Originally proposed as an alternative to traditional energy planning methodology in the 1970s, backcasting is increasingly applied in futures studies related to sustainability, as it is viewed as a natural step in operationalizing sustainable development. This futures study is concerned with data-driven smart sustainable urbanism as an instance of sustainable urban development—a strategic approach

Cyber-attacks these threats, the cyber security assessment of IT and OT infrastructures can foster a higher degree of safety and resilience against cyber-attacks. Therefore, the use of attack simulations based on system architecture models is proposed. To reduce the effort of creating new attack graphs for each system under assessment, domain-specific languages (DSLs) can be employed. DSLs codify the

The IoT and big data technologies have become essential to the functioning of both smart cities and sustainable cities, and thus, urban operational functioning and planning are becoming highly responsive to a form of data-driven urbanism. This offers the prospect of building models of smart sustainable cities functioning in real time from routinely sensed data. This in turn allows to monitor, understand

Power system operation increasingly relies on numerous day-ahead forecasts of local, disaggregated loads such as single buildings, microgrids and small distribution system areas. Various data-driven models can be effective predicting specific time series one-step-ahead. The aim of this work is to investigate the adequacy of neural network methodology for predicting the entire load curve day-ahead and

René Schumann1*, Michael Brand2 and Khoa Nguyen1 1 HES-SO Valais Wallis, SiLab, Rue de Technpole 3, 3960 Sierre, 3960 Sierre, Switzerland; 2 OFFIS - Institut für Informatik, Escherweg 2, 26121 Oldenburg, Switzerland. Correspondence: René Schumann (rene.schumann@hevs.ch) Dear readers, Fig. 1 (abstract P1). General Procedure for Protocol Fuzzing.Full size image Fig. 1 (abstract P4). Developed sensor

Unlocking and managing flexibility is an important contribution to the integration of renewable energy and an efficient and resilient operation of the power system. In this paper, we discuss how the potential of a fleet of battery-electric transportation vehicles can be used to provide frequency containment reserve. To this end, we first examine the use case in detail and then present the system designed

In the context of a pilot project, the Lugaggia Innovation Community (LIC), we address the problem of non-intrusive load monitoring for the purpose of demand side management on low voltage grids in presence of distributed power generation (photovoltaic). From the power readings of smart meters, we estimate the photovoltaic production and detect the activation of major loads (heatpumps and domestic

The transition of the power grid requires new technologies and methodologies, which can only be developed and tested in simulations. Especially larger simulation setups with many levels of detail can become quite slow. Therefore, the number of possible simulation evaluations decreases. One solution to overcome this issue is to use surrogate models, i. e., data-driven approximations of (sub)systems

In this paper, a thorough analysis of quantification of the heating appliances’ flexibility provided by 200 households located in the Sion area (Switzerland) is presented. An extended evaluation of the available flexibility throughout the year as well as a correlation analysis between the outside temperature and flexibility is performed. The influence of pooling households in the prediction process

To face the challenges of climate change, the integration of renewable energy sources in the energy-intensive heating sector is a crucial aspect of emission reduction. For an efficient operation of coupling devices such as heat pumps with intermittent sources of renewable energy, accurate heat load forecasts need to be developed and embedded into an operation strategy to enable further decarbonisation

Heat pumps embody solutions that heat or cool buildings effectively and sustainably, with zero emissions at the place of installation. As they pose significant load on the power grid, knowledge on their existence is crucial for grid operators, e.g., to forecast load and to plan grid operation. Further details, like the thermal reservoir (ground or air source) or the age of a heat pump installation

The development of efficient electric vehicle (EV) charging infrastructure requires modelling of consumer demand at an appropriate level of detail. Since only limited information about real customers is available, most simulations employ a stochastic approach by combining known or estimated business features (e.g. arrival and departure time, requested amount of energy) with random variations. However

This paper introduces a framework for agent based autonomous charging and discharging of Battery Electric Vehicle (BEV) at local energy communities. Agents are programmed to control the bidirectional charging according to green energy utilisation incentives, based on load and generation forecasts. The optimization is achieved within a group of independent prosumers following a fully distributed approach

Modern power systems are cyber-physical systems with increasing relevance and influence of information and communication technology. This influence comprises all processes, functional, and non-functional aspects like functional correctness, safety, security, and reliability. An example of a process is the data acquisition process. Questions focused in this paper are, first, how one can trust in process

