Integrating plug-in electric vehicles into the electric power system

This dissertation contributes to our understanding of how plug-in hybrid electric vehicles (PHEVs) and plug-in battery-only electric vehicles (EVs)—collectively termed plug-in electric vehicles (PEVs)—could be successfully integrated with the electric power system. The research addresses issues at a diverse range of levels pertaining to light-duty vehicles, which account for the majority of highway vehicle miles traveled, energy consumed by highway travel modes, and carbon dioxide emissions from on-road sources. Specifically, the following topics are investigated: (i) On-board power electronics topologies for bidirectional vehicle-to-grid and grid-to-vehicle power transfer; (ii) The estimation of the electric energy and power consumption by fleets of light-duty PEVs; (iii) An operating framework for the scheduling and dispatch of electric power by PEV aggregators; (iv) The pricing of electricity by PHEV aggregators and how it affects the decision-making process of a cost-conscious PHEV owner; (v) The impacts on distribution systems from PEVs under aggregator control; (vi) The modeling of light-duty PEVs for long-term energy and transportation planning at a national scale

Smart operation of transformers for sustainable electric vehicles integration and model predictive control for energy monitoring and management

The energy transmission and distribution systems existing today are stillsignificantly dependent on transformers,despite beingmore efficient and sustainable than those of decadesago. However, a large numberof power transformers alongwith other infrastructures have been in service for decades and are considered to be in their final ageing stage. Anymalfunction in the transformerscouldaffect the reliability of the entire electric network and alsohave greateconomic impact on the system.Concernsregardingurban air pollution, climate change, and the dependence on unstable and expensive supplies of fossil fuels have lead policy makers and researchers to explore alternatives to conventional fossil-fuelled internal combustion engine vehicles. One such alternative is the introduction of electric vehicles. A broad implementation of such mean of transportation could signify a drastic reduction in greenhouse gases emissions and could consequently form a compelling argument for the global efforts of meeting the emission reduction targets. In this thesis the topic of a high penetration of electric vehicles and their possible integration in insular networksis discussed. Subsequently, smart grid solutions with enabling technologies such as energy management systems and smart meters promote the vision of smart households, which also allows for active demand side in the residential sector.However, shifting loads simultaneously to lower price periods is likely to put extra stress on distribution system assets such as distribution transformers. Especially, additional new types of loads/appliances such as electric vehicles can introduce even more uncertaintyon the operation of these assets, which is an issue that needs special attention. Additionally, in order to improve the energy consumption efficiencyin a household, home energy management systems are alsoaddressed. A considerable number ofmethodologies developed are tested in severalcasestudies in order to answer the risen questions.Os sistemas de transmissão e distribuição de energia existentes hoje em dia sãosignificativamente dependentes dos transformadores, pese embora sejammais eficientes e sustentáveis do que os das décadas passadas. No entanto, uma grande parte dos transformadores ao nível dadistribuição, juntamente com outras infraestruturassubjacentes, estão em serviço há décadas e encontram-se nafasefinal do ciclo devida. Qualquer defeito no funcionamento dos transformadorespode afetara fiabilidadede toda a redeelétrica, para além de terum grande impactoeconómico no sistema.Os efeitos nefastos associadosàpoluição do arem centro urbanos, asmudançasclimáticasea dependência de fontes de energiafósseis têm levado os decisores políticos e os investigadores aexplorar alternativas para os veículos convencionais de combustão interna. Uma alternativa é a introdução de veículos elétricos. Umaampla implementação de tal meio de transporte poderia significar uma redução drástica dos gases de efeito de estufa e poderiareforçar os esforços globais para ocumprimento das metas de redução de emissõesde poluentes na atmosfera.Nesta tese é abordado o tema da elevada penetração dos veículos elétricose a sua eventual integração numarede elétricainsular. Posteriormente, são abordadas soluções de redeselétricasinteligentes com tecnologias específicas, tais como sistemas de gestão de energia e contadores inteligentes que promovamo paradigmadas casas inteligentes, que também permitem a gestão da procura ativano sector residencial.No entanto, deslastrando significativamente as cargaspara beneficiar de preçosmais reduzidosé suscetíveldecolocarconstrangimentosadicionaissobre os sistemas de distribuição, especialmentesobre ostransformadores.Osnovos tipos de cargas tais como os veículos elétricospodem introduzir ainda mais incertezassobre a operação desses ativos, sendo uma questão que suscitaespecial importância. Além disso, com ointuitode melhorar a eficiência do consumo de energia numa habitação, a gestão inteligente daenergia é um assunto que também éabordadonesta tese. Uma pletora de metodologias é desenvolvida e testadaemvários casos de estudos, a fim de responder às questões anteriormente levantadas

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

A Techno-Economic Investigation of Advanced Vehicle Technologies and Their Impacts on Fuel Economy, Emissions, and the Future Fleet

A more sustainable transportation energy future for society is the principal motivation of this dissertation. The central purpose of this work is to investigate vehicle technologies that contribute to fuel and emissions reductions while preserving consumer choice, and to evaluate their technological performance and economic practicability as essential aspects of meeting aspirational targets and regulatory requirements associated with the future vehicle fleet

