrio stabile in seguito a guasti, riduzione della generazione da fonte rinnovabile o improvviso aumento della domanda. Il capitolo si concentra principalmente sulla formulazione matematica del problema GRLS e sull'algoritmo di soluzione proposto. Infine, sono presentati e commentati i risultati di simulazione basati su un caso studio reale. Nel Capitolo 3, è proposta una metodologia semplice ed efficace per identificare profili di carico tipico relativi alla ricarica di veicoli elettrici: in particolare, l’analisi condotta si basa sull’analisi dei dati acquisiti durante lo svolgimento del progetto di ricerca COSMO. Il capitolo, inoltre, introduce una formulazione matematica del problema dello scheduling delle ricariche dei veicoli elettrici, che garantisce un appiattimento del profilo di carico e riduce allo stesso tempo il costo della ricarica per gli utenti. Infine, sono commentati i risultati delle simulazioni eseguite dimostrando l'efficacia della metodologia proposta. Il Capitolo 4 introduce alcune soluzioni innovative per l'efficienza energetica nei sistemi di trasporto urbani: l’attenzione viene posta, in particolare, sui sistemi di accumulo dell’energia e sulla condotta di guida Eco-Drive in reti metropolitane. In dettaglio, nel capitolo, vengono introdotti e commentati la formulazione matematica dei problemi di ottimizzazione proposti e i rispettivi algoritmi di soluzione. I risultati ottenuti fanno parte delle attività svolte nell’ambito del progetto di ricerca SFERE. Infine, il Capitolo 5 conclude la tesi con alcune osservazioni finali e con i possibili sviluppi dell'attività di ricerca proposta. [a cura dell'autore] XIV n.s.Abstract
2014 - 2015 One of the mega trends over the past century has been humanity’s move towards cities. Public Administration and Municipalities are facing a challenging task, to harmonize a sustainable urban development offering to people in city the best living conditions. Smart cities [...]Abstract
The electrical grid is a huge and complex system which represents a critical infrastructure. Due to this fact, the electric power industry has traditionally adopted a conservative attitude regarding changes. As a result of that, the electrical grid has experienced very few breakthroughs for decades and currently is not prepared to face novel challenges, such as properly integrating DERs (Distributed Energy Resources) or proactively controlling the energy demand by means of the so-called DR (Demand Response) programs, which mainly derive from nowadays society concerns on global warming and climate change. Upgrading traditional electrical grid to the so-called Smart Grid represents one of the most complex engineering projects ever and will certainly drive the next wave of research and innovation in both the energy and the ICT (Information and Communications Technology) sectors. The road towards the Smart Grid will mean an unprecedented revolution especially at the power distribution and customer domains, since the unpredictable and uncontrollable nature of renewables will impose the coordination of generation and consumption points in almost real time. M2M (Machine-to-Machine) communications allow networked devices to communicate between them without further human intervention. What in the very beginning seemed to be a tailored solution for telemetry applications, has become a communications paradigm itself, addressing the myriad of applications existing and yet to be in the wide context of the Internet of Things. As a matter of fact, M2M communications represent one of the main pillars of the Smart Grid in that they will enable the bidirectional real-time exchange of information between the consumption and generation facilities to be monitored and controlled, and the information systems where the optimization processes run. There is a plethora of communications technologies and protocols available within the scope of M2M communications for the Smart Grid. Hence, research is needed in two directions. On the one side, it is required to evaluate how different communications architectures and technologies meet the specific requirements of the Smart Grid before undertaking the important investments needed to deploy this kind of infrastructures on a large scale. On the other side, it is crucial to develop common data models which serve as reference to future horizontal or wide scope protocols which expand across different domains or areas. This thesis aims to tackle these issues. The main goal of the thesis is to contribute to the area of M2M communications architectures tailored to the power distribution and customer domains of the Smart Grid. In order to achieve this overall objective, first we carry out a survey on the most relevant standardization activities developed in parallel to this thesis and on the most outstanding technological and research trends within the Smart Grid area, identifying gaps and challenges. Second, we propose a novel M2M communications architecture to support energy efficiency and optimum coordination of DER (Distributed Energy Resources) within the so-called energy-positive neighborhoods, which are neighborhoods which ensure a substantial part of their consumption