In modern distribution grids, the access to the growing amount of data from various sources, the execution of complex algorithms on-demand, and the control of sparse actuators require on-demand scalability to support fluctuating workloads. Cloud computing technologies represent a viable solution for these requirements. To ensure that data can be exchanged and shared efficiently, as well as the full achievement of the cloud computing benefits to support the advanced analytic and mining required in smart grids, applications can be empowered with semantic information integration. This paper adopts the semantic web into a cloud-based platform to analyse power distribution grids data and apply a service restoration application to re-energize loads after an electrical fault. The exemplary implementation of the demo is powered by FIWARE, which is based on open-source and customizable building blocks for future internet applications and services, and the SARGON ontology for the energy domain. The tests are deployed by integrating the semantic information, based on the IEC 61850 data model, in the cloud-based service restoration application and interfacing the field devices of the distribution grids. The platform performances, measured as network latency and computation time, ensures the feasibility of the proposed solution, constituting a reference for the next deployments of smart energy platforms.

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In modern distribution grids, the access to the growing amount of data from various sources, the execution of complex algorithms on-demand, and the control of sparse actuators require on-demand scalability to support fluctuating workloads. Cloud computing technologies represent a viable solution for these requirements. To ensure that data can be exchanged and shared efficiently, as well as the full achievement of the cloud computing benefits to support the advanced analytic and mining required in smart grids, applications can be empowered with semantic information integration. This paper adopts the semantic web into a cloud-based platform to analyse power distribution grids data and apply a service restoration application to re-energize loads after an electrical fault. The exemplary implementation of the demo is powered by FIWARE, which is based on open-source and customizable building blocks for future internet applications and services, and the SARGON ontology for the energy domain. The tests are deployed by integrating the semantic information, based on the IEC 61850 data model, in the cloud-based service restoration application and interfacing the field devices of the distribution grids. The platform performances, measured as network latency and computation time, ensures the feasibility of the proposed solution, constituting a reference for the next deployments of smart energy platforms.

In a modern smart energy system, the amount of available data from various sources is growing significantly. Other sectors such as medical or social sectors exhibit the same phenomenon. Due to the amount, complexity and heterogeneity of data, a complex algorithm is required for the integration and analysis of heterogeneous data sources. The Web of Things and semantic-based approaches address the fragmentation of standards, platforms, services and technologies in smart energy and non-energy sectors, and enable heterogeneous data integration and interoperability. This paper presents SiSEG, a semantic annotation service that is developed to automate the process of annotating data and address the problem of heterogeneous data integration in a reusable and extensible way by using the fuzzy method. Moreover, the accuracy of SiGEG has been evaluated.

Due to the increasing complexity of the global energy system and the amount of data transmitted by smart devices, there is an urgent need to unlock smart technologies and sendees with investments on the scalability of computational resources. This objective can be achieved by means of a standardized software platform that can support interoperability and behave as the main vehicle for the rapid implementation of innovative energy sendees. One possibility to enhance computational power on demand is cloud computing, which forms the Internet of Things (IoT). In this work, a customizable open-source IoT platform setup using the FIWARE framework is deployed, which exploits the advantages for a smart energy domain. The term platform comprehends a set of software tools that allow quick integration of various devices. This study presents the implemented platform and analyses its functionality in different use cases on the European level.