by Matias Almeida Garzon
The application of common information models has increased among European utilities. Four years ago, SSEN started exploring the CIM model applied to asset management. In a conversation with Neil Meredith, he was generous enough to share the company’s CIM architecture featuring the Maximo platform for asset and work management and the Data Model for Energy and Utilities (DMEU)
The goal of the integration strategy was drafted around the principle of formulating and implementing a CIM-based common messaging model able to process information from the entire network’s assets, including GIS, ADMS, CBRM, etc. After the data has been “translated” into a common semantic representation in the integration layer, it can be visualised and used in the Maximo platform.
As Meredith explains, the remaining challenge is tracking the date route from the origin to the intended source. The engineering team is able to personalise each CIM profile according to their needs. This is why the key resides in having operational knowledge of both business expertise of the electrical network model and IT knowledge of UML modelling.
A second part of these activities relates to what the company has denominated as a common network model (CNM). The underlying intentions behind this were to provide transparency and open access to data by digitising the networks’ information. This platform accurately represents the distribution network through the electrical connectivity model. Available information includes assets, operations, outages, etc. This is enabled by a CIM-inspired logical data model known as the data model for energy and utilities (DMEU).
Considering the increased digitalisation trend in the power grid, gaining theoretical knowledge about the advantage of CIM frameworks to manage multiple assets. The CIM Fundamentals online training programme, created by Smart Grid Forums, is designed to provide industry professionals with the necessary skills across 12 weeks.
➡️Click on the link below to learn more about the programme:
https://hubs.li/Q01LRXS60
➡️To read the research document, visit:
https://shorturl.at/inOU2