With about 55,000 transmission substations in the U.S. and the average age of the transformers in these substations over 40 years old, many substations are going to be refurbished, retrofitted, extended or upgraded. Utilities are opting to create digital twins of their existing substations as part of this process to enable maintenance and upgrading activities to be performed more efficiently. For older substations records may consist in outdated 2D paper drawings or documents may be missing altogether. New digital scanning technology together with machine learning is making it possible to semi-automate the process of creating intelligent BIM models from point clouds derived from laser scanning or photography.
Companies are recognizing the benefits of an integrated geospatial and building information modeling (BIM) approach to design and construction. I blogged about the winner of the Year in Infrastructure 2019 award who applied BIM processes and reality modeling on a brownfield substation expansion project. The integrated approach enabled the organization to cut design time, minimize site visits, reduce land requirement and material waste, and, most importantly, eliminate change orders during construction.
Now reality capture and deep learning have been incorporated in a substation design product to semi-automate the scan-to-BIM process for brownfield substations.
primtech is a CAD-based design tool for high voltage substations. An important recent enhancement Optical Symbol Recognition (OSR) allows point clouds from laser scanning or photography to be imported and then to apply machine learning to semi-automate the process of creating an intelligent BIM model.
The software includes an extensive library, which contains more than four thousand intelligent 2D and 3D electrical devices from different manufacturers, steel structures, foundations, and wires and tubes. The library has been growing for over 15 years and includes new equipment and elements as well as for legacy assets. Each symbol (device, steel or foundation, etc.) has a specific geometric signature in the database in addition to meta data, file links, connection points and defined object behaviors. Together these comprise smart objects that enables objects in point clouds to be recognized and converted into an intelligent substation information model. The resulting intelligent model provides the basis for the calculations required in the substation engineering process.
The OSR process consists of two phases; first conductors are created and then equipment is added. A wire can be created by simply selecting three points, first anchor point, maximum sag point and end anchor point. For tubes, two or more points can be selected. Wires and tubes are available in the library for different conductor types according to international standards. After conductors has been created and placed, the OSR tool provides a list of compatible library symbols for each symbol type. It is up to the user to choose which symbol should be selected. The user can select the perfect matching symbol or another one in the list. A similar workflow applies to all the other symbols like support structures and foundation heads. The system then combines the symbols to create assemblies (electrical device, support structure, foundation head) and places them in the model. Once an assembly has been created, the OSR tool will recognize identical assemblies in the point cloud and propose it for those positions in the substation. The wires are automatically attached to the respective electrical connection points on the equipment upon the insertion of the assemblies. After the OSR tool has examined all objects in the point cloud and they have been mapped to an assembly in the model, a logical and intelligent primtech BIM model has been created. The model can be used as a full-fledged template for extension or retrofit - to create parts lists and plans as well as to carry out calculations including phase checking, clearance calculation, lightning protection calculation, sag and short-circuit effects calculations.
The new OSR technology is not fully automatic but drastically improves efficiency and reliability of converting point clouds into intelligent 3D models.This is an important advance that could dramatically improve the process of scanning brownfield substations and generating intelligent models by making the process more efficient and less error-prone.
M. Kokorus, F. Pizarro, W. Eyrich and S. Heuser, "From Optical Symbol Recognition (OSR) of Point Clouds to the Substation Information Model," 2018 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), Denver, CO, USA, pp. 1-4., 16-19 April, 2018
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