Increasing interdependencies between power and ICT systems amplify the possibility of cascading failures. Resilience against such failures is an essential property of modern and sustainable power systems and networks. To assess the resilience and predict the behaviour of a system consisting of interdependent subsystems, the interconnection requires adequate modeling. This work presents an approach

The integration of ICT into power systems has increased the interdependencies between the two systems. The operation of power system depends on several ICT-enabled grid services which manifest the interdependencies. ENTSO-E system state classification is a tool that is widely used by operators to determine the current operational state of the power system. However, it does not adequately describe the

Electrical networks of transmission system operators are mostly built up as isolated networks without access to the Internet. With the increasing popularity of smart grids, securing the communication network has become more important to avoid cyber-attacks that could result in possible power outages. For misuse detection, signature-based approaches are already in use and special rules for a wide range

In the battle against climate change, electrification plays an increasingly large role in our society. The growing use of electricity networks requires advanced coordination mechanisms to avoid the tragedy of the commons. In this paper, we explore the effects of optimum time-dependent pricing (TDP) on supplier surplus within electricity markets, using a parameterized optimization model. Varying not

In this work, we study the performance of a distributed optimal power flow control algorithm with respect to realistic communication quality of service. By making use of a communication network simulator, namely “GNS3”, we created a framework that simulates both the controllers involved in the optimal power flow algorithm and the communication between them. Using this platform, we investigate and give

Both rising and more volatile energy prices are strong incentives for manufacturing companies to become more energy-efficient and flexible. A promising approach is the intelligent control of Industrial Energy Supply Systems (IESS), which provide various energy services to industrial production facilities and machines. Due to the high complexity of such systems widespread conventional control approaches

Dear readers, The recent environmental and societal developments, in particular, the climate change happening more and more visible to larger parts of the society and also the COVID-19 pandemic has shown that changes in society, economy and all other energy-usage areas of our societies are needed but also possible. At the same time, we have also seen the new rise of AI / Informatics, which is now considered

This paper presents a novel Non-Intrusive Load Monitoring (NILM) approach focusing on the Energy Efficiency (EE) assessment of residential appliances. This approach (NILMEE) is able to identify the individual consumption of several household devices, providing proper information for evaluating energy efficiency and pointing out the operational issues or labelling mismatches of appliances, while recommending

Load identification is an essential step in Non-Intrusive Load Monitoring (NILM), a process of estimating the power consumption of individual appliances using only whole-house aggregate consumption. Such estimates can help consumers and utility companies improve load management and save power. Current state-of-the-art methods for load identification generally use either steady state or transient features

The vision of the future Smart Grid considers end-users connected to it as both consuming and generating energy. Equipped with small-scale renewable energy generators and storage systems, end-users, also known as prosumers, engage in a local energy market for procuring and selling energy, in turn disrupting the traditional utility model. The appeal of this vision lies in the engagement of end-users

Data centres have been the focus of research as candidates for demand response or other demand side management programs for quite some time. However, a complete framework optimising data centre demand response is still missing. This is due to the complexity of integrating more than one power flexibility technology and more than one market for power flexibility. In the presented work, this challenge

With the increased penetration of distributed renewable energy sources (DRES) in the grid, new pathways are required to keep the electricity distribution system stable. The provision of ancillary services (AS) by the DRES can contribute in this regard. However, it is necessary to communicate the need for AS from the third party providers such as distribution system operator (DSO) to the DRES in an

The big data revolution is heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities. Big data technologies have become essential to the functioning of cities. Consequently, urban processes and practices are becoming highly responsive to a form of data-driven urbanism that is the key mode of production for smart cities. Such form is increasingly

Ecological urbanism is seen today as one of the keys towards unlocking the quest for a low-carbon or fossil fuel–free society. Global and local policies promote and advocate the eco–city as the most environmentally sound model of sustainable urbanism. It is argued that the eco–city strategies and solutions are expected to deliver positive outcomes in terms of minimal demand on energy resources and

The production of electrical energy has always been a subject of debate to fight against climate change and preserve natural resources. Several countries, including Morocco, have proposed ambitious policies to develop renewable energy sources of production in the short and medium term. The major problem of renewable sources production is their intermittent nature. Using storage units, particularly

