The design of future energy automation and management systems requires Distribution System Operators (DSOs) to analyse and compare different technical solutions for determining which of these could be best implemented in their networks. This paper presents a methodology that helps DSOs carry out such a complex task. The methodology is based on the Smart Grid Architecture Model (SGAM) framework. It was implemented using a web-based application that facilitates editing and automatic analysis of SGAM architectures. The methodology was successfully evaluated in the context of DISCERN European research project.

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The rising number of mobile devices increase the interest in longer battery durations. To increase battery duration, researchers try to improve e.g. different hardware components, such as processors and GPS for lower energy consumption. Frequently, software optimization possibilities to save energy are forgotten. Hence, an approach is shown to reduce energy consumption of applications by reengineering. Therefor, energy-wasteful code in applications is searched by code analysis and then restructured to optimize their energy consumption. Energy savings are validated by different energy measurements techniques. MotivationThe scope of mobile devices is increasing, due to new user requirements, more powerful processors, and diversity of applications. Mobile devices are used for many tasks, and thus, users carry their smartphone with them the whole day. Hence, batteries of these devices need to endure this time. The Blackberry Z10 shows the contrary [1]: First tests showed that batteries of Z10s are empty after about five hours. These are only 21 % of a day which does not match users expectation's of at least one day uptime. Blackberry's solution is an external battery which loads the main battery to lengthen its operating time. This is not acceptable for most users to use two batteries. Therefore, manufacturers should be interested in energyefficient software to extend devices' battery duration.To improve batteries' duration by software optimization, software evolution techniques are used: Reverse Engineering produces an abstract view of components and relationships inside on applications and provides to analyze for energy wasting software behavior [2]. Reengineering is applied to improve existing applications regarding their energy consumption, in which the intended application behavior is not changed. Therefor, code analyzing and restructuring are used to obtain more energy-efficient code. Both steps describe refactoring which is concerned with detecting and restructuring inefficient code (code smells) without changing its behavior [3]. This paper is structured as follows: First, some energy code smells which have been validated to be energy-wasteful by measurement are presented in Section 2. Next, the process of identifying and restructuring of energy code smells is described in Section 3. Section 4 shows a validity of the energy consumption of applications before and after reengineering. Section 5 concludes this paper with an outlook. Energy RefactoringEnergy refactorings contain energy code smells which are energy-wasteful parts of code. These energy code smells and their restructurings are defined and described similar as the code smells of Fowler [3]. Two such energy code smells are Binding ressources too early and Third party advertising [4].

Abstract-Conserving resources and saving energy has become an important issue for information and communication technology. With increasing adoption of smartphones and tablet PCs, reducing energy consumption in mobile computing is of particular significance. User expectations towards their mobile devices are rising, and functionality is increasing. Accordingly, available energy is made a scarce resource. This paper discusses how software reengineering techniques, like dynamic analysis and refactoring, can be applied to the field of energy-aware computing, to monitor, analyze, and optimize the energy profile of mobile applications and devices.

The project Integrating the Energy System (IES) Austria recognises interoperability as key enabler for the deployment of smart energy systems. Interoperability is covered in the Strategic Energy Technology Plan (SET-Plan) activity A4-IA0-5 and provides an added value because it enables new business options for most stakeholders. The communication of smart energy components and systems shall be interoperable to enable smooth data exchange, and thereby, the on demand integration of heterogeneous systems, components and services. The approach developed and proposed by IES, adopts the holistic methodology from the consortium Integrating the Healthcare Enterprise (IHE), established by information technology (IT) vendors in the health sector and standardised in the draft technical report ISO DTR 28380-1, to foster interoperable smart energy systems. The paper outlines the adopted IES workflow in detail and reports on lesson learnt when trial Integration Profiles based on IEC 61850 were tested at the first Connectathon Energy instalment, organised in conjunction with the IHE Connectathon Europe 2018. The IES methodology is found perfectly applicable for smart energy systems and successfully enables peer-to-peer interoperability testing among vendors. The public specification of required Integration Profiles, to be tested at subsequent Connectathon Energy events, is encouraged.