Optimal behavior of responsive residential demand considering hybrid phase change materials

Due to communication and technology developments, residential consumers are enabled to participate in Demand Response Programs (DRPs), control their consumption and decrease their cost by using Household Energy Management (HEM) systems. On the other hand, capability of energy storage systems to improve the energy efficiency causes that employing Phase Change Materials (PCM) as thermal storage systems to be widely addressed in the building applications. In this paper, an operational model of HEM system considering the incorporation of more than one type of PCM in plastering mortars (hybrid PCM) is proposed not only to minimize the customerâ s cost in different DRPs but also to guaranty the habitantsâ  satisfaction. Moreover, the proposed model ensures the technical and economic limits of batteries and electrical appliances. Different case studies indicate that implementation of hybrid PCM in the buildings can meaningfully affect the operational pattern of HEM systems in different DRPs. The results reveal that the customerâ s electricity cost can be reduced up to 48% by utilizing the proposed model.The work of M. Shafie-khah and J.P.S. Catalão was supported by FEDER funds through COMPETE and by Portuguese funds through FCT, under FCOMP-01-0124-FEDER-020282 (Ref. PTDC/EEA-EEL/118519/2010) and UID/CEC/50021/2013, and also by the EU 7th Framework Programme FP7/2007-2013 under Grant agreement No. 309048 (project SiNGULAR)

Driving emissions down: Whole-supply-chain mitigation of greenhouse gases from passenger vehicles

Greenhouse-gas emitting human activities have caused the warming of the earth surface temperature by 0.97°C relative to pre-industrial levels. In order to prevent the most catastrophic consequences of climate change, most countries are committed to pursue action to limit global warming to well below 2°C under the Paris Agreement. Global transportation is the single largest user of energy as well as the largest carbon-dioxide emitting end-use sector, chiefly driven by passenger vehicles. Emissions caused by vehicles do not only occur at the vehicle tailpipe though. Pollutants are released along the entire vehicle supply chain, ranging from electric power plant discharges for electric vehicle charging, to industrial emissions from vehicle manufacturing and fuel processing. Detailed process models are used in this work in order to quantify the environmental burden of vehicle emissions along the entire supply chain. It is further investigated how these emissions can be mitigated, focusing on material efficiency and fueling behavior. These and other polluting processes are usually insufficiently considered in aggregate models of climate change mitigation. Therefore, it is also explored how the representation of vehicle supply chain emissions can be improved in these models. Finally, an integration of supply chain emissions with a climate change mitigation model of the US economy is achieved and several insights are gained from that exercise. It is shown that these emissions can significantly affect the composition of the US vehicle fleet and thus, the optimal climate change mitigation pathway of the US vehicle sector. In summary, this work contributes to a better understanding of future emissions of low-carbon vehicle systems. The results can guide future transport policy and investment decisions regarding low-carbon vehicle technology portfolios and their supporting infrastructure

Comparative analysis of tertiary control systems for smart grids using the Flex Street model

Various smart grid control systems have been developed with different architectures. Comparison helps developers identify their strong and weak points. A three-step analysis method is proposed to facilitate the comparison of independently developed control systems. In the first step, a microgrid model is created describing demand and supply patterns of controllable and non-controllable devices (Flex Street). In the second step, a version of Flex Street is used to design a case, with a given control objective and key performance indicators. In the last step, simulations of different control systems are performed and their results are analysed and compared. The Flex Street model describes a diverse set of households based on realistic data. Furthermore, its bottom-up modelling approach makes it a flexible tool for designing cases. Currently, three cases with peak-shaving objectives are developed based on scenarios of the Dutch residential sector, specifying various penetration rates of renewable and controllable devices. The proposed method is demonstrated by comparing IntelliGator and TRIANA, two independently developed control systems, on peak reduction, energy efficiency, savings and abated emissions. Results show that IntelliGator---a real-time approach---is proficient in reducing peak demand, while TRIANA---a planning approach---also levels intermediate demand. Both systems yield benefits (\geneuro5--54 per household per year) through reduced transport losses and network investments in the distribution network

