New Plug-in Electric Vehicles Charging Models Based on Demand Response Programs for System Reliability Improvement

Recent years have seen a dramatic worldwide increase in the use of plug-in electric vehicles (PEVs). Their tremendous social, economic, and environmental benefits have made PEVs highly promising alternatives to conventional automobiles powered by internal combustion engines. Continuing government initiatives and technological advances are expected to lead to an even more rapid rise in the PEV penetration in the near future. Despite the important advantages of PEVs, however, their integration also raises new concerns and presents a number of special difficulties to the power system reliability. There is in fact recognized need to address the challenges imposed by PEV charging loads, to study their adverse impact on overall system reliability, and to determine whether existing generation capacity is sufficient for accommodating these new types of loads with their high penetration levels and different uncertainty characteristics. This thesis presents a comprehensive reliability framework for incorporating different PEV charging load models into the evaluation of generation adequacy. The proposed framework comprises special treatment and innovative models to achieve an accurate determination of the impact of PEV load models on reliability. First, a goodness-of-fit statistical analysis determines the probability distribution functions (PDFs) that best reflect the main characteristics of driver behaviour. Second, robust and detailed stochastic methods are developed for modeling different charging scenarios (uncontrolled charging and charging based on TOU pricing). These models are based on the use of a Monte Carlo simulation in conjunction with the fitted PDFs to generate and assess a large number of possible scenarios while handling the uncertainties associated with driver behaviour, penetration levels, charging levels, battery capacities, and customer response to TOU pricing. When PEV charging loads become a significant factor in power systems and PEV charging times are uncontrolled, they are expected to cause a severe risk to system reliability, especially at higher PEV penetration and charging levels. Solutions that maintain an acceptable level of system reliability and ensure adequate generation capacity must therefore be found. Proposed in this thesis is novel reliability-based frameworks for the application of different DR programs for use with PEV charging loads. The proposed frameworks are in line with the recent trend toward investigating solutions at the demand side and exploiting the existing flexibility to help improve reliability. The first framework is proposed for incorporating PEV charging loads to respond to dynamic critical events. The framework involves two models: the first determines the time and demand for critical system events, when system supply facilities are unable to meet PEV loads, and the second assesses the feasibility of PEV owner response to critical events. The second framework is proposed for designing time-of-use (TOU) schedules to mitigate the impact of uncontrolled PEV charging load. The proposed framework involves the use of different stochastics simulation models, visualization approaches, and expert rules that help to arrive at proper TOU schedules for PEV charging load

Exploring the Role of Perceived Range Anxiety in Adoption Behavior of Plug-in Electric Vehicles

A sustainable solution to negative externalities imposed by road transportation is replacing internal combustion vehicles with electric vehicles (EVs), especially plug-in EV (PEV) encompassing plug-in hybrid EV (PHEV) and battery EV (BEV). However, EV market share is still low and is forecast to remain low and uncertain. This shows a research need for an in-depth understanding of EV adoption behavior with a focus on one of the main barriers to the mass EV adoption, which is the limited electric driving range. The present study extends the existing literature in two directions; First, the influence of the psychological aspect of driving range, which is referred to as range anxiety, is explored on EV adoption behavior by presenting a nested logit (NL) model with a latent construct. Second, the two-level NL model captures individuals' decision on EV adoption behavior distinguished by vehicle transaction type and EV type, where the upper level yields the vehicle transaction type selected from the set of alternatives including no-transaction, sell, trade, and add. The fuel type of the vehicles decided to be acquired, either as traded-for or added vehicles, is simultaneously determined at the lower level from a set including conventional vehicle, hybrid EV, PHEV, and BEV. The model is empirically estimated using a stated preferences dataset collected in the State of California. A notable finding is that anxiety about driving range influences the preference for BEV, especially as an added than traded-for vehicle, but not the decision on PHEV adoption.Comment: 27 pages, 3 figures, 5 table

Exploring the Role of Perceived Range Anxiety in Adoption Behavior of Plugin Electric Vehicles

A sustainable solution to negative externalities imposed by road transportation is replacing internal combustion vehicles with electric vehicles (EVs), especially plug-in EV (PEV) encompassing plugin hybrid EV (PHEV) and battery EV (BEV). However, EV market share is still low and is forecast to remain low and uncertain. This shows a research need for an in-depth understanding of EV adoption behavior with a focus on one of the main barriers to the mass EV adoption, which is the limited electric driving range. The present study extends the existing literature in two directions; First, the influence of the psychological aspect of driving range, which is referred to as “range anxiety”, is explored on EV adoption behavior by presenting a nested logit (NL) model with a latent construct. Second, the two-level NL model captures individuals’ decision on EV adoption behavior distinguished by vehicle transaction type and EV type, where the upper level yields the vehicle transaction type selected from the set of alternatives including no-transaction, sell, trade, and add. The fuel type of the vehicles decided to be acquired, either as tradedfor or added vehicles, is simultaneously determined at the lower level from a set including conventional vehicle, hybrid EV, PHEV, and BEV. The model is empirically estimated using a stated preferences dataset collected in the State of California. A notable finding is that anxiety about driving range influences the preference for BEV, especially as an added than traded-for vehicle, but not the decision on PHEV adoption

