Recent years have seen a growing tendency that a large number of generators are connected to the electricity distribution networks, including renewables such as solar photovoltaics, wind turbines and biomass-fired power plants. Meanwhile, on the demand side, there are also some new types of electric loads being connected at increasing rates, with the most important of them being the electric vehicles (EVs). Uncertainties both from generation and consumption of electricity mentioned above are thereby being introduced, making the management of the system more challenging. With the proportion of electric vehicle ownership rapidly increasing, uncontrolled charging of large populations may bring about power system issues such as increased peak demand and voltage variations, while at the same time the cost of electricity generation, as well as the resulting Greenhouse Gases (GHG) emissions, will also rise. The work reported in this PhD Thesis aims to provide solutions to the three significant challenges related to EV integration, namely voltage regulation, generation cost minimisation and GHG emissions reduction. A novel, high-resolution, bottom-up probabilistic EV charging demand model was developed, that uses data from the UK Time Use Survey and the National Travel Survey to synthesise realistic EV charging time series based on user activity patterns. Coupled with manufacturers' data for representative EV models, the developed probabilistic model converts single user activity profiles into electrical demand, which can then be aggregated to simulate larger numbers at a neighbourhood, city or regional level. The EV charging demand model has been integrated into a domestic electrical demand model previously developed by researchers in our group at the University of Edinburgh. The integrated model is used to show how demand management can be used to assist voltage regulation in the distribution system. The node voltage sensitivity method is used to optimise the planning of EV charging based on the influence that every EV charger has on the network depending on their point of connection. The model and the charging strategy were tested on a realistic "highly urban" low voltage network and the results obtained show that voltage fluctuation due to the high percentage of EV ownership (and charging) can be significantly and maintained within the statutory range during a full 24-hour cycle of operation. The developed model is also used to assess the generation cost as well as the environmental impact, in terms of GHG emissions, as a result of EV charging, and an optimisation algorithm has been developed that in combination with domestic demand management, minimises the incurred costs and GHG emissions. The obtained results indicate that although the increased population of EVs in distribution networks will stress the system and have adverse economic and environmental effects, these may be minimised with careful off-line planning.

O objetivo deste trabalho é avaliar qual seria o impacto da inserção dos veículos elétricos nos sistemas de distribuição de energia elétrica de duas distribuidoras brasileiras, a EDP Bandeirante e EDP ESCELSA. Como esta tecnologia ainda não se encontra em utilização no Brasil, será adotada uma abordagem prospectiva, de modo a projetar o crescimento da frota de veículos elétricos até o ano de 2020. Para que se possa simular em uma sub estação, qual será o impacto da adoção desta tecnologia. Utilizando-se das projeções de crescimento da frota, também serão quantificados o impacto na matriz energética nacional e nas emissões de gases do efeito estufa. / This work, aims to evaluate the impact of the electric vehicles insertion on two power distribution utilities, EDP Bandeirante and EDP ESCELSA. How the electric vehicles aren´t a reality on Brazil, an prospective approach will be adopted, to project the growth of the electric vehicles fleet until the 2020 year, so that can be simulated in one substation, the impact that would be caused by the adoption of this technology. Using these projections, the impact on Brazilian energetic matrix, and the greenhouse gas emissions will be calculated to.