On the effects of eletric vehicles on the power system

In Kombination mit erneuerbaren Energien (EEG) werden Elektrofahrzeuge (EVs) als wichtiger Bestandteil einer Transformation hin zu nachhaltigen Energiesystemen angesehen. Obwohl EVs heute nur einen geringen Anteil an der Fahrzeugdurchdringung in Deutschland darstellen, ist es das Ziel der Bundesregierung, dass im Jahr 2030 sechs Millionen EVs auf deutschen Straßen fahren sollen. Die Realisierung dessen hätte aufgrund des daraus resultierenden zusätzlichen Strombedarfs erhebliche Auswirkungen auf das Stromsystem. Wie hoch diese sind, hängt maßgeblich von der Ladestrategie der Fahrzeuge ab und ist der Forschungsgegenstand dieser Arbeit. Die übergeordnete ökonomische Fragestellung lautet: Welche Auswirkungen haben unterschiedliche EV-Ladestrategien auf Strommengen und -preise in einem Stromsystem mit einem hohen Anteil an erneuerbaren Energien? Zur Beantwortung dessen wird zunächst der zeitabhängige Strombedarf von EVs bewertet. Im Anschluss, werden die EV-Ladestrategien unkontrolliertes Laden (UNC), kostengesteuertes Laden (DSM) und bidirektionales Laden (V2G) in einem europäischen Strommarktmodell umgesetzt und die Auswirkungen quantifiziert. Dadurch wurden folgende Erkenntnisse erlangt: EVs tragen zu einer besseren Integration der EEG bei, da alle drei Ladestrategien deren Abregelung reduzieren. Der zusätzliche Spitzenlastbedarf aufgrund von UNC wird je Millionen EVs im schlimmsten Fall auf 560 MW geschätzt. Entsprechend des Fahrverhaltens variiert die Stromnachfrage stark zwischen Werktagen und Wochenendtagen. An Werktagen sind die Spitzenwerte fast dreimal so hoch wie an Wochenendtagen. Wird durch UNC die Stromnachfrage erhöht, bedarf es des vermehrten Einsatzes von Spitzenlastkraftwerken, was zu steigenden Preisspitzen führt. Im Gegensatz dazu verschieben die beiden flexiblen Ladestrategien DSM und V2G die EV-Stromnachfrage in Zeiten mit geringer residualer Netzlast bzw. bei V2G deutlich zugunsten von Kraftwerken mit den niedrigsten Grenzkosten. Dies führt bei DSM zu einer Anhebung der Preise in Schwachlastzeiten. Bei V2G wird die Preisstruktur erheblich geglättet, indem Spitzenlastpreise reduziert und Schwachlastpreise deutlich erhöht werden. An Wochenenden ist dieser Effekt bei V2G noch stärker als an Werktagen, da ein großer Teil der EVs als stationärer Speicher genutzt werden kann. Neben ökonomischer Effizienz hat dies teilweise unerwünschte ökologische Nebenwirkungen. So werden im Fall von V2G bei niedrigen CO2-Preisen emissionsintensive Technologien wie Braunkohlekraftwerke begünstigt. Nichtsdestotrotz führen systemische Effekte, nämlich die Reduzierung von EEG-Abschaltungen, die Substitution von Spitzenlastkraftwerken und ein erhöhter Stromaustausch mit den Nachbarländern zu einer Gesamtreduktion der CO2-Emissionen. Bei hohen CO2-Preisen sind die Effekte durch V2G hinsichtlich der CO2-Emissionen und der ökonomischen Effizienz durchweg positiv. Begrenzt werden diese Vorteile von V2G durch wirtschaftliche Sättigungseffekte, welche bereits ab zwei Millionen Fahrzeugen deutlich werden.In combination with renewable energy sources (RES), electric vehicles (EVs) are seen as an important element of a transformation towards sustainable energy systems. Although EVs currently represent only a small fraction of vehicle penetration in Germany, it is the goal of the German government to have six million EVs on German roads by 2030. The achievement of this would have a significant impact on the electricity system due to the resulting additional energy demand. How large these impacts are is the subject of this work. The overarching economic research question is: What effects do different EV charging strategies have on quantities and prices in a power system with a high share of RES? To answer this question, the time-dependent electricity demand of EVs is initially evaluated. Subsequently, the EV charging strategies uncontrolled charging (UNC), demand side management (DSM), in the sense of cost effective charging and bidirectional charging, i.e. vehicle-to-grid (V2G) are implemented in a European electricity market model and the impacts quantified. To summarize the findings: EVs contribute to the integration of RES, since all three charging strategies reduce curtailment. In the worst case scenario, the additional peak load demand due to UNC is estimated at 560 MW per million EVs. The demand for electricity varies greatly between working days and weekend days, depending on the driving patterns. On working days, the peak demand is almost three times as high as on weekend days. Overall, UNC leads to the increased use of peak load power plants, which leads to rising price peaks. In contrast, the two flexible charging strategies DSM and V2G shift the EVs' electricity demand in times of low residual grid load or, in the case of V2G, significantly in favour of the power plants with the lowest marginal costs. With DSM, this results in an increase in prices during off-peak periods. With V2G, the price structure is considerably smoothed by reducing peak load prices and significantly increasing off-peak prices. On weekend days this effect is even stronger with V2G than on working days, since a large part of the EVs can be used as stationary storage. In addition to economic effciency, this has partly undesirable ecological side effects. In the case of V2G, emission-intensive technologies such as lignite-fired power plants are promoted at low CO2 prices. Nevertheless, systemic effects, namely the reduction of RES curtailment, the substitution of peak load power plants, and an increased electricity exchange with neighboring countries, lead to an overall reduction of the CO2 emissions. These benefits of V2G are limited due to economic saturation effects, which are already noticeable starting at two million vehicles