Os desafios do mercado automóvel atual: extensões descendentes de marcas premium e a adoção de veículos elétricos

The automotive sector is one of the most competitive and complex markets in the world. The dynamics of this context push manufacturers into implementing downward brand extensions, blurring the differences between value and premium brands. Through an experimental approach, the main study aimed to understand how consumers evaluate a downward brand line extension in the European premium automotive market. Results indicated that the extension purchase intention is dependent of the consumer’s extension attitude, the extension perceived fit, and the status-seeking behaviour, but not of the parent brand attitude, the ownership status, or the innovativeness. The second purpose to the study was to investigate the consumer attitudes towards the adoption of electrical vehicles (EVs) and also to analyse the influence of consumer attitudes on EV adoption in an EV secondary market context. The study relied mainly on in-depth interviews of drivers of conventional vehicles, complemented, in the first part, with quantitative data collected by a survey on drivers’ attitudes. Results suggest that the preference between battery charging point types (personal, workplace, public) is important and dependent on the driver context. The existence of a second conventional car and an advanced range management system were also noted as potentially important. A secondary market of EVs was also suggested as potentially viable, if certain conditions are met.O setor automóvel é um dos mercados mais competitivos e complexos no mundo. As forças dinâmicas que caracterizam este contexto levam os fabricantes a implementar extensões descendentes da marca, reduzindo as diferenças entre as marcas massificadas e marcas premium. Através do método experimental, o estudo principal procurou perceber como os consumidores avaliam extensões descendentes de marcas premium no mercado automóvel Europeu. Os resultados indicaram que a intenção de compra de uma extensão é dependente da atitude do consumidor face à extensão, da semelhança percebida da extensão face à marca mãe, e da procura de prestígio por parte do consumidor, mas não é dependente da atitude do consumidor à marca mãe, do efeito de propriedade, ou da innovativeness. O segundo estudo teve por objetivo investigar as atitudes dos consumidores face à adoção de veículos elétricos, e ainda a aceitação dos consumidores ao mercado secundário de veículos elétricos. O estudo utilizou fundamentalmente entrevistas em profundidade a condutores de veículos convencionais, complementadas, numa primeira parte, com dados quantitativos recolhidos por inquérito sobre as perceções dos consumidores de automóveis. Os resultados sugerem que a preferência entre os tipos de estações de carregamento de baterias (residencial, local de trabalho, pública) é importante e dependente do contexto do consumidor. A existência de um segundo carro convencional e um sistema de gestão de viagem avançado também foram notadas como potencialmente importantes. Foi ainda sugerido que um mercado secundário de veículos elétricos poderá ser viável, caso sejam garantidas certas condições.Programa Doutoral em Marketing e Estratégi

A literacy model for sustainable avitourism

Avitourism (birding) in South Africa, with remarkable birdlife, provides economic, social and conservation opportunities. Globally, bird species are decreasing rapidly due to environmental degradation and climate change. The dependence of avitourism on natural resources is undisputable, urging further research. Avitourism research is embryonic compared to higher-order tourism markets (i.e. naturebased) and under-researched in the southern hemisphere. Despite increased international scholarship, substantial knowledge gaps remain regarding strategies to enhance sustainable avitourism. Education, encouraging changes in environmental behaviour, is essential to solve environmental problems. The current day learners influence the future state of the natural environment and consequently the sustainability of avitourism in South Africa. The research therefore aimed to develop a literacy model for sustainable avitourism aimed at secondary school learners in Gauteng (South Africa). In phase 1 of the methodological procedure, mechanisms facilitating behavioural change towards nature were explored. A conceptual literacy framework for sustainable avitourism was developed in phase 2 (theoretical contribution). Phase 3, consisted empirical research. Multi-stage sampling was used to collect primary data by distributing questionnaires at 17 purposively selected secondary schools in Gauteng from July to October 2014. The data were obtained from n = 5 488 secondary school learners (aged 13–17). Descriptive statistics provided insight into ‘environmental and avitourism literacy’ of the learners. Exploratory- and confirmatory factor analyses (EFA; CFA) and structural equation modelling (SEM) were employed to test the conceptual literacy framework. Obtaining the primary objective, a literacy model for sustainable avitourism was developed and confirmed (empirical contribution). Critical paths were identified in the model to enhance the likelihood of behavioural change. The literacy model could be useful for environmental education and avitourism roleplayers, assisting in curriculum development and evaluation (practical contribution). This model could also be applied to other educational contexts, including art and music. Bird education teaches a love for birds and nature, leading to conservation and sustained birdlife, to ensure avitourism attractions in the future. The development of sustainable avitourism intervention programmes is suggested for further research. Longitudinal research could evaluate the effects of the intervention programmes.Ultimately, the learners of today are the responsible citizens and tourists of tomorrow.Abstract in English, Sesotho and AfrikaansTransport, Logistics and TourismD.Phil. (Management Studies

