Grid Twin
The Grid Twin improves project delivery, asset management and operational planning through fusion of up-to-date spatial, asset, environmental and operational data.
The Problems
Engineering and Project teams rely on up-to-date asset information to plan new, remedial and upgrade works. Acquisition of this information can be time and cost-prohibitive, and thus, many smaller works are done on generic/as-designed rather than as-is data. At short notice, teams often rely on verbal descriptions or pre-planned schedules and put considerable contingency into budget and schedule, as they know that conditions on the ground will rarely reflect plans.
Maintenance and Reliability teams rely on pre-planned calendars and static status reports to plan shutdowns and interventions. At short notice, teams often rely on verbal descriptions or pre-planned schedules and put considerable contingency into budget and schedule, as they know that conditions on the ground will rarely reflect plans. During shuts, adjacent work that could be completed at low cost is often not attempted or is treated as emergent work.
Training teams rely on prescribed and generic documentation and real-world experience to develop training that prepares workers for high-risk work. This training is based on ideal equipment designs or a single closely located installation and ignores the many spatial/access/adjacency/uniqueness issues that actual work entails.
Operations & Planning teams need to trade off pre-planned works with unplanned changes to networks and markets that impact revenue, cost and service level agreements. The ability to rapidly plan and execute unplanned-but-not-emergency works is constrained by data access, cross-functional collaboration, and governance factors. As a result, some organisations default to emergency works to solve planning changes (firefighters), and some organisations delay decisions to ensure all processes are observed (bureaucrats). In both cases, significant global sub-optimal tradeoffs are made, often by siloedon makers or local decisi operating without the data or governance required to make effective and efficient decisions.
Control room operators often rely on asset/process/network data as their primary means of decision making, with little or no current and contextual work/maintenance/project data, and often with little governance or authority to make non-network decisions, and little ability to collaborate with field workers beyond phone calls. The siloed “asset view” and prevailing control room mindset of process-only or emergency control, leaves all unplanned-but-not-emergency works to be managed in an ad-hoc way or without the assistance and visibility that control rooms have.
A Grid Twin provides power companies with cross-domain data and near real time context to improve Engineering & Project delivery, Maintenance & Training, and Operations & Planning.
The Grid Twin is a flexible tool that can grow with additional data inputs and models, providing different use cases to different users.
A Grid Twin brings together several key data sets:
3D models of assets and installations
Environmental and asset spatial data at and along point and linear assets
Asset and Maintenance master data
Maintenance plans and work orders
Project and shutdown schedules and plans
Network models
Example Grid Twin Use Case - Substation Upgrade & Maintenance Works
Use cases: Asset Upgrade Projects & Major Shutdowns
Primary Users: Engineering, Projects & Maintenance
Potential changes required:
Regular or rapidly deployed scanning of substations and the surrounding environment, potentially to include colour video
Easy / fast Integration of scan data into planning and design tools
Semi-automated/automated spatial change identification and clearance/measurement tools (especially for non-engineering users)
Overlay/comparison of updated spatial data with design changes & construction planning activities (including use of construction equipment models & spaces (e.g. laydown/crane/setup) where possible)
Business process changes require area/environment scanning to be conducted before planning works and risk assessments to be conducted using up-to-date spatial data
The ability to provide “on demand” visualisation for risk assessments and project planning, especially if available across multiple time periods (e.g. previous projects, inclement weather, sunrise/sunset at that time of year, etc.), enables systematic and highly contextual planning by decisions makers
Immersion (e.g. VR/XR) into these “historic” and recent visualisations provides highly enhanced situation awareness for decision-makers before they set foot on the site. In particular, being able to test site lines and introduce supervisors and leading hands to proposed works and conditions enables enhanced design of work, not just the scheduling of activities.
Reduced Design Periods
Engineering teams can design works faster with contextual and accurate spatial data and provision of risk assessments. Opportunities exist for design, constructability and risk assessment activities to occur in the same visualisations and for previous similar activities to be available for review and use.
Reduced Project Cost & Schedule
Engineering & Project teams can reduce contingencies in quantities and time with far less risk when they have designed and virtually constructed with up-to-date data. Of particular importance is the ability to “see” what was done previously, what worked and what didn’t from lessons learned with visual context (the previous scans and plans), and to utilise the historical data in the context of up-to-date visualisation.
Lower Probabilities of Delays
Along with shorter schedules, the risk of delays is decreased, as site conditions are far better known, and risk and constructability activities are based on previous works and recent site conditions.
Lower Risk & Improved