The transportation sector is a largest emitter of greenhouse gases in the U.S., accounting for 28.6% of all 2016 emissions, the majority of which come from the passenger vehicle fleet [1,2]. One major technology that is being investigated by researchers, planners, and policy makers to help lower the emissions from the transportation sector is the plug-in electric vehicle (PEV). The focus of this work is to investigate and model the impacts of increased levels of PEVs on the regional electric power grid and on the net change in CO2 emissions due to the decrease tailpipe emissions and the increase in electricity generation under current emissions caps. The study scope includes all of New England and New York state, modeled as one system of electricity supply and demand, which includes the estimated 2030 baseline demand and the cur- rent generation capacity plus increased renewable capacity to meet state Renewable Portfolio Standard targets for 2030. The models presented here include fully electric vehicles and plug-in hybrids, public charging infrastructure scenarios, hourly charging demand, solar and wind generation and capacity factors, and real-world travel derived from the 2016-2017 National Household Travel Survey. We make certain assumptions, informed by the literature, with the goal of creating a modeling methodology to improve the estimation of hourly PEV charging demand for input into regional electric sector dispatch models. The methodology included novel stochastic processes, considered seasonal and weekday versus weekend differences in travel, and did not force the PEV battery state-of-charge to be full at any specific time of day. The results support the need for public charging infrastructure, specifically at workplaces, with the “work” infrastructure scenario shifting more of the unmanaged charging demand to daylight hours when solar generation could be utilized. Workplace charging accounted for 40% of all non-home charging demand in the scenario where charging infrastructure was “universally” available. Under the increased renewable fuel portfolio, the reduction in average CO2 emissions ranged from 90 to 92% for the vehicles converted from ICEV to PEV. The total emissions reduced for 15% PEV penetration and universally available charging infrastructure was 5.85 million metric tons, 5.27% of system-wide emissions. The results support the premise of plug-in electric vehicles being an important strategy for the reduction of CO2 emissions in our study region. Future investigation into the extent of reductions possible with both the optimization of charging schedules through pricing or other mechanisms and the modeling of grid level energy storage is warranted. Additional model development should include a sensitivity analysis of the PEV charging demand model parameters, and better data on the charging behavior of PEV owners as they continue to penetrate the market at higher rates.

Electric vehicles (EVs) offer an exciting opportunity in China both in terms of the potential to build a domestic manufacturing base and the potential to create a strong domestic market for the product. The Chinese nation stands to benefit from both supply-side and demand-side promotion due to the economic stimulus from EV manufacturing and export, the environmental benefits of reduced air pollution and reduced greenhouse gas emissions, and the energy security benefits of transitioning away from foreign oil dependence. The Chinese have several advantages when it comes to stimulating EV industry development and EV deployment, including: leadership in battery technology, great potential for cost competitiveness, an enormous and emerging number of new car buyers, and high level government support. Yet a number of challenges must be taken into account as well, including: shortfalls in overall automobile R&D spending, consumer concerns about Chinese cars’ safety and reliability, enhancing the appeal of the Chinese brand, and heavy national infrastructure demands. This paper will seek to examine the opportunities and challenges associated with EV deployment in China and identify industry actions and policy measures to facilitate the process.

The Personal Transportation System safeguards peoples’ cultural understanding of freedom: to move individually without being dependent on others. However, the increasing number of private vehicles driven on fossil fuels contributes to unsustainability and one of the most urgent issues, climate change. The authors explored electric vehicles as an alternative to fossil fuel driven vehicles as a way of moving strategically towards sustainability in the Personal Transportation System. In order to increase demand of electric vehicles, barriers need to be overcome. The authors identified perceived barriers and enablers through literature review, interviews with automobile dealers and other stakeholders of the EV sector in Southeast Sweden, as well as through an electronic survey of individuals living in this region. The outcome of the thesis is a pilot strategy using behavior change tools from Community-Based Social Marketing in order to address the perceived barriers and enablers on the demand side of the electric vehicle market. With highly positive attitudes towards electric vehicles in Southeast Sweden, the strategy may be successful in the region; however, it needs to be combined with further measures on the supply side of the market which cannot be addressed with behavior change tools.

