Renewable energy sources are key enablers to decrease greenhouse gas emissions and to cope with the anthropogenic global warming. Their intermittent behaviour and limited storage capabilities present challenges to power system operators in maintaining the high level of power quality and reliability. However, the increased availability of advanced automation and communication technologies has provided new intelligent solutions to face these challenges. Previous work has presented various new methods to operate highly interconnected power grids with corresponding components in a more effective way. As a consequence of these developments the traditional power system is transformed into a cyber-physical system, a smart grid.Previous and ongoing research activities have mainly focused on validating certain aspects of smart grids, but until now no integrated approach for analysing and evaluating complex configurations in a cyber-physical systems manner is available. This paper tackles this issue and addresses system validation approaches for smart grids. Different approaches for different stages in the design, development, and roll-out phase of smart grid solutions and components are discussed. Finally, future research directions are analysed.Keywords: smart grid; simulation; hardware-in-the-loop; research; infrastructure; education; training IntroductionEnergy efficiency and low-carbon technologies are key enablers to mitigate the increasing emission of green-house gases still resulting in a global warming trend [1]. The efforts to reduce greenhouse gas emissions also strongly affect the power system. Renewable sources, storage systems and flexible loads provide enhanced possibilities but power system operators and utilities have to cope with their fluctuating nature, limited storage capabilities and the typically higher complexity of the whole infrastructure with a growing amount of heterogeneous components [2]. Additionally, due to changing framework conditions, like the liberalization of the energy markets and new regulatory rules, as well as technology developments (e.g., new components), approaches for design, planning, and operation of the future electric energy system have to be restructured. Sophisticated component design methods, intelligent information and communication architectures, automation and control concepts as well as proper standards are necessary in order to manage the higher complexity of such intelligent power systems (i.e., smart grids) [3][4][5]. Besides technical challenges also economic, ecological and social issues have to be addressed in smart grid research and innovation, too.During the last decade-especially in the past framework programs of the European Commission (i.e., FP6 and FP7)-a growing number of research and technology development activities have already been carried out in this area. Their main attempt was to fulfil the challenging goals and needs of the Strategic Energy Technology Plan (SET-Plan) of the European Commission for a sustainable environment and to foster the inno...

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Abstract-The increasing share of distributed energy resources and renewable energy in power systems results in a highly variable and less controllable energy production. Therefore, in order to ensure stability and to reduce the infrastructure and operation cost of the power grid, flexible and controllable demand is needed. The research area of demand side management is still very much in flux and several options are being presented which can all be used to manage loads in order to achieve a flexible and more responsive demand. These different control schemes are developed with different organization of the power sector in mind and thus can differ significantly in their architecture, their integration into the various markets, their integration into distribution network operation and several other aspects. This paper proposes a classification of load control policies for demand side management in smart buildings, based on external behavior: direct, indirect, transactional and autonomous control; internal operation: decision support system scope, control strategy, failure handling and architecture. This classification assists in providing an overview of the control schemes as well as different ways of representing a building.

Abstract-This work presents two large-scale regional models used for the evaluation of normalized power output from wind turbines and photovoltaic power plants on a European regional scale. The models give an estimate of renewable production on a regional scale with 1 h resolution, starting from a mesoscale meteorological data input and taking in account the characteristics of different plants technologies and spatial distribution. An evaluation of the hourly forecasted energy production on a regional scale would be very valuable for the transmission system operators when making the long-term planning of the transmission system, especially regarding the cross-border power flows. The tuning of these regional models is done using historical meteorological data acquired on a per-country basis and using publicly available data of installed capacity.Index Terms-Large-scale integration, modeling, photovoltaic (PV) power systems, renewable energy sources, wind energy.

Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads. As a result of these developments the validation on the system level becomes much more important during the whole engineering and deployment process, today. In earlier development stages and for larger system configurations laboratory-based testing is not always an option. Due to recent developments, simulation-based approaches are now an appropriate tool to support the development, implementation, and rollout of smart grid solutions. This paper discusses the current state of simulation-based approaches and outlines the necessary future research and development directions in the domain of power and energy systems.

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Abstract-Distributed control strategies applied to power distribution control problems are meant to offer robust and scalable integration of distributed energy resources (DER). However, the term "distributed control" is often loosely applied to a variety of very different control strategies. In particular there is a lack of discrimination between aspects related to communication topology, physical distribution of components and associated control objectives. This has lead to a lack of objective criteria for performance comparison and general quality assessment of state of the art distributed control solutions. For such comparison, a classification is required that is consistent across the different aspects mentioned above. This paper develops systematic categories of control strategies that accounts for communication, control and physical distribution aspects of the problem, and provides a set of criteria that can be assessed for these categories. The proposed taxonomy is applied to the state of the art as part of a review of existing work on distributed control of DER. Finally, we demonstrate the applicability and usefulness of the proposed classification to researchers and system designers.

Abstract-The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification.