Software-intensive systems interoperability in Smart Grids: A semantic approach

Espinoza, Angelina; Ortega, Mariano; Fernández, Carlos Morón; Garbajosa, Juan; Alvarez, Alejandro

doi:10.1109/indin.2011.6034984

Cited by 7 publications

(9 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fully exploiting the possibilities that this intelligence allows includes, for instance, advanced processing and reasoning on huge data streams (expressed in RDF triplets) as shown in [16,22]. Future works will aim to refine the distributed service discovery and determine the physical limits of the PGDIN's processing event streams.…”

Section: Discussionmentioning

confidence: 99%

“…The major domain authorities (EPRI and IEC, the International Electro-technical Commission) have backed the development of a central smart grid standard, the so-called CIM (Common Information Model, [18]) and, then, defined its OWL model, laying the foundations for many research projects that have extended the CIM to include related electric protocols [19], combined the CIM ontology with other protocols' ontologies to achieve interoperability [20], etc. The EPRI has issued a number of recommendations to carry out this harmonisation, which could be implemented through OWL language assertions, once both data models are converted to its semantic form, thus also allowing us to perform automatic reasoning and inference processes [21][22][23].…”

Section: Power Network Nowadaysmentioning

confidence: 99%

“…The aforementioned OWL-DL ontology enables the PGDIN to deal with a unified domain that combines all concerning standards. In order to be able to cope with all the requirements discussed before, the PGDIN is composed of the following modules and technology interfaces (the rationale of choosing the technologies presented next has been discussed and justified in [16,[21][22][23]), as shown in Figure 1.…”

Section: System Architecturementioning

confidence: 99%

See 2 more Smart Citations

Distributed Semantic Architecture for Smart Grids

et al. 2012

Self Cite

View full text Add to dashboard Cite

The smart grid revolution demands a huge effort in redesigning and enhancing current power networks, as well as integrating emerging scenarios such as distributed generation, renewable energies or the electric vehicle. This novel situation will cause a huge flood of data that can only be handled, processed and exploited in real-time with the help of cutting-edge ICT (Information and Communication Technologies). We present here a new architecture that, contrary to the previous centralised and static model, distributes the intelligence all over the grid by means of individual intelligent nodes controlling a number of electric assets. The nodes own a profile of the standard smart grid ontology stored in the knowledge base with the inferred information about their environment in RDF triples. Since the system does not have a central registry or a service directory, the connectivity emerges from the view of the world semantically encoded by each individual intelligent node (i.e., profile + inferred information). We have described a use-case both with and without real-time requirements to illustrate and validate this novel approach.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Power Network Nowadaysmentioning

confidence: 99%

Section: System Architecturementioning

confidence: 99%

See 1 more Smart Citation

Distributed Semantic Architecture for Smart Grids

et al. 2012

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, some authors consider the use of ontologies in context aware environments to be very sensitive to the size of the dataset and unreasonable to use for time-critical applications [8]. Similarly, in [3], the authors have reported a limitation in semantic processing, where the reasoner and rule engine would not be able to perform in realtime when applied to the full semantics model. We too are skeptical about the performance in scenarios of Smart City where the context data are of large size, constantly changing, and often incomplete.…”

Section: Information and Communications Technologymentioning

confidence: 99%

“…As a result, an ontology-based semantic model has become prevalent in the area of context aware and Smart City technologies [1,12,14]. Nonetheless, semantic processing is not capable of managing such vast amounts of data, as are expected in the Smart City scenario, in realtime [1,2,3,8]. Furthermore, in [10], the call for application of Big Data technology in Smart Grid analytics is emphasized and, as suggested in [11], cloud delivery of energy management solutions is largely becoming an accepted approach.…”

Section: Introductionmentioning

confidence: 99%

Big Data in Large Scale Intelligent Smart City Installations

Girtelschmid

Steinbauer

Kumar

et al. 2013

Proceedings of International Conference on Information Integration and Web-Based Applications &Amp; Services

View full text Add to dashboard Cite

This paper highlights how the domain of Smart Cities is often modeled by ontologies to create applications and services that are highly flexible, (re)configurable, and inter-operable. However, ontology repositories and their accompanying reasoning and rule languages face the disadvantage of bad runtime behavior, especially if the models grow large in size. We propose an architecture that uses tools and methods from the domain of Big Data processing in conjunction with an ontology repository and a rule engine to overcome potential performance bottlenecks that will occur in this scenario.

show abstract

On the application of Big Data in future large-scale intelligent Smart City installations

Girtelschmid

Steinbauer

Kumar

et al. 2014

International Journal of Pervasive Computing and Communications

View full text Add to dashboard Cite

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The purpose of this article is to propose and evaluate a novel system architecture for Smart City applications which uses ontology reasoning and a distributed stream processing framework on the cloud. In the domain of Smart City, often methodologies of semantic modeling and automated inference are applied. However, semantic models often face performance problems when applied in large scale. Design/methodology/approach -The problem domain is addressed by using methods from Big Data processing in combination with semantic models. The architecture is designed in a way that for the Smart City model still traditional semantic models and rule engines can be used. However, sensor data occurring at such Smart Cities are pre-processed by a Big Data streaming platform to lower the workload to be processed by the rule engine. Findings -By creating a real-world implementation of the proposed architecture and running simulations of Smart Cities of different sizes, on top of this implementation, the authors found that the combination of Big Data streaming platforms with semantic reasoning is a valid approach to the problem. Research limitations/implications -In this article, real-world sensor data from only two buildings were extrapolated for the simulations. Obviously, real-world scenarios will have a more complex set of sensor input values, which needs to be addressed in future work. Originality/value -The simulations show that merely using a streaming platform as a buffer for sensor input values already increases the sensor data throughput and that by applying intelligent filtering in the streaming platform, the actual number of rule executions can be limited to a minimum.

show abstract

Software-intensive systems interoperability in Smart Grids: A semantic approach

Cited by 7 publications

References 2 publications

Distributed Semantic Architecture for Smart Grids

Distributed Semantic Architecture for Smart Grids

Big Data in Large Scale Intelligent Smart City Installations

On the application of Big Data in future large-scale intelligent Smart City installations

Contact Info

Product

Resources

About