{"id":23473,"date":"2023-02-06T13:59:12","date_gmt":"2023-02-06T18:59:12","guid":{"rendered":"https:\/\/www.parsons.com\/?p=23473"},"modified":"2023-05-31T17:21:01","modified_gmt":"2023-05-31T21:21:01","slug":"the-distribution-digital-twin-a-key-enabler-of-grid-modernization","status":"publish","type":"post","link":"https:\/\/www.parsons.com\/2023\/02\/the-distribution-digital-twin-a-key-enabler-of-grid-modernization\/","title":{"rendered":"The Distribution Digital Twin \u2013 A Key Enabler Of Grid Modernization"},"content":{"rendered":"\n
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This is the fifth in my series of articles focused on the <\/em>Modernization of the Electric Grid<\/em><\/a>. This chapter extends the discussion from the previous article on the distribution system, and in particular the importance of a critical technology used in the planning, development, operation and maintenance of the system – the Digital Twin.<\/em><\/p>\n\n\n\n

One of the most exciting, and rapidly advancing, technologies today is the Digital Twin (DT or Twin). The concept has wide application for industrial plants (manufacturing, oil and gas wells, refineries, generation stations), transportation infrastructure, military bases, and of course, utilities. The renewed emphasis on national infrastructure improvement and upgrades has many industries looking for new ways to most efficiently plan and manage these huge investments. In addition, asset owners seek better ways to document and maintain the information associated with these large scale infrastructure investments. <\/p>\n\n\n

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Parsons, for example, in partnership with a DT technology company, is supporting one of the largest airports in the Country with their first effort to create a modern digital twin of a recently renovated terminal, runway, and central utility plant. The airport will be better able to visualize and support asset operations as it also begins integrating more of its asset and information systems with the new platform.<\/p>\n\n\n\n

Digital twin is a relatively new term in the electric transmission and distribution (T&D) industry, building on the traditional concepts of maps, schematics and simple computer-based models. The modern digital twin not only encompasses a \u201cdigital\u201d version of traditional \u201cone-line\u201d and \u201cthree-line\u201d schematics and maps. It can also incorporate a full 3 dimensional (3D) geospatial model of the energized lines and equipment AND the structures supporting them. Electric power substations, for example, typically contain a lot of equipment, conductors, and control wiring packed into a relatively small space (though some substations are pretty huge!). The compact nature of the substation makes accurate measurement of clearances between equipment, steelwork, and conductor bus pipes critically important for reliability and worker safety. This is where a highly accurate 3D model of everything<\/em> in the station can be extremely helpful for design engineers planning expansions, removals, or replacements of equipment.<\/p>\n\n\n\n

Another, and I would argue more important, component of the digital twin is the tremendous amount of data related to all the underlying elements of the model, the asset ontology (relationship between the assets), AND the relationships between the elements and data sources. Aside from the myriad detailed attributes of each model element, the digital twin can include historical (and planned) model changes, equipment maintenance and inspection records, and live sensor data streams with measurement and status information from all across the grid. Even customer information, like how much power is consumed or supplied to the grid, can be part of the digital twin.<\/p>\n\n\n\n

In the last blog article<\/a>, I discussed several Information Technology (IT) systems that are becoming very important enablers of grid modernization. Advanced Distribution Management Systems (ADMS), Volt-Var Optimization (VVO) systems, and Distributed Energy Resource Management Systems (DERMS) all rely to some extent on elements of the distribution digital twin model. An accurate twin, important for the creation of these grid management systems, will indeed be critical for the safe and secure operation of the grid itself. Systems like an ADMS will have a \u201cstudy mode\u201d environment (a twin of the live model) used to check whether proposed changes or additions to grid configuration will work as planned. DERMS platforms will have similar environments to test demand response and DER dispatch events prior to initiation. In addition, all these systems will require robust cybersecurity algorithms, constantly monitoring thousands of sensors across the grid for live measurements and status, instantly alerting for unexpected conditions, or voltage or power levels that fall outside of expected tolerance ranges at any location. The configuration of the grid, as well as the physical and electrical locations of all sensors must be modeled exactly in the twin. This will make an accurate digital twin a truly mission critical<\/em> requirement.<\/p>\n\n\n

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Another system that has become a very common customer-facing tool for many electric utilities is the Distributed Generation (DG) Hosting Capacity Map. This visual, geographic representation of the distribution system provides customers, regulators, legislators, and DG developers basic information about where siting DG resources will be least difficult (in other words, least expensive) for the grid to accommodate. The map display requires, at the least, a reasonably accurate GIS and distribution circuit-level knowledge of installed (and planned) DG connected to the system. It can be fairly simple in design, and in most cases today the maps are, but there can also be a tremendous amount of information and processing going on to create that display depending on the desire for accuracy and the ability to successfully produce that accuracy from elements of the digital twin. There are also powerful opportunities emerging to enhance the display to provide much more than just \u201chosting capacity\u201d. Eventually, these maps will be able to inform where DERs can actually provide benefit to the grid. They can also be more interactive and help determine what capacity and mix of DERs (e.g., solar PV and battery storage) will provide the most<\/em><\/strong> benefit at any given location.<\/p>\n\n\n\n

The engineering tools exist today to perform this type of analysis, and programming tools can be leveraged to automate the process. However, the most significant barrier to the implementation of systems like this (as well as ADMS, VVO, and DERMS) lies in the myriad details of the source databases required by these systems. The electric distribution digital twin, as it exists today in most electric utilities, is still far from being a complete and fully integrated system. The importance of accurate data sources, and the ability to create reliable connections between these sources, is being more acutely recognized by utilities every day as they try to meet the growing expectations of customers and regulators. In the process of implementing these new IT systems, the gaps in critical data sources, and especially the lack of automated connections between them, become obvious and cause delays and cost overruns. That is beginning to change, as this need for a better grid digital twin is impacted by the same forces pushing modernization of the actual grid. <\/p>\n\n\n\n

Some of the key data sources making up the distribution digital twin are as follows:<\/p>\n\n\n\n