Three papers on inverse optimization algorithms, PEV sales forecasting, and PEVs\u27 potential impact on power systems

This thesis consists of three journal papers that I have been worked on during my PhD program of study. The first paper presents heuristic algorithms that are designed to be implemented and executed in parallel with an existing algorithm in order to overcome its two limitations. Computational experiments show that implementing the heuristic algorithm on one auxiliary processor in parallel with the existing algorithm on the main processor significantly improves its computational efficiency, in addition to providing a series of improving feasible upper bound solutions. In the second paper, we present two interactive models to jointly forecast PEV sales and the diurnal recharging load curve in the U.S. between 2012 and 2020. A case study is conducted for the Midwest ISO region. Compared to the sales forecasts from the literature, our results turn out to be less optimistic. Our recharging load forecast results also suggest that, if appropriately managed, the impact of PEVs on electricity load would not be overwhelming in the next decade. The third paper focuses on assessing and mitigating the potential impact of PEVs recharging load on power systems, Case study show that electricity rates with higher flexibility induces PEVs to have less impact on the power systems in terms of both generation cost and uncertainties. Also, PEV users higher recharging behavior responsiveness will improve the effectiveness of price incentives and the control ability of the power utilities under all types of TOU rates mechanisms

Benefits of stochastic optimisation with grid price prediction for electric vehicle charging

© 2017 SAE International. The goal of grid friendly charging is to avoid putting additional load on the electricity grid when it is heavily loaded already, and to reduce the cost of charging to the consumer. In a smart metering system, Day Ahead tariff (DA) prices are announced in advance for the next day. This information can be used for a simple optimization control, to select to charge at cheapest times. However, the balance of supply and demand is not fully known in advance and the Real-Time Prices (RTP) are therefore likely to be different at times. There is always a risk of a sudden price change, hence adding a stochastic element to the optimization in turn requiring dynamic control to achieve optimal time selection. A stochastic dynamic program (SDP) controller which takes this problem into account has been made and proven by simulation in a previous paper. Since there are differences between the DA and the RTP tariff, this paper proposes a (1) predictor to create an unbiased estimate of the RTP tariff based on available data. It uses a regression on historical data to find the best prediction of the expected price. Finally, a (2) case study based on data from the Illinois Electricity Grid prices is presented to validate the SDP controller over several years of data. The stochastic optimization uses the RTP prices effectively, getting very close to the globally optimal charging price. However, the predictor achieves only a slight reduction in prediction uncertainty with this data sate, and it has a negligible effect on cost. This means that DA prices can be used as a fair prediction of RTP charging cost here. The SDPM successfully reacts in the case study and leads to savings on charging costs over the years presented

Model for the impact evaluation of electric vehicle integration on the adequacy of generating systems

TCC (graduação) - Universidade Federal de Santa Catarina. Araranguá. Engenharia de Energia.Recentemente, a integração de veículos elétricos em sistemas de potência tem ganhado atenção substancial da academia e de empresas do setor elétrico principalmente por causa dos serviços auxiliares que essa tecnologia pode oferecer aos sistemas de potência. Ainda, a presença crescente de fontes renováveis nos sistemas de potência trouxe uma incerteza adicional à previsão de capacidade de geração disponível. Por isso, esse estudo tem como objetivo desenvolver um modelo de veículos elétricos para a avaliação do impacto da integração em larga escala de veículos elétricos na adequação de sistemas de geração. Para incluir a crescente presença de energia eólica, o método proposto é usado para avaliar o impacto da integração de veículos elétricos em uma versão modificada do sistema elétrico IEEE RTS-96. Os resultados mostram que o impacto da integração em larga escala de VEs na adequação de sistemas de geração depende do critério usado pelos proprietários dos VEs no momento de decidir por carregar ou não seus VEs. Ainda, é mostrado que o impacto dos VEs pode ser reduzido e até mesmo ser positivo, se os VEs são considerados provedores de serviços auxiliares à rede.In recent years, the integration of electric vehicles (EVs) into power systems has gained substantial attention by the academia and utilities mainly due to the new opportunities of ancillary services that this technology can offer to power systems. Moreover, the growing presence of renewable energy sources in power systems has brought additional uncertainty to the forecast of available generating capacity. Thereby, this study aims at developing an EV model for evaluating the impact of large-scale EV integration on the adequacy of generating systems. In order to account for the growing presence of wind generation, the proposed method is used to evaluate the impact of EV integration on a modified version of the IEEE RTS - 96 electric system. The results show that large-scale EV integration impact on the adequacy of generating systems depends on the criterion used by EV's owners when deciding whether to recharge their EVs or not. Also, it is shown that the EV impact can be reduced and even be positive, if the EVs are regarded as providers of ancillary services to the grid

