Applying the Smart Grid Architecture Model for Designing and Validating System-of-Systems in the Power and Energy Domain: A European Perspective

Uslar, Mathias; Rohjans, Sebastian; Neureiter, Christian; Andrén, Filip; Velásquez, Jorge; Steinbrink, Cornelius; Efthymiou, Venizelos; Migliavacca, Gianluigi; Horsmanheimo, Seppo; Brunner, Helfried; Strasser, Thomas

doi:10.3390/en12020258

Cited by 120 publications

(74 citation statements)

References 65 publications

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“…Despite the introduction of Information and Communication Technologies (ICT) in the power generation industry, this innovation is concentrated in central nodes and partially incorporated to remote substations, whereas remote terminals are almost entirely archaic [6]. Additionally, factors such as population growth, climate change, equipment failures, restrictions in power generation capacity, demand for resilience and the reduction of fossil fuels are identified as reason for the creation of a new infrastructure for power distribution [7].…”

Section: Introductionmentioning

confidence: 99%

A Methodology for Dependability Evaluation of Smart Grids

et al. 2019

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Smart grids are a new trend in electric power distribution, which has been guiding the digitization of electric ecosystems. These smart networks are continually being introduced in order to improve the dependability (reliability, availability) and efficiency of power grid systems. However, smart grids are often complex, composed of heterogeneous components (intelligent automation systems, Information and Communication Technologies (ICT) control systems, power systems, smart metering systems, and others). Additionally, they are organized under a hierarchical topology infrastructure demanded by priority-based services, resulting in a costly modeling and evaluation of their dependability requirements. This work explores smart grid modeling as a graph in order to propose a methodology for dependability evaluation. The methodology is based on Fault Tree formalism, where the top event is generated automatically and encompasses the hierarchical infrastructure, redundant features, load priorities, and failure and repair distribution rates of all components of a smart grid. The methodology is suitable to be applied in early design stages, making possible to evaluate instantaneous and average measurements of reliability and availability, as well as to identify eventual critical regions and components of smart grid. The study of a specific use-case of low-voltage distribution network is used for validation purposes.

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Section: Introductionmentioning

confidence: 99%

A Methodology for Dependability Evaluation of Smart Grids

et al. 2019

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“…In other words, the prosumers become the new actors in local electricity power market, considered as µM [19,20]. A different formulation of the PEST optimization follows a hierarchical framework considering the future energy price uncertainty in [21], information and communication technologies (ICT) in [22], and multi-layer architecture model in [23,24]. Paper [25] proposes a comprehensive analysis regarding the P2P communication architectures and highlights the performance of common protocols evaluated in accordance with IEEE 1547.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

et al. 2020

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A growing number of households benefit from government subsidies to install renewable generation facilities such as PV panels, used to gain independence from the grid and provide cheap energy. In the Romanian electricity market, these prosumers can sell their generation surplus only at regulated prices, back to the grid. A way to increase the number of prosumers is to allow them to make higher profit by selling this surplus back into the local network. This would also be an advantage for the consumers, who could pay less for electricity exempt from network tariffs and benefit from lower prices resulting from the competition between prosumers. One way of enabling this type of trade is to use peer-to-peer contracts traded in local markets, run at microgrid (μG) level. This paper presents a new trading platform based on smart peer-to-peer (P2P) contracts for prosumers energy surplus trading in a real local microgrid. Several trading scenarios are proposed, which give the possibility to perform trading based on participants’ locations, instantaneous active power demand, maximum daily energy demand, and the principle of first come first served implemented in an anonymous blockchain trading ledger. The developed scheme is tested on a low-voltage (LV) microgrid model to check its feasibility of deployment in a real network. A comparative analysis between the proposed scenarios, regarding traded quatities and financial benefits is performed.

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“…The platform architecture may also define the business/market layer from the Smart Grid Architecture Model (SGAM) [83]. SGAM has three dimensions: domains on the x-axis (Generation, Transmission, Distribution, Distributed Energy Resources, Customer premises), Zones of ICT-based control systems on the y-axis (Process, Field, Station, Operation, Enterprise, Market), and the Interoperability layer on the z-axis (Components, Communication Information, Function, Business).…”

Section: System Structure: the Architectural Framework Of The Ai Enermentioning

confidence: 99%

Electricity Market Empowered by Artificial Intelligence: A Platform Approach

Ahokangas

Louis

et al. 2019

Energies

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Artificial intelligence (AI) techniques and algorithms are increasingly being utilized in energy and renewable research to tackle various engineering problems. However, a majority of the AI studies in the energy domain have been focusing on solving specific technical issues. There is limited discussion on how AI can be utilized to enhance the energy system operations, particularly the electricity market, with a holistic view. The purpose of the study is to introduce the platform architectural logic that encompasses both technical and economic perspectives to the development of AI-enabled energy platforms for the future electricity market with massive and distributed renewables. A constructive and inductive approach for theory building is employed for the concept proposition of the AI energy platform by using the aggregated data from a European Union (EU) Horizon 2020 project and a Finnish national innovation project. Our results are presented as a systemic framework and high-level representation of the AI-enabled energy platform design with four integrative layers that could enable not only value provisioning but also value utilization for a distributed energy system and electricity market as the new knowledge and contribution to the extant research. Finally, the study discusses the potential use cases of the AI-enabled energy platform.

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Applying the Smart Grid Architecture Model for Designing and Validating System-of-Systems in the Power and Energy Domain: A European Perspective

Cited by 120 publications

References 65 publications

A Methodology for Dependability Evaluation of Smart Grids

A Methodology for Dependability Evaluation of Smart Grids

A New Vision on the Prosumers Energy Surplus Trading Considering Smart Peer-to-Peer Contracts

Electricity Market Empowered by Artificial Intelligence: A Platform Approach

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