by local generation based on renewables. The proposed architecture comprises three network segments, for the sake of flexibility and scalability, and combines different communications technologies to meet the specific communications requirements of each of them. Next, we model formally the domain of knowledge of energy efficiency platforms for energy-positive neighborhoods by means of an ontology developed in OWL (Ontology Web Language), with the aim that it becomes a reference data model for the application of M2M communications to this context. Thus, this ontology has been made public through the EC (European Commission) eeBuildings Data Model community, so that other researches can re-use it and extend it. We also propose a methodology that can be applied, in general, to characterize any communications overlay deployed on top of an infrastructure devoted to any purpose. Following this methodology, we model the traffic of the proposed M2M communications architecture in realistic large-scale scenarios. The main goal of this model is to ensure that potential works based on it actually mean and bring value to the interested parties. Although the model is tailored to the Portuguese power distribution grid, since it is based on actual data provided by EDP (Energias de Portugal), it can be easily adapted to other scenarios by suitably tuning the appropriate parameters. Taking this model as reference, we finally evaluate the core of the proposed M2M communications architecture twofold. On the one side, we analyze the impact of using IPSec (Internet Protocol Security) or TLS/SSL (Transport Layer Security/Secure Socket Layer) as VPN (Virtual Private Network) technologies on the operational costs of a potential energy efficiency platform which relies on the proposed M2M communications architecture. To the author’s best knowledge, no similar studies are available in the state of the art. The main conclusion of this analysis is that using TLS/SSL along with data aggregation is the best option to minimize operational costs at neighborhood level. On the other side, we evaluate by means of simulations the performance of IEEE 802.11b, using as metric the goodput (i.e., throughput at the application layer), and GPRS (General Packet Radio Service), using as metric the transmission time. The first conclusion of these simulations is along the line that IEEE 802.11b meets the requirements in terms of goodput of the NAN (Neighborhood Area Networks), which is of special interest to the Smart Grid community taking into account the low cost and wide adoption of this technology. The second conclusion of such simulations is that GPRS meets the requirements in terms of bandwidth of the backhaul network, thus confirming that it represents a very attractive technology considering that it is the most mature and widely deployed cellular technology in Europe. Presidente: Jürgen Jähnert; Vocal: David Fernández Cambronero; Secretario: Francisco Valera PintorAbstract
The electrical grid is a huge and complex system which represents a critical infrastructure. Due to this fact, the electric power industry has traditionally adopted a conservative attitude regarding changes. As a result of that, the electrical grid has experienced very few breakthroughs [...]Abstract
This paper proposes an integrated system for traction and battery charging of electric vehicles (EVs) with universal interface to the power grid. In the proposed system, the power electronics converters comprising the traction drive system are also used for the battery charging system, reducing the required hardware, meaning the integrated characteristic of the system. Besides, this interface is universal, since it can be performed with the three main types of power grids, namely: (1) Single-phase AC power grids; (2) Three-phase AC power grids; (3) DC power grids. In these three types of interfaces with the power grid, as well as in the traction drive operation mode, bidirectional operation is possible, framing the integration of this system into an EV in the context of smart grids. Moreover, the proposed system endows an EV with an on-board fast battery charger, whose operation allows either fast or slow battery charging. The main contributes of the proposed system are detailed in the paper, and simulation results are presented in order to attain the feasibility of the proposed system. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT -Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013. This work has been supported by FCT within the Project Scope DAIPESEV - Development of Advanced Integrated Power Electronic Systems for Electric Vehicles: PTDC/EEI-EEE/30382/2017. Mr. Tiago Sousa is supported by the doctoral scholarship SFRH/BD/134353/2017 granted by the Portuguese FCT agency. This work is part of the FCT project 0302836 NORTE-01-0145-FEDER-030283. Document type: Conference objectAbstract
This paper proposes an integrated system for traction and battery charging of electric vehicles (EVs) with universal interface to the power grid. In the proposed system, the power electronics converters comprising the traction drive system are also used for the battery charging system, [...]