Cost-optimal charging of electric vehicles using real-time pricing

The large-scale adoption of EVs presents both potential benefits and difficult challenges. The already stressed electricity grids will have to manage the influx of EV charging requirements, which is especially difficult at peak times. This calls for smart solutions to optimally charge EVs in a grid-friendly way, using demand response where possible. In line with the demand, the electricity prices at peak times can be very high and it would also be advantageous for the user to avoid charging at these times. Therefore, the goal of grid friendly charging is twofold: to avoid putting additional load on the electricity grid when it is heavily loaded already, and to reduce the cost of charging to the consumer. [Continues.

Planning Model for Implementing Electric Vehicle Charging Infrastructure in Distribution System

Plug-in electric vehicles (PEVs) are growing in popularity in developed countries in an attempt to overcome the problems of pollution, depleting natural oil and fossil fuel reserves and rising petrol costs. In addition, automotive industries are facing increasing community pressure and governmental regulations to reduce emissions and adopt cleaner, more sustainable technologies such as PEVs. However, accepting this new technology depends primarily on the economic aspects for individuals and the development of adequate PEV technologies. The reliability and dependability of the new vehicles (PEVs) are considered the main public concerns due to range anxiety. The limited driving range of PEVs makes public charging a requirement for long-distance trips, and therefore, the availability of convenient and fast charging infrastructure is a crucial factor in bolstering the adoption of PEVs. The goal of the work presented in this thesis was to address the challenges associated with implementing electric vehicle fast charging stations (FCSs) in distribution system. Installing electric vehicle charging infrastructure without planning (free entry) can cause some complications that affect the FCS network performance negatively. First, the number of charging stations with the free entry can be less or more than the required charging facilities, which leads to either waste resources by overestimating the number of PEVs or disturb the drivers’ convenience by underestimate the number of PEVs. In addition, it is likely that high traffic areas are selected to locate charging stations; accordingly, other areas could have a lack of charging facilities, which will have a negative impact on the ability of PEVs to travel in the whole transportation network. Moreover, concentrating charging stations in specific areas can increase both the risk of local overloads and the business competition from technical and economic perspectives respectively. Technically, electrical utilities require that the extra load of adopting PEV demand on the power system be managed. Utilities strive for the implementation of FCSs to follow existing electrical standards in order to maintain a reliable and robust electrical system. Economically, the low PEV penetration level at the early adoption stage makes high competition market less attractive for investors; however, regulated market can manage the distance between charging stations in order to enhance the potential profit of the market. As a means of facilitating the deployment of FCSs, this thesis presents a comprehensive planning model for implementing plug-in electric vehicle charging infrastructure. The plan consists of four main steps: estimating number of PEVs as well as the number of required charging facilities in the network; selecting the strategic points in transportation network to be FCS target locations; investigating the maximum capability of distribution system current structure to accommodate PEV loads; and developing an economical staging model for installing PEV charging stations. The development of the comprehensive planning begins with estimating the PEV market share. This objective is achieved using a forecasting model for PEV market sales that includes the parameters influencing PEV market sales. After estimating the PEV market size, a new charging station allocation approach is developed based on a Trip Success Ratio (TSR) to enhance PEV drivers’ convenience. The proposed allocation approach improves PEV drivers’ accessibility to charging stations by choosing target locations in transportation network that increase the possibility of completing PEVs trips successfully. This model takes into consideration variations in driving behaviors, battery capacities, States of Charge (SOC), and trip classes. The estimation of PEV penetration level and the target locations of charging stations obtained from the previous two steps are utilized to investigate the capability of existing distribution systems to serve PEV demand. The Optimal Power Flow (OPF) model is utilized to determine the maximum PEV penetration level that the existing electrical system can serve with minimum system enhancement, which makes it suitable for practical implementation even at the early adoption rates. After that, the determination of charging station size, number of chargers and charger installation time are addressed in order to meet the forecasted public PEV demand with the minimum associated cost. This part of the work led to the development of an optimization methodology for determining the optimal economical staging plan for installing FCSs. The proposed staging plan utilizes the forecasted PEV sales to produce the public PEV charging demand by considering the traffic flow in the transportation network, and the public PEV charging demand is distributed between the FCSs based on the traffic flow ratio considering distribution system margins of PEV penetration level. Then, the least-cost fast chargers that satisfy the quality of service requirements in terms of waiting and processing times are selected to match the public PEV demand. The proposed planning model is capable to provide an extensive economic assessment of FCS projects by including PEV demand, price markup, and different market structure models. The presented staging plan model is also capable to give investors the opportunity to make a proper trade-off between overall annual cost and the convenience of PEV charging, as well as the proper pricing for public charging services.

