The Innovation Interface: Business model innovation for electric vehicle futures

There is huge potential to link electric vehicles, local energy systems, and personal mobility in the city. By doing so we can improve air quality, tackle climate change, and grow new business models. Business model innovation is needed because new technologies and engineering innovations are currently far ahead of the energy system’s ability to accommodate them. This report explores new business models that can work across the auto industry, transport infrastructure and energy systems

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

A roadmap for China to peak carbon dioxide emissions and achieve a 20% share of non-fossil fuels in primary energy by 2030

As part of its Paris Agreement commitment, China pledged to peak carbon dioxide (CO2) emissions around 2030, striving to peak earlier, and to increase the non-fossil share of primary energy to 20% by 2030. Yet by the end of 2017, China emitted 28% of the world's energy-related CO2 emissions, 76% of which were from coal use. How China can reinvent its energy economy cost-effectively while still achieving its commitments was the focus of a three-year joint research project completed in September 2016. Overall, this analysis found that if China follows a pathway in which it aggressively adopts all cost-effective energy efficiency and CO2 emission reduction technologies while also aggressively moving away from fossil fuels to renewable and other non-fossil resources, it is possible to not only meet its Paris Agreement Nationally Determined Contribution (NDC) commitments, but also to reduce its 2050 CO2 emissions to a level that is 42% below the country's 2010 CO2 emissions. While numerous barriers exist that will need to be addressed through effective policies and programs in order to realize these potential energy use and emissions reductions, there are also significant local environmental (e.g., air quality), national and global environmental (e.g., mitigation of climate change), human health, and other unquantified benefits that will be realized if this pathway is pursued in China

Commercial EV fleet smart charging for cost reduction and renewables integration : A case study in Germany

The transition towards electric mobility reduces transportation carbon emissions but imposes challenges to integrate a growing electricity demand with renewable electricity generation and power systems. Smart charging arises as a key technology to minimize operational costs and support higher usage of green electricity for EVs. Market analysis indicates a trend towards dynamic electricity tariffs, incentivizing EV charging at times favourable to the electricity grid. This thesis studies, for a commercial EV fleet in Germany, different smart charging strategies considering a Real-Time-Pricing (RTP) tariff indexed to day-ahead market prices, and renewable electricity integrations. HOMER Grid is used to model such smart charging strategies and generate new EV load profiles. A dynamic model is used to calculate project economics and carbon impact using the generated smart charging EV load profiles and varying solar PV and batteries capacities. Direct and indirect CO2 emissions and renewable electricity usage ratios are calculated based on granular electricity grid and self-consumption data. The resulting Levelized Cost of Energy (LCOE) is minimized using Microsoft Excel’s Solver with GRG Non-linear solving method, varying solar PV and batteries capacities. The adoption of an RTP tariff decreases LCOE from € 0.530 to € 0.314 per kWh. A smart charging strategy designed to reduce peak demand and schedule charging at times of lower prices reduces LCOE further to € 0.283 per kWh. The lowest LCOE of € 0.281 per kWh is obtained with 34.4 kWp of solar PV capacity and no batteries. Carbon impact is minimized with larger solar PV and batteries capacitiesA transição para a mobilidade eléctrica reduz as emissões de carbono do setor de transporte, mas impõe desafios para integrar uma crescente demanda de eletricidade com eletricidade de fontes renováveis e sistemas de energia. O carregamento inteligente surge como uma tecnologia chave para minimizar os custos operacionais e apoiar uma maior utilização de eletricidade verde para VEs. O mercado de energia indica uma tendência para tarifas de eletricidade dinâmicas, incentivando o carregamento de VEs em momentos favoráveis à rede eléctrica. Esta tese estuda, para uma frota comercial de VEs na Alemanha, diferentes estratégias de carregamento inteligente considerando uma tarifa de Preços em Tempo Real (RTP) indexada aos preços do mercado grossista, e integração de eletricidade renovável. HOMER Grid é utilizado para modelar as estratégias de carregamento inteligente e gerar novos perfis de carregamento de VEs. Um modelo dinâmico permite calcular os custos do projeto e o impacto do carbono, utilizando os perfis de carregamento inteligente gerados e variando a capacidade de produção solar fotovoltaica e baterias. As emissões diretas e indiretas de CO2 e as frações de utilização de eletricidade renovável são calculados com base em dados granulares da rede eléctrica, e de autoconsumo. O Custo Nivelado de Energia (LCOE) resultante é minimizado utilizando o Solver do Microsoft Excel com o método de resolução não linear GRG, variando as capacidades de energia solar fotovoltaica e das baterias. A adoção de uma tarifa RTP diminui o LCOE de € 0.530 para 0.314 euros por kWh. Uma estratégia de carregamento inteligente, concebida para reduzir os picos e programar o carregamento para períodos de preços mais baixos, reduz ainda mais o LCOE para € 0.283 euros por kWh. O LCOE mais baixo, de € 0.281 euros por kWh, é obtido com 34,4 kWp de capacidade solar PV e sem baterias. O impacto do carbono é minimizado com maiores capacidades de energia solar fotovoltaica e de bateria