The adoption of plug-in electric vehicles (PEV) requires research for models and algorithms tracing the vehicle assignment incorporating PEVs in the transportation network so that the traffic pattern can be more precisely and accurately predicted. To attain this goal, this dissertation is concerned with developing new formulations for modeling travelling behavior of electric vehicle drivers in a mixed flow traffic network environment. Much of the work in this dissertation is motivated by the special features of PEVs (such as range limitation, requirement of long electricity-recharging time, etc.), and the lack of tools of understanding PEV drivers traveling behavior and learning the impacts of charging infrastructure supply and policy on the network traffic pattern. The essential issues addressed in this dissertation are: (1) modeling the spatial choice behavior of electric vehicle drivers and analyzing the impacts from electricity-charging speed and price; (2) modeling the temporal and spatial choices behavior of electric vehicle drivers and analyzing the impacts of electric vehicle range and penetration rate; (3) and designing the optimal charging infrastructure investments and policy in the perspective of revenue management. Stochastic traffic assignment that can take into account for charging cost and charging time is first examined. Further, a quasi-dynamic stochastic user equilibrium model for combined choices of departure time, duration of stay and route, which integrates the nested-Logit discrete choice model, is formulated as a variational inequality problem. An extension from this equilibrium model is the network design model to determine an optimal charging infrastructure capacity and pricing. The objective is to maximize revenue subject to equilibrium constraints that explicitly consider the electric vehicle drivers’ combined choices behavior. The proposed models and algorithms are tested on small to middle size transportation networks. Extensive numerical experiments are conducted to assess the performance of the models. The research results contain the author’s initiative insights of network equilibrium models accounting for PEVs impacted by different scenarios of charging infrastructure supply, electric vehicles characteristics and penetration rates. The analytical tools developed in this dissertation, and the resulting insights obtained should offer an important first step to areas of travel demand modeling and policy making incorporating PEVs. / text

Τα τελευταία 35 χρόνια έχει προκύψει ένα ενεργειακό πρόβλημα το οποίο μας επιβάλει να αλλάξουμε την ενεργειακή μας αντίληψη. Το πετρέλαιο αλλά και άλλα ορυκτά καύσιμα έχουν πεπερασμένα αποθέματα και η χρήση τους επιβαρύνει το περιβάλλον. Επίσης γεωπολιτικά συμφέροντα δεν επιτρέπουν την ανεμπόδιστη διανομή του. Μέσα σε αυτό το κλίμα της ενεργειακής απεξάρτησης από τα ορυκτά καύσιμα αναπτύσσονται τα τελευταία χρόνια τα υβριδικά οχήματα. Τα ηλεκτρικά υβριδικά οχήματα είναι ένα μεταβατικό στάδιο από την πετρελαιοκίνηση στην εξ’ ολοκλήρου κίνηση μέσω ηλεκτρισμού από ενεργειακές κυψέλες. Αποτελούνται από έναν συμβατικό κινητήρα εσωτερικής καύσης και μια ηλεκτρική μηχανή, η οποία τροφοδοτείται από συσσωρευτές. Τα υβριδικά οχήματα χωρίζονται σε διάφορες κατηγορίες ανάλογα με τις τεχνολογίες υβριδοποίησης που διαθέτουν και την διάταξη του ηλεκτρομηχανολογικού τους συστήματος. Στόχος της παρούσας διπλωματικής εργασίας (η οποία είναι η συνέχεια δυο προηγούμενων) είναι η προσπάθεια κατασκευής ενός υβριδικού αυτοκινήτου. Για να γίνει αυτό εφικτό απαιτούνται, ένα όχημα το οποίο να μπορεί να δεχθεί εύκολα μηχανολογικές μετατροπές, ένας ηλεκτρικός κινητήρας και συσσωρευτές. Ο ηλεκτρικός κινητήρας ελέγχεται από έναν αντιστροφέα. Ο αντιστροφέας είναι μια ηλεκτρική συσκευή η οποία μετατρέπει το συνεχές ρεύμα των συσσωρευτών σε εναλλασσόμενο. Βασικό κομμάτι του αντιστροφέα είναι η λογική παλμοδότησής του. Ο αντιστροφέας που κατασκευάστηκε χρησιμοποιεί τον άμεσο έλεγχο ροπής, ο οποίος είναι ένα είδος άμεσου διανυσματικού ελέγχου που χρησιμοποιεί τον μετασχηματισμό Park. / Τα τελευταία 35 χρόνια έχει προκύψει ένα ενεργειακό πρόβλημα το οποίο μας επιβάλει να αλλάξουμε την ενεργειακή μας αντίληψη. Το πετρέλαιο αλλά και άλλα ορυκτά καύσιμα έχουν πεπερασμένα αποθέματα και η χρήση τους επιβαρύνει το περιβάλλον. Επίσης γεωπολιτικά συμφέροντα δεν επιτρέπουν την ανεμπόδιστη διανομή του. Μέσα σε αυτό το κλίμα της ενεργειακής απεξάρτησης από τα ορυκτά καύσιμα αναπτύσσονται τα τελευταία χρόνια τα υβριδικά οχήματα. Τα ηλεκτρικά υβριδικά οχήματα είναι ένα μεταβατικό στάδιο από την πετρελαιοκίνηση στην εξ’ ολοκλήρου κίνηση μέσω ηλεκτρισμού από ενεργειακές κυψέλες. Αποτελούνται από έναν συμβατικό κινητήρα εσωτερικής καύσης και μια ηλεκτρική μηχανή, η οποία τροφοδοτείται από συσσωρευτές. Τα υβριδικά οχήματα χωρίζονται σε διάφορες κατηγορίες ανάλογα με τις τεχνολογίες υβριδοποίησης που διαθέτουν και την διάταξη του ηλεκτρομηχανολογικού τους συστήματος. Στόχος της παρούσας διπλωματικής εργασίας (η οποία είναι η συνέχεια δυο προηγούμενων) είναι η προσπάθεια κατασκευής ενός υβριδικού αυτοκινήτου. Για να γίνει αυτό εφικτό απαιτούνται, ένα όχημα το οποίο να μπορεί να δεχθεί εύκολα μηχανολογικές μετατροπές, ένας ηλεκτρικός κινητήρας και συσσωρευτές. Ο ηλεκτρικός κινητήρας ελέγχεται από έναν αντιστροφέα. Ο αντιστροφέας είναι μια ηλεκτρική συσκευή η οποία μετατρέπει το συνεχές ρεύμα των συσσωρευτών σε εναλλασσόμενο. Βασικό κομμάτι του αντιστροφέα είναι η λογική παλμοδότησής του. Ο αντιστροφέας που κατασκευάστηκε χρησιμοποιεί τον άμεσο έλεγχο ροπής, ο οποίος είναι ένα είδος άμεσου διανυσματικού ελέγχου που χρησιμοποιεί τον μετασχηματισμό Park.

