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Until recently, there have been relatively few studies exploring the power consumption of ICT resources in data centres. In this paper, we propose a methodology to capture the behaviour of most relevant energy-related ICT resources in data centres and present a generic model for them. This is achieved by decomposing the design process into four modelling phases. Furthermore, unlike the state-of-the-art approaches, we provide detailed power consumption models at server and storage levels. We evaluate our model for different types of servers and show that it suffers from an error rate of 2% in the best case, and less than 10% in the worst case.

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The future of e-mobility will consist of a large number of connected electric vehicles, smart charging stations and information systems at the intersection of electricity and mobility sector. When engineering and integrating the multitude of systems into even more complex systems-of-systems for e-mobility, interoperability and complexity handling are vital. Model-based system architectures support the engineering process of information systems with the concepts of abstraction, reduction and separation of concerns. In this paper, we contribute to the research body, by extracting requirements for managing complexity and interoperability of these systems. Further, a comparative analysis of the state-of-the-art in existing architecture models and frameworks for e-mobility is conducted. Based on the identified gaps in existing research, we propose the E-Mobility Systems Architecture (EMSA) Model, a three-dimensional systems architecture model for the e-mobility sector. Its structure originates from the well-established Smart Grid Architecture Model. We further allocate all relevant entities from the e-mobility sector to the EMSA dimensions, including a harmonized role model, functional reference architecture, component and systems allocation, as well as a mapping of data standards and communication protocols. The model then is validated qualitatively and quantitatively against the requirements with a case study approach. Our evaluation shows that the EMSA Model fulfills all requirements regarding the management of complexity and ensuring interoperability. From the case study, we further identify gaps in current data model standardization for e-mobility.

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Abstract-The power grid has become a critical infrastructure, which modern society cannot do without. It has always been a challenge to keep power supply and demand in balance; the more so with the recent rise of intermittent renewable energy sources. Demand response schemes are one of the counter measures, traditionally employed with large industrial plants. This paper suggests to consider data centres as candidates for demand response as they are large energy consumers and as they are able to adapt their power profile sufficiently well. To unlock this potential, we suggest a system of contracts that regulate collaboration and economic incentives between the data centre and its energy supplier (GreenSDA) as well as between the data centre and its customers (GreenSLA). Several presented use cases serve to validate the suitability of data centers for demand response schemes.

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e existing electromobility (EM) is still in its edgling stage and multiple challenges have to be overcome to make Electric Vehicles (EVs) as convenient as combustion engine vehicles. Users and Electric Vehicle Fleet Operators (EFOs) want their EVs to be charged and ready for use at all times. is straightforward goal, however, is counteracted from various sides: e range of the EV depends on the status and depletion of the EV ba ery which is in uenced by EV use and charging characteristics. Also, most convenient charging from the user's point of view, might unfortunately lead to problems in the power grid. As in the case of a power peak in the evening when EV users return from work and simultaneously plug in their EVs for charging. Last but not least, the mass of EV ba eries are an untapped potential to store electricity from intermi ent renewable energy sources. In this paper, we propose a novel approach to tackle this multilayered problem from di erent perspectives. Using on-board EV data and grid prediction models, we build up an information model as a foundation for a back end service containing EFO and Charging Station Provider (CSP) logic as well as a central Advanced Drivers Assistant System (ADAS). ese components connect to both battery management and user interfaces suggesting various routing and driving behaviour alternatives customized and incentivized for the current user pro le optimizing above mentioned goals. CCS CONCEPTS •Applied computing →Transportation; •Hardware →Smart grid; Energy distribution; •Social and professional topics →User characteristics; •So ware and its engineering →So ware architectures;