Towards Sustainable Transport and Mobility

Small island states are one of the most affected areas by sea-level rise, and sustainable transport development is crucial to their transition towards resiliency. However, their special spatial situations, insularity, geographic remoteness, small populations, and small economies resulted in high transport costs and car dependencies. The book moves away from the conventional focus on urban areas in the Global North and tourism. It gives a different perspective on sustainable transport, travelling, and commuting in the Caribbean and Europe. The authors provide research-based insights and show the state-of-the-art and future approaches for policy-makers, academics, and practitioners. Even beyond small island state research, the book offers an innovative outlook

A Longer-run Perspective on Fiscal Sustainability

This paper investigates the sustainability of fiscal policy in a set of 19 countries by taking a longer-run secular perspective over the period 1880-2009. Via a systematic analysis of the stationarity properties of the first-differenced level of government debt, and disentangling the components of the debt series using Structural Time Series Models, we are able to conclude that the solvency condition would be satisfied in mostly all cases since non-stationarity can be rejected, and, therefore, longer-run fiscal sustainability cannot be rejected (Japan and Spain can be exceptions). The same would be true for the panel sample analysis.fiscal sustainability, government debt, unit roots, breaks, structural time series models Classification-C23, E62, H62

Efficient operation of recharging infrastructure for the accommodation of electric vehicles: a demand driven approach

Large deployment and adoption of electric vehicles in the forthcoming years can have significant environmental impact, like mitigation of climate change and reduction of traffic-induced air pollutants. At the same time, it can strain power network operations, demanding effective load management strategies to deal with induced charging demand. One of the biggest challenges is the complexity that electric vehicle (EV) recharging adds to the power system and the inability of the existing grid to cope with the extra burden. Charging coordination should provide individual EV drivers with their requested energy amount and at the same time, it should optimise the allocation of charging events in order to avoid disruptions at the electricity distribution level. This problem could be solved with the introduction of an intermediate agent, known as the aggregator or the charging service provider (CSP). Considering out-of-home charging infrastructure, an additional role for the CSP would be to maximise revenue for parking operators. This thesis contributes to the wider literature of electro-mobility and its effects on power networks with the introduction of a choice-based revenue management method. This approach explicitly treats charging demand since it allows the integration of a decentralised control method with a discrete choice model that captures the preferences of EV drivers. The sensitivities to the joint charging/parking attributes that characterise the demand side have been estimated with EV-PLACE, an online administered stated preference survey. The choice-modelling framework assesses simultaneously out-of-home charging behaviour with scheduling and parking decisions. Also, survey participants are presented with objective probabilities for fluctuations in future prices so that their response to dynamic pricing is investigated. Empirical estimates provide insights into the value that individuals place to the various attributes of the services that are offered by the CSP. The optimisation of operations for recharging infrastructure is evaluated with SOCSim, a micro-simulation framework that is based on activity patterns of London residents. Sensitivity analyses are performed to examine the structural properties of the model and its benefits compared to an uncontrolled scenario are highlighted. The application proposed in this research is practice-ready and recommendations are given to CSPs for its full-scale implementation.Open Acces

Transient engine model for calibration using two-stage regression approach

Engine mapping is the process of empirically modelling engine behaviour as a function of adjustable engine parameters, predicting the output of the engine. The aim is to calibrate the electronic engine controller to meet decreasing emission requirements and increasing fuel economy demands. Modern engines have an increasing number of control parameters that are having a dramatic impact on time and e ort required to obtain optimal engine calibrations. These are further complicated due to transient engine operating mode. A new model-based transient calibration method has been built on the application of hierarchical statistical modelling methods, and analysis of repeated experiments for the application of engine mapping. The methodology is based on two-stage regression approach, which organise the engine data for the mapping process in sweeps. The introduction of time-dependent covariates in the hierarchy of the modelling led to the development of a new approach for the problem of transient engine calibration. This new approach for transient engine modelling is analysed using a small designed data set for a throttle body inferred air ow phenomenon. The data collection for the model was performed on a transient engine test bed as a part of this work, with sophisticated software and hardware installed on it. Models and their associated experimental design protocols have been identi ed that permits the models capable of accurately predicting the desired response features over the whole region of operability. Further, during the course of the work, the utility of multi-layer perceptron (MLP) neural network based model for the multi-covariate case has been demonstrated. The MLP neural network performs slightly better than the radial basis function (RBF) model. The basis of this comparison is made on assessing relevant model selection criteria, as well as internal and external validation ts. Finally, the general ability of the model was demonstrated through the implementation of this methodology for use in the calibration process, for populating the electronic engine control module lookup tables