Scientific Results

  • ID:
    publications-5292
  • Type:
    Book chapter
  • Year:
    2022
  • Authors:
    Sweetapple C.; Salomons E.; Le Gall F.; Abid A.; Vamvakeridou-Lyroudia L.; Chen A.S.; van den Broeke J.
  • Title:
    Integrating Epanet and FIWARE for Development of Water Distribution System Digital Twins
  • Venue/Journal:
    Springer Water
  • DOI:
    10.1007/978-981-19-1600-7_68
  • Research type:
  • Water System:
  • Technical Focus:
  • Abstract:
    Digital Twins (DTs) have significant potential in the area of water distribution system (WDS) management. However, development of DTs can be complex, with the need for any hydraulic and/or quality model to be constantly paired with data and information from multiple sources in the physical world. Transmission, conversion, validation, storage and protection of this data are all important issues, and are currently complicated by a lack of standardization. However, standardization, along with interoperability and integration are fundamental features of a successful DT. This research, therefore, aims to provide a flexible solution for integrating hydraulic and quality WDS models with heterogeneous data sources by integrating the WDS simulation toolkit, OWA-EPANET 2.2, with the cloud-based context information platform, FIWARE. To achieve this, a new open source ‘Water Network Management’ FIWARE data model is first developed to enable management of all network data in a standardized, NGSI-LD format, based on JSON-LD serialization. Secondly, an interface is developed to: (a) translate existing EPANET model data into the requisite NGSI-LD format; (b) post this to a context information broker; (c) retrieve all data necessary to generate an up-to-date network model for simulation (capturing real-time network data supplied to the context broker from other sources); and (d) as and when required, run hydraulic and quality simulations of the network. Lastly, this FIWARE-integrated implementation of EPANET is demonstrated using a small case study WDS from the South West of England, where it utilises real-time data available from 91 smart meters in the network. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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