Alocação holística de estações de recarga rápida para veículos elétricos

Orientador: Walmir de Freitas FilhoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A frota de veículos elétricos (VEs) tem crescido ao longo dos anos e uma maior adoção é esperada nas próximas décadas. Um aspecto chave para auxiliar na inserção dos VEs é a adequada disponibilidade (número, locais e tamanhos) das estações de recarga rápida (ERRs) que auxiliam em viagens, tanto entre cidades quanto dentro das cidades. Dado que estes estudos requerem a modelagem de grandes regiões considerando incertezas, aumentando consideravelmente a dimensão e complexidade do problema, uma metodologia capaz de fornecer uma solução de custo-benefício pode ser preferível, do ponto de vista prático, em comparação com um método de otimização clássico. Este projeto propõe o desenvolvimento de uma metodologia holística escalonável que integra simulações de fluxo de veículos e simulações multifásicas de redes elétricas em alta resolução (minutos) com propósito de encontrar o número, os locais e tamanhos de ERRs que propiciam o menor custo para a sociedade considerando incertezas nos padrões de fluxo de veículos. Primeiro, nesta metodologia são determinados os potenciais locais de instalação de ERRs com base na análise de tráfego, e na sequência, são explorados estes locais com propósito de quantificar custos diretos (equipamentos e terreno) e indiretos (perda de produtividade e reforços de rede) para encontrar a solução de menor custo. A metodologia é testada em um estudo de caso real brasileiro compreendendo 6 cidades e 26 subestações elétricas. A flexibilidade da metodologia é também investigada adaptando o modelo original para considerar a perspectiva de um investidor privado, pois a instalação de ERRs é definida com um investimento de longo prazo que necessita ser planejado considerando o máximo de aspectos possíveis. Por fim, a metodologia proposta também é utilizada para avaliar o potencial de tecnologias disruptivas, como geradores fotovoltaicos e baterias, com propósito de reduzir os impactos de ERRs nas redes elétricasAbstract: Electric vehicle (EV) fleet has constantly increased over the last years and higher adoption is expected in the coming decades. A key aspect to support and boost the EV uptake is the adequate availability (number, locations, and sizes) of fast charging stations (FCSs) to enable inter and intra-city travels. As these studies require the modelling of large geographical regions and several uncertainties, increasing considerably the dimension and complexity of the problem, a methodology able to provide the least-cost solution might be more relevant from a practical application perspective than a classical optimization-based approach. In this Ph.D. thesis is, therefore, proposed a scalable and holistic methodology that integrates high-resolution data of traffic flow and simulations of multi-phase electrical distribution systems to be applied to metropolitan areas to find number, locations, and sizes of FCSs considering the least societal cost and uncertainties in driving patterns. First, potential FCSs locations are determined based on traffic flow and then progressively explored to quantify capital (equipment and land) and indirect costs (loss of productivity related to the traffic flow, and necessity of reinforcements related to the electrical system) to obtain the least-cost solution. The applicability of the proposed method is evaluated by using a Brazilian real case study comprising a metropolitan region with 6 cities and 26 primary substations. The flexibility of the proposed approach is also investigated by adapting the original model considering the perspective of third-part investors, as FCSs is determined as a long-term investment that must be well-planned considering as many aspects as possible. Finally, the proposed concept is also applied to analyse the potential of grid-edge technologies, such as photovoltaic generators and energy storage systems, to reduce the impacts of FCSs in the electric system and reduce the long-term costsDoutoradoEnergia ElétricaDoutor em Engenharia Elétrica2015/24448-6FAPES

Secure Large Scale Penetration of Electric Vehicles in the Power Grid

As part of the approaches used to meet climate goals set by international environmental agreements, policies are being applied worldwide for promoting the uptake of Electric Vehicles (EV)s. The resulting increase in EV sales and the accompanying expansion in the EV charging infrastructure carry along many challenges, mostly infrastructure-related. A pressing need arises to strengthen the power grid to handle and better manage the electricity demand by this mobile and geo-distributed load. Because the levels of penetration of EVs in the power grid have recently started increasing with the increase in EV sales, the real-time management of en-route EVs, before they connect to the grid, is quite recent and not many research works can be found in the literature covering this topic comprehensively. In this dissertation, advances and novel ideas are developed and presented, seizing the opportunities lying in this mobile load and addressing various challenges that arise in the application of public charging for EVs. A Bilateral Decision Support System (BDSS) is developed here for the management of en-route EVs. The BDSS is a middleware-based MAS that achieves a win-win situation for the EVs and the power grid. In this framework, the two are complementary in a way that the desired benefit of one cannot be achieved without attaining that of the other. A Fuzzy Logic based on-board module is developed for supporting the decision of the EV as to which charging station to charge at. GPU computing is used in the higher-end agents to handle the big amount of data resulting in such a large scale system with mobile and geo-distributed nodes. Cyber security risks that threaten the BDSS are assessed and measures are applied to revoke possible attacks. Furthermore, the Collective Distribution of Mobile Loads (CDML), a service with ancillary potential to the power system, is developed. It comprises a system-level optimization. In this service, the EVs requesting a public charging session are collectively redistributed onto charging stations with the objective of achieving the optimal and secure operation of the power system by reducing active power losses in normal conditions and mitigating line congestions in contingency conditions. The CDML uses the BDSS as an industrially viable tool to achieve the outcomes of the optimization in real time. By participating in this service, the EV is considered as an interacting node in the system-wide communication platform, providing both enhanced self-convenience in terms of access to public chargers, and contribution to the collective effort of providing benefit to the power system under the large scale uptake of EVs. On the EV charger level, several advantages have been reported favoring wireless charging of EVs over wired charging. Given that, new techniques are presented that facilitate the optimization of the magnetic link of wireless EV chargers while considering international EMC standards. The original techniques and developments presented in this dissertation were experimentally verified at the Energy Systems Research Laboratory at FIU