Ontology Modeling for Decentralized Household Energy Systems

@article{Wu2021OntologyMF,
  title={Ontology Modeling for Decentralized Household Energy Systems},
  author={Jian-tao Wu and Fabrizio Orlandi and Tarek Alskaif and Declan O’Sullivan and Soumyabrata Dev},
  journal={2021 International Conference on Smart Energy Systems and Technologies (SEST)},
  year={2021},
  pages={1-6}
}
  • Jian-tao Wu, F. Orlandi, Soumyabrata Dev
  • Published 3 August 2021
  • Computer Science, Engineering
  • 2021 International Conference on Smart Energy Systems and Technologies (SEST)
In a decentralized household energy system consisting of various devices such as washing machines, heat pumps, and solar panels, understanding the electric energy consumption and production data at the granularity of the device helps end-users be closer to the system and further achieve the sustainability of energy use. However, many datasets in this area are isolated from other domains with records of only energy-related data. This may raise a loss of information (e.g. weather) that is… 
3 Citations

Figures and Tables from this paper

Detecting Rainfall Events Leveraging Climate Knowledge Graphs

TLDR
This paper utilizes the recently created knowledge graph about climate observations as a use case to create a work ow for scholars to facilitate the extraction of climate data from any knowledge graph for automated conversion from graph-form data to tabular- form data suitable for feeding into machine learning models.

References

SHOWING 1-10 OF 23 REFERENCES

Interlinking Heterogeneous Data for Smart Energy Systems

TLDR
This work proposes an approach based on Web (W3C) standards and Linked Data technologies for representing and converting PV and weather records into an Resource Description Framework (RDF) graph-based data format that is ideal in a data integration scenario where data needs to be converted into homogeneous form and different datasets could be interlinked for distributed analysis.

A Clustering Framework for Residential Electric Demand Profiles

TLDR
A novel objective validation strategy is proposed, whose recommendations are then cross-verified by performed subjective validation by performing subjective validation of the electric demand profiles of individual households located in the city Amsterdam, the Netherlands.

An Ontology Model for Climatic Data Analysis

TLDR
The idea of this work is to convert relational climate data to the Resource Description Framework (RDF) data model, so that it can be stored in a graph database and easily accessed through the Web as Linked Data.

Validating Clustering Frameworks for Electric Load Demand Profiles

TLDR
The proposed scheme considers all the steps prior to the clustering algorithm, including the pre-processing and dimensionality reduction steps, in order to provide recommendations over the complete framework to provide better, unbiased, and uniform recommendations as compared to the standard Clustering Validity Indices.

The SEAS Knowledge Model

TLDR
This deliverable describes the SEAS Knowledge Model as a basis for semantic interoperability in the SEas ecosystem as well as an innovative Web ontology designed to meet the current best practices in terms of quality, metadata, and publication.

Planned ETSI SAREF Extensions based on the W3C&OGC SOSA/SSN-compatible SEAS Ontology Pattern

TLDR
These planned additions to SAREF will ease its adoption and extension by industrial stake-holder, while ensuring easy maintenance of its quality, coherence, and modularity.