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NETWORK / 19 / JUNE 2018 traditional power generation. As a foundation for simulation and predictive analysis, utilities systems are expanding their capabilities to include support for DER. Due to the nature of DERs, utilities are not always able to control how or when these resources are connected. Or- ganisations are implementing microgrids to meet their own re- quirements for high availability rather than relying on the utility. Digitalisation of the operation Network management systems have become more sophisti- cated, enabling data tracking, advanced decision support, and operational analytics. Using high volumes of digital data from many devices and integrat - ing information technologies (IT) and operational tech- nologies (OT) with engineering systems provides the basis to create a digital view of a utility. Combined with reality data from laser scans and high-resolution photography, this "digital twin" utilises powerful capabilities for reliability analysis and design optimisation. These capabilities are critical whether in response to unplanned external events or the need to evaluate design op - tions for future system changes in both greenfield and brown- field situations. As DERs grow in usage, the grid is concurrently becoming more populated with sensing and actuating devices as part of the process of digitalisa - tion, or the process of moving to a digital business. A digital representation of the grid is vis- ible at its fullest extension and will provide massive volumes of data that can be used to better understand grid perfor - mance currently, previously, and potentially in the future. By combining algorithms and simulation capabilities with the digital representation, a "digital twin" is created. Though digital twins have been around for a long time, IoT has ensured that digital twin implementation is now cost-effective. work reliability study, network models from a GIS, combined with asset lifecycle informa - tion, were used by a planning engineer to examine unreli- able networks and improve maintenance. Furthermore, this approach can improve network modelling by determining where new DER will be most effective. Interoperability with the CDE can help identify optimum grid connection points. CDE critical for efficient management of DER Using asset lifecycle informa- tion to plan an asset's reliability bolsters the value of network data because it is relied on from the engineering design phase to the analysis domain. This use of asset lifecycle information also demonstrates why interoper - ability with the CDE is critical for efficient management of a decentralised grid. A utility will have regulatory and related internal standards for network design, including operating criteria, load condi - tions, failure modes, and digital catalogs of approved construc- tion components that define and guide how planning and design is performed and what parts are usable. Without a CDE, imple - mentation and management of the many interfaces become challenging IT problems when facing a decentralised grid. Simulation uses digitalisa - tion to model the current grid or show the grid with proposed grid changes. AŽer identifying a connection point, the analyst needs to understand how the new DER will affect the network. A model of the DER is connected to a digital representation of the network and algorithms are applied to simulate network op- eration under varied conditions. This is done in the design stage. Predictive analytics is an- other capability that is essential in a network model that sup- ports DER. The goal of predic- tive analysis is to find problems before they occur at a reason- able cost. The historical and real-time data available through a CDE can make seeing trends and understanding anomalies difficult without the necessary capabilities to track, analyse, and report important events, es - pecially in a decentralised grid populated with large numbers of DERs and IoT devices. Analyt- ics can provide perspectives of the event that help determine whether a change is a symptom or a cause. Conclusion As utilities face huge changes and work to adjust all aspects of their business with the integra- tion of DERs, agile approaches to technology and information management will assist in goal achievement. To embrace the digitalisation process, lead - ers need to emphasise the importance of the CDE, the need for integrated engineering and analysis, and the value of predictive analytics. In addition, new approaches to network modelling must be adopted to handle the new world of distrib - uted generation. As costs reduce and DERs grow in popularity, it is important to the grid that DER integration, and not just con - nection, is carried out smoothly and reliably to the benefit of the utility and the customer. Incorporating DERs into the digital twin is one way of easing them into the grid at the design phase. Once implemented, DERs can be monitored in the same way as the rest of the grid to as- sess reliability and performance. Then, DERs become truly beneficial because they ease the burden of the central grid. Big data must contain an information model that docu- ments the grid assets and main- tains their status at any point in time. Asset lifecycle manage- ment documents when and where the asset was installed, its maintenance and service record, and other key informa- tion required for comprehensive asset stewardship. Speaking a common language To make digitalisation worth- while, systems must be able to share information seamlessly. Therefore, systems should interoperate through a CDE. Reliability analysis, compli - ance and safety reporting, and operational analytics are core functions needed for asset stewardship, and they involve multiple database components and systems. Through enter - prise interoperability based on industry standards, data can be instantly available. The IEC Common Informa - tion Model (CIM) is important to interoperability. CIM derives from the standards for distribu- tion, transmission, and energy markets. It provides a common language for communication between utility systems within the industry and with external entities. Proprietary interfaces that have been standardised and made public are just as impor - tant for interoperability because they are able to export and import data from other systems and are transparent. In a net -