A growing demand in sustainable energy harvested from renewable resources, such as wind or solar power, leads to new challenges in the electricity grid, which in future is also referred to as the smart grid. This also reflects in a more decentralized and diverse energy market. In such a market, prices do not only depend on production and demand, but also the source of energy production influences the

Mass adoption of battery electric vehicles (BEVs) and their associated charging requirements introduce new electricity demand, which needs to be managed to minimise electricity grid upgrades. Management of BEV charging requires coordination and communication between various mobility and energy entities. Communication protocols provide a set of rules and guidelines to facilitate the communication and

The electric vehicles (EV) market is projected to continue its rapid growth, which will profoundly impact the demand on the electricity network requiring costly network reinforcements unless EV charging is properly managed. However, as well as importing electricity from the grid, EVs also have the potential to export electricity through vehicle-to-grid (V2G) technology, which can help balance supply

The smart grid achieves bidirectional information and energy flow between energy consumer and utility grid, aiding energy users not only to utilize energy, but also to produce, sell, and share energy with other consumers or with the utility grid. This type of energy user is referred to as the “prosumer”. Thus, prosumer management structures are important within energy market. However, prior studies

Business ecosystem is popularly used to investigate a complex social system with the business perspective, and particularly contributes to the understanding of actors and their relations in the innovation research. However, the aspect of business ecosystem modeling is limited discussed in the literature, although the importance has emerged significantly in recent years due to the emphasis on cross-disciplinary

Power grids are becoming increasingly intelligent. In this regard, they benefit considerably from the information technology (IT) networks coupled with their underlying operational technology (OT) networks. While IT networks provide sufficient controllability and observability of power grid assets such as voltage and reactive power controllers, distributed energy resources, among others, they make

The number of electric vehicles (EVs) is steadily growing. This provides a promising opportunity for balancing the smart grid of the future, because vehicle-to-grid (V2G) systems can utilize the batteries of plugged-in EVs as much needed distributed energy storage: In times of high production and low demand the excess energy in the grid is stored in the EVs’ batteries, while peaks in demand are mitigated

Communicating the energetic flexibility of distributed energy resources (DERs) is a key requirement for enabling explicit and targeted requests to steer their behavior. The approach presented in this paper allows the generation of load profiles that are likely to be feasible, which means the load profiles can be reproduced by the respective DERs. It also allows to conduct a targeted search for specific

In Germany and many other countries the energy market has been subject to significant changes. Instead of only a few large-scale producers that serve aggregated consumers, a shift towards regenerative energy sources is taking place. Energy systems are increasingly being made more flexible by decentralised producers and storage facilities, i.e. many consumers are also producers. The aggregation of producers

Dear readers, With increasingly more ambitious and necessary climate goals, the role of Energy Informatics as an interdisciplinary research field has become more pronounced. The DACH+ Energy Informatics conference aims at bringing together researchers and practitioners from the areas of energy systems as well as information and communication technology to present new results and discuss future research

The increasing penetration of residential photovoltaics (PV) comes with numerous challenges for distribution system operators. Technical difficulties arise when an excess of PV energy is injected into the grid, causing voltage rise or overloading of the lines. Economic challenges appear because PV owners and consumers are not participating equally in the grid costs. Indeed, PV owners benefit by self-consuming

Load management of electrical devices in residential buildings can be applied with different goals in the power grid, such as the cost optimization regarding variable electricity prices, peak load reduction or the minimization of behavioral efforts for users due to load shifting. A cooperative multi-objective optimization of consumers and generators of power has the potential to solve the simultaneity

Smart grids promise a more reliable, efficient, economically viable, and environment-friendly electricity infrastructure for the future. State estimation in smart grids plays a pivotal role in system monitoring, reliable operation, automation, and grid stabilization. However, the power consumption data collected from the users during state estimation can be privacy-sensitive. Furthermore, the topology

The constantly increasing electricity and energy demand in residential buildings, as well as the need for higher absorption rates of renewable sources of energy, demand for an increased flexibility at the end-users. This need is further reinforced by the rising numbers of residential Photovoltaic (PV) and battery-storage systems. In this case, flexibility can be viewed as the excess energy that can

Surrogate models are used to reduce the computational effort required to simulate complex systems. The power grid can be considered as such a complex system with a large number of interdependent inputs. With artificial neural networks and deep learning, it is possible to build high-dimensional approximation models. However, a large data set is also required for the training process. This paper presents

