Smart Energy and Intelligent Transportation Systems

With the Internet of Things and various information and communication technologies, a city can manage its assets in a smarter way, constituting the urban development vision of a smart city. This facilitates a more efficient use of physical infrastructure and encourages citizen participation. Smart energy and smart mobility are among the key aspects of the smart city, in which the electric vehicle (EV) is believed to take a key role. EVs are powered by various energy sources or the electricity grid. With proper scheduling, a large fleet of EVs can be charged from charging stations and parking infrastructures. Although the battery capacity of a single EV is small, an aggregation of EVs can perform as a significant power source or load, constituting a vehicle-to-grid (V2G) system. Besides acquiring energy from the grid, in V2G, EVs can also support the grid by providing various demand response and auxiliary services. Thanks to this, we can reduce our reliance on fossil fuels and utilize the renewable energy more effectively. This Special Issue “Smart Energy and Intelligent Transportation Systems” addresses existing knowledge gaps and advances smart energy and mobility. It consists of five peer-reviewed papers that cover a range of subjects and applications related to smart energy and transportation

Optimal train control on various track alignments considering speed and schedule adherence constraints

The methodology discussed in this dissertation contributes to the field of transit operational control to reduce energy consumption. Due to the recent increase in gasoline cost, a significant number of travelers are shifting from highway modes to public transit, which also induces higher transit energy consumption expenses. This study presents an approach to optimize train motion regimes for various track alignments, which minimizes total energy consumption subject to allowable travel time, maximum operating speed, and maximum acceleration/deceleration rates. The research problem is structured into four cases which consist of the combinations of track alignments (e.g., single vertical alignment and mixed vertical alignment) and the variation of maximum operating speeds (e.g., constant and variable). The Simulated Annealing (SA) approach is employed to search for the optimal train control, called golden run . To accurately estimate energy consumption and travel time, a Train Performance Simulation (TPS) is developed, which replicates train movements determined by a set of dynamic variables (e,g., duration of acceleration and cruising, coasting position, braking position, etc.) as well as operational constraints (e.g., track alignment, speed limit, minimum travel time, etc.) The applicability of the developed methodology is demonstrated with geographic data of two real world rail line segments of The New Haven Line of the Metro North Railroad: Harrison to Rye Stations and East Norwalk to Westport Stations. The results of optimal solutions and sensitivity analyses are presented. The sensitivity analyses enable a transit operator to quantify the impact of the coasting position, travel time constraint, vertical dip of the track alignment, maximum operating speed, and the load and weight of the train to energy consumption. The developed models can assist future rail system with Automatic Train Control (ATC), Automatic Train Operation (ATO) and Positive Train Control (PTC), or conventional railroad systems to improve the planning and operation of signal systems. The optimal train speed profile derived in this study can be considered by the existing signal system for determining train operating speeds over a route

Prospects for Electric Mobility: Systemic, Economic and Environmental Issues

The transport sector, which is currently almost completely based on fossil fuels, is one of the major contributors to greenhouse gas emissions. Heading towards a more sustainable development of mobility could be possible with more energy efficient automotive technologies such as battery electric vehicles. The number of electric vehicles has been increasing over the last decade, but there are still many challenges that have to be solved in the future. This Special Issue “Prospects for Electric Mobility: Systemic, Economic and Environmental Issues” contributes to the better understanding of the current situation as well as the future prospects and impediments for electro mobility. The published papers range from historical development of electricity use in different transport modes and the recent challenges up to future perspectives

Documentation of IFE-TIMES-Norway v2

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Documentation of IFE-TIMES-Norway v3

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The impact of valuation rules for intangible assets in Japanese and German accounts of listed companies : [Version April 2003]

Intangible assets as goodwill, licenses, research and development or customer relations become in high technology and service orientated economies more and more important. But comparing the book values of listed companies and their market capitalization the financial reports seems to fail the information needs of market participants regarding the estimate of the proper firm value. Moreover, with the introduction of Anglo-American accounting systems in Europe and Asia we can observe even in the accounts of companies sited in the same jurisdiction diverging accounting practices for intangible assets caused by different accounting standards. To assess the relevance of intangible assets in Japanese and German accounts of listed companies we therefore measure certain balance sheet and profit and loss relations according to goodwill and self-developed software. We compare and analyze valuation rules for goodwill and software costs according to German GAAP, Japanese GAAP, US GAAP and IAS to determine the possible impact of diverging rules in the comparability of the accounts. Our results show that the comparability of the accounts is impaired because of different accounting practices. The recognition and valuation of goodwill and self-developed software varies significantly according to the accounting regime applied. However, for the recognition of self-developed software, the effect on the average impact on asset coefficients or profit is not that high. Moreover, an industry bias can only be found for the financial industry. In contrast, for goodwill accounting we found major differences especially between German and Japanese Blue Chips. The introduction of the new goodwill impairment only approach and the prohibition of the pooling method may have a major impact especially for Japanese companies’ accounts

Infrastructure and Growth in South Africa: Benchmarking, Productivity and Investment Needs, paper presented at Economic Society of South Africa (ESSA) Conference, Durban, 9/7-9/2005

The paper provides three principal results. First, we benchmark South African infrastructure performance in terms of access, pricing, and quality against key comparator groups of countries using the most recent World Bank benchmarking data base (2005). Second, we establish clear empirical links between infrastructure and productivity using South African time-series data. And third, we estimate long-run demand for electricity and telephony using a panel of 52 low-income and middle- income countries for the period 1980-2002 and then project investment needs in these sectors until 2010. Our projections indicate average annual electricity generating requirement of US$0.5 billion or about 0.2$1.98 billion or 0.75% of GDP for telephony.infrastructure, growth, productivity, investment, South Africa

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