日本の電力部門における炭素・水・エネルギー・ネクサスと交通部門のエネルギー転換のシナリオ分析

Tohoku University博士（環境科学）thesi

Towards Cyber Security for Low-Carbon Transportation: Overview, Challenges and Future Directions

In recent years, low-carbon transportation has become an indispensable part as sustainable development strategies of various countries, and plays a very important responsibility in promoting low-carbon cities. However, the security of low-carbon transportation has been threatened from various ways. For example, denial of service attacks pose a great threat to the electric vehicles and vehicle-to-grid networks. To minimize these threats, several methods have been proposed to defense against them. Yet, these methods are only for certain types of scenarios or attacks. Therefore, this review addresses security aspect from holistic view, provides the overview, challenges and future directions of cyber security technologies in low-carbon transportation. Firstly, based on the concept and importance of low-carbon transportation, this review positions the low-carbon transportation services. Then, with the perspective of network architecture and communication mode, this review classifies its typical attack risks. The corresponding defense technologies and relevant security suggestions are further reviewed from perspective of data security, network management security and network application security. Finally, in view of the long term development of low-carbon transportation, future research directions have been concerned.Comment: 34 pages, 6 figures, accepted by journal Renewable and Sustainable Energy Review

Zero-Emission Heavy-Duty Vehicle Integration in Support of a 100% Renewable Electric Grid

For California and other parts of the world to move towards a net-zero-emission grid, potentially a 100% renewable grid, complementary technologies to support renewable solar and wind integration need to be clearly established. Specifically, the integration of variable and intermittent solar and wind renewable generation requires resources that can respond dynamically to changes in the net load in order to ensure stable grid performance. Zero-emission vehicles (ZEVs), encompassing battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs), are uniquely positioned to (1) support variable renewable generation and provide benefits to the grid while, at the same time (2) reducing emissions from the transportation sector. Due to their disproportionately large contribution to air pollution and greenhouse gas (GHG) emissions, targeting heavy-duty vehicles (HDVs) is essential if reduction goals are to be met. This work assesses the feasibility of heavy duty ZEVs (HD-ZEVs), selecting California as the example. From a technical standpoint, more than half of Class 3-7 vehicle miles travelled (VMT) can be met with heavy-duty BEV product in development today without trip modification. Class 8 trucks have a much lower BEV feasibility due to their longer trip distances and heavy-duty FCEV product becomes more likely. The challenge becomes providing carbon-free fuel, namely renewable electricity for HD-BEVs, and renewable hydrogen for HD-FCEVs. This study assesses the fuel supply chain impact of HD-ZEV deployment on GHG emissions and air quality for the year 2050. HD-BEVs relying on uncoordinated charging can increase peak load demand and hinder the target of achieving zero GHG emissions from the electric grid. Intelligent charging of HD- BEVs and renewable hydrogen production for HD-FCEVs are both effective methods for utilizing otherwise curtailed renewable generation for the support of a zero or near-zero emissions electric grid. This study also finds that moving towards an 80% reduction in GHG emissions from HDVs through ZEV adoption has the co-benefit of significantly reducing ozone and PM2.5 concentrations in key regions of California. In comparison, reducing grid emissions from an 80% reduction to a 100% clean electric grid has a significantly smaller, but not trivial, impact in criteria air pollutant concentrations

100% Renewable Energy Transition: Pathways and Implementation

Energy markets are already undergoing considerable transitions to accommodate new (renewable) energy forms, new (decentral) energy players, and new system requirements, e.g. flexibility and resilience. Traditional energy markets for fossil fuels are therefore under pressure, while not-yet-mature (renewable) energy markets are emerging. As a consequence, investments in large-scale and capital intensive (traditional) energy production projects are surrounded by high uncertainty, and are difficult to hedge by private entities. Traditional energy production companies are transforming into energy service suppliers and companies aggregating numerous potential market players are emerging, while regulation and system management are playing an increasing role. To address these increasing uncertainties and complexities, economic analysis, forecasting, modeling and investment assessment require fresh approaches and views. Novel research is thus required to simulate multiple actor interplays and idiosyncratic behavior. The required approaches cannot deal only with energy supply, but need to include active demand and cover systemic aspects. Energy market transitions challenge policy-making. Market coordination failure, the removal of barriers hindering restructuring and the combination of market signals with command-and-control policy measures are some of the new aims of policies.The aim of this Special Issue is to collect research papers that address the above issues using novel methods from any adequate perspective, including economic analysis, modeling of systems, behavioral forecasting, and policy assessment.The issue will include, but is not be limited to: Local control schemes and algorithms for distributed generation systems; Centralized and decentralized sustainable energy management strategies; Communication architectures, protocols and properties of practical applications; Topologies of distributed generation systems improving flexibility, efficiency and power quality; Practical issues in the control design and implementation of distributed generation systems; Energy transition studies for optimized pathway options aiming for high levels of sustainabilit