In the last years, diverse agent-based concepts for voltage control in distribution grids were presented in literature. All these approaches are developed manually. Up to now, no tailoring approach has been presented to adapt these concepts to different – likewise specific – grid situations. As the effectiveness of voltage control schemes is highly dependent on the specific grid situation, this can

An algorithm for the non-intrusive disaggregation of energy consumption into its end-uses, also known as non-intrusive appliance load monitoring (NIALM), is presented. The algorithm solves an optimisation problem where the objective is to minimise the error between the total energy consumption and the sum of the individual contributions of each appliance. The algorithm assumes that a fraction of the

The massive deployment of distributed generators from renewable sources in recent years has led to a fundamental paradigm change in terms of planning and operation of the electric power system. The usage of advanced automation and information and communication technology is a key element to handle these new challenges and to turn the traditional power system into a smart grid. The implementation of

Stimulating households to save energy with behaviour change support systems is a challenge and an opportunity to support efforts towards more sustainable energy consumption. The approaches developed so far, often either; do not consider the underlying behaviour change process in a systematic way, or do not provide a systematic linking of design elements to findings from behaviour change literature

Flow-based Market Coupling (FBMC) provides welfare gains from cross-border electricity trading by efficiently providing coupling capacity between bidding zones. In the coupled markets of Central Western Europe, common regulations define the FBMC methods, but transmission system operators keep some degrees of freedom in parts of the capacity calculation. Besides, many influencing factors define the

Due to environmental and resiliency benefits, distributed energy resources (DER) are a potential solution for meeting future electricity demand, but their integration into centralized power markets on the large scale is challenging. Many practitioners argue that blockchain technology can create new market structures for DER like local peer-to-peer energy markets which foster renewable generation. To

Historically, the power distribution grid was a passive system with limited control capabilities. Due to its increasing digitalization, this paradigm has shifted: the passive architecture of the power system itself, which includes cables, lines, and transformers, is extended by a communication infrastructure to become an active distribution grid. This transformation to an active system results from

The nationwide rollout of smart meters in private households raises privacy concerns: Is it possible to extract privacy-sensitive information from a household’s power consumption? For a small sample of 869 Upper Austrian households, information about consumption-heavy amenities and household characteristics are available. This work studies the detection of households with swimming pools (the most common

The integration of decentralized prosumers into current energy systems leads to continuously increasing complexity in today‘s popular term of the Smart Grid. Since conventional engineering methods reach their limits when dealing with the challenges in developing such systems, model-driven approaches like Domain Specific Systems Engineering (DSSE) gain significant importance. Contributing to the agile

Power system automation is heavily dependent on the reliable interconnection of power system field equipment and centralised control applications. Particularly important to achieve reliability in automated power systems is the redundant connection of field equipment controllers. Today, the fundamental redundancy management and switch-over processes are handled by the power system control applications

The management and transmission networks is becoming increasingly complex due to the proliferation of renewables-based distributed energy resources (DER). Existing control systems for DER are based on static specifications from interdependent network connection documents. Such systems are inflexible and their maintenance requires concerted effort between grid stakeholders. In this paper we present

In this paper we present insights drawn from recent research projects aimed at developing visualization and gamification tools to stimulate individual behaviour change and promote energy and water saving. We address both the design of resource-saving programmes and the methodologies to assess their effectiveness. We conclude by presenting a vision for the future and discussing open issues that could

The rising demand for sustainable energy requires to identify the sites for photovoltaic systems with the best performance. This paper tackles the question of feasibility of photovoltaic power plants at high altitude. A direct comparison between an alpine and an urban area site is conducted in the south of Austria. Two low-cost automatic photovoltaic power measurement devices with dual-axis sun tracking

The analysis of electrical load signatures is an enabling technology for many applications, such as ambient assisted living or energy-saving recommendations. Through the digitalization of electricity metering infrastructure, meter reading intervals are gradually becoming more frequent than the traditional once-per-year reporting. In fact, across smart meter generations, samples were initially reported

Optimizing energy consumption in local energy communities is one of the key contributions to the so-called smart grid. Such communities are equipped with rooftop photovoltaic power plants or other forms of small power plants for local energy production. In addition, a number of appliances allow for shiftable energy consumption, e.g., heat pumps or electric vehicle charging stations. The ability to

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