• Preprint 230

Technical Report 230, c4e-Preprint Series, Cambridge

OntoPowerSys: A Power Systems Ontology for Cross Domain Interactions in an Eco Industrial Park

Authors: Aravind Devanand, Gourab Karmakar, Nenad Krdzavac, Leonardus Kevin Aditya, Rémy Rigo-Mariani, Ashok Krishnan, Eddy Y.S. Foo, Iftekhar A. Karimi, and Markus Kraft*

Reference: Technical Report 230, c4e-Preprint Series, Cambridge, 2019

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Highlights
  • A domain ontology for power systems in an Eco Industrial Park.
  • Implementation of the ontology as a Knowledge Management System of J-Park Simulator.
  • Application of the ontology for the automated generation of grid topology.
  • Application of the ontology for studying cross domain interactions in a biodiesel plant.
Abstract

Graphical abstract Knowledge management in multi-domain, heterogeneous industrial networks like an Eco Industrial Park (EIP) is a challenging task. In the present paper, an ontology based management system has been proposed for tackling this challenge. It focuses on the power systems domain and provides a framework for integrating this knowledge with other domains of an EIP. The proposed ontology, OntoPowSys is expressed using a Description Logics (DL) syntax and OWL2 language was used to make it alive. It is then used as a part of the Knowledge Management System (KMS) in a virtual EIP called the J-Park Simulator (JPS). The advantages of the proposed approach are demonstrated by conducting two case studies on the JPS. The first case study illustrates the application of Optimum Power Flow (OPF) in the electrical network of the JPS. The second case study plays an important role in understanding the cross domain interactions between chemical and electrical engineering domains in a biodiesel plant of the JPS. These case studies are available as web services on the JPS website. The results showcase the advantages of using ontologies in the development of decision support tools. These tools are capable of taking into account contextual information on top of data during their decision making process. They are also able to exchange knowledge across different domains without the need for a communication interface.

Material from this preprint has been published in Energy and AI.

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