No description available.

A series hybrid electric vehicle is a vehicle that is powered by both an engine and a battery pack. An electric motor provides all of the mechanical motive power to the transmission. Engine power is decoupled from the transmission by converting engine power into electricity which powers the electric motor. The mechanical decoupling of the engine from the transmission allows the engine to be run at any operating point (including off) during vehicle operation while the battery back supplies or consumes the remaining power. Therefore, the engine can be operated at its most efficient operating point or in a high-efficiency operating region. The first objective of this research is to develop a dynamic model of a series hybrid diesel-electric powertrain for implementation in Simulink. The vehicle of interest is a John Deere M-Gator utility vehicle. This model serves primarily to test energy management strategies, but it can also be used for component sizing given known load profiles for a vehicle. The second objective of this research is to develop and implement multiple energy management strategies of varying complexity from simple thermostat control to an optimal control law derived using dynamic programming. These energy management strategies are then tested and compared over the criteria of overall fuel efficiency, power availability, battery life, and complexity of implementation. Complexity of implementation is a critical metric for control designers and project managers. The results show that simple point-based control logic can improve upon thermostat control if engine efficiency maps are known. All control method results depend on the load profile being used for a specific application.

Two studies are presented quantifying the impact of plug-in hybrid vehicles (PHEVs) on power systems. The first study quantifies this impact in terms of (a) primary fuel utilization shifts, (b) pollution shifts, and (c) total cost for consumers. The second study quantifies this impact on distribution transformers. In the first study vehicle and power system simulations are used to compute the expected power system fuels utilized to meet a projected level of power demand. The projected electric power demand includes business as usual electric load and random PHEV charging electric load. In the second study the impact on distribution transformers is quantified through a loss of life calculation. The loss of life calculation is based on distribution transformer hot-spot temperature. The hot-spot temperature is estimated using an electro-thermal distribution transformer model and is a function of the transformer currents. The transformer currents are computed using a center-tapped single phase transformer model. Random business as usual and PHEV charging electric loading is assumed.