Electricity load estimation and management for plug-in vehicle recharging on a national scale prior to the development of third party monitoring and control mechanisms

In accordance with the main aim of the study, a widely accessible, modifiable tool was created for parties interested in maintaining the national electricity supply network and parties interested in informing policy on plug-in vehicle adoption schemes and recharging behaviour control. The Parry Tool enables the user to incorporate present limits to plug-in vehicle recharging demand scheduling as imposed by the state of present technology (no third party mechanism for monitoring and control of recharging), present human travel behaviour needs and existing patterns in electricity usage; into the investigation of the impacts of recharging demand impacts and the design of mitigation measures for deflecting (parrying) worst case scenarios."br/"The second aim of the project was to demonstrate the application of the Parry Tool. The multidisciplinary/interdisciplinary information gathered by the Parry Tool was used to produce national demand profiles for plug-in vehicle recharging demand, calculated using socioeconomic and travel behaviour-estimated population sizes for plug-in eligible vehicles and vehicle usage patterns, which were added to existing national electricity demand for a chosen test week – this was the first scenario subsequently tested. The information gathered by the Parry Tool was then used to inform the design of two demand management methods for plug-in vehicle recharging: Recharging Regimes and weekly recharging load-shifting – these were the second and third scenarios subsequently tested."br/"Unmitigated simultaneous recharging demand in scenario 1 (all vehicles assumed to recharge at home upon arrival home every day) severely exacerbated peak demand, raising it by 20% above the highest peak in existing demand for the year 2009 over half an hour from 58,554 MW to 70,012 MW – a challenge to the generation sector. This increased the difference between daily demand minima and maxima and made the new total demand have sharper peaks – a challenge for grid regulators."br/"Recharging Regimes in scenario 2 split the estimated national plug-in vehicle populations into groups of different sizes that started recharging at different times of the day, with the word ‘regime’ being applied because the spread of start times changed over the course of the test week from workdays to weekend. This avoided exacerbation of the peak and reduced the difference between daily demand minima and maxima by raising minima, providing a load-levelling service. Scenario 3 embellished the Recharging Regimes with workday-to-weekend recharging load-shifting that therefore took better advantage of the often overlooked weekly pattern in existing demand (demand being higher on workdays than weekends), by allowing partial recharging of a segment of the plug-in vehicle population."br/"Limited consideration of the impact of changing vehicle energy usage (for which distance travelled was assumed to proxy in this study) showed that the more vehicles used their batteries during the day, the better the levelling effect offered by Recharging Regimes. Greater utilisation of battery capacity each day, however, can also be assumed to lessen the potential for workday-to-weekend load levelling, because load-shifting depends upon vehicles being able to partially recharge or defer recharging to later days and still meet their travel needs plus keep a reserve State Of Charge (SOC) for emergency and other unplanned travel. Whilst altering vehicle energy usage did not change the finding that unmitigated simultaneous recharging exacerbated existing peak demand, it was noted that when limited mileage variation was considered this sharpened the profile of total demand – the rise and fall of the new peak far steeper than that of the original peak in existing demand."br/"The Parry Tool combines a series of integrated methods, several of which are new contributions to the field that use UK data archives but may potentially be adapted by researchers looking at energy issues in other nations. It presents a novel fossil-fuel based justification for targeting road transport – acknowledging energy use of fossil fuel as the originator of many global and local problems, the importance of non-energy use of petroleum products and subsequent conflicts of interest for use, and a fossil fuel dependency based well-to-wheel assessment for UK road transport for the two energy pathways: electricity and petroleum products. It presents a method for the recalculation and ranking of top energy use/users using national energy use statistics that better highlights the importance of the electricity industry. It also presents the first publicly documented method for the direct consultation and extraction of vehicle-focused statistics from the people-focused National Travel Survey database, including a travel behaviour and household income-based assessment of plug-in vehicle eligibility, used to scale up to national estimates for battery electric and plug-in electric hybrid vehicle (BEV and PHEV) national population sizes."br/"The work presented here is meant to allow the reader to perceive the potential benefits of using several resources in combination. It details the Parry Tool, a framework for doing so, and where necessary provides methods for data analysis to suit. It should however be noted that methods were kept as simple as possible so as to be easily followed by non-specialists and researchers entering the field from other disciplines. Methods are also predominantly data-exploratory in nature: strong conclusions therefore should not be drawn. Rather, the work here should be seen as a guideline for future work that may more rigorously study these combined topics and the impacts they may have upon plug-in vehicle ownership, usage behaviour, impacts of recharging upon the national network and the design of mitigation measures to cope with this new demand

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

Optimal Operation of a Rooftop Photovoltaic Electric Vehicle Parking Lot

Devida à rápida expansão a nível global dos veículos elétricos (VEs), surge a necessidade de desenvolver parques de estacionamento para VEs, de forma a dar resposta às necessidades de carregamento dos mesmos e simultaneamente utilizá-los em benefício das smart grids. No entanto, o aumento do número de VEs nos sistemas de distribuição requer uma atenção redobrada, caso contrário, a fiabilidade do sistema de energia poderá ser comprometida. Assim, parques de estacionamento de VEs poderão representar uma solução evitar problemas de estabilidade. A instalação de painéis fotovoltaicos em parques de estacionamento tem vindo a ganhar interesse como uma abordagem apropriada para o seu design e operação, sendo uma solução acessível e conveniente para o carregamento de VEs. Dado que os VEs se encontram estacionados durante consideráveis períodos de tempo durante o dia, especialmente em grandes centros urbanos, podem ser carregados diretamente através de energia solar fotovoltaica. Deste modo, o objetivo da presente dissertação foca-se na operação ótima de um parque de estacionamento de VEs com cobertura fotovoltaica, considerando diferentes parâmetros tais como as condições meteorológicas e o comportamento dos utilizadores de VEs. Esta análise resultará em encontrar a solução ótima da operação do parque de estacionamento do ponto de vista do proprietário/operador, minimizando os custos de operação e maximizando os serviços fornecidos à rede.Due to the rapidly increasing share of electric vehicles (EVs) worldwide, there will be a need to offer many EV parking lots, to provide for their charging requirements in addition to attempting to fully utilize them for the benefit of future smart grids. However, increasing EVs penetration in such systems has to be planned with extra care, otherwise it might instead be a source of problems to grid reliability. Hence, well-operated EV parking lots can be a good solution to increase system stability. Equipping the parking lots with rooftop photovoltaics (PVs) has been gaining interest as a good approach for their design and operation, being an opportune and reasonably priced solution for EV charging needs. On this basis, when EVs are parked for a considerable period of time during the day, particularly in the mostly located near urban populations hubs, they can be charged directly by the solar generation. Accordingly, the aim of this paper is to provide a feasible solution for optimal operation of a PV-equipped EV parking lot, considering several parameters including weather conditions and EV driver's behaviors. This analysis will result in finding the optimal strategy for the operation of the parking lot from the owner/operator perspective in order to minimize costs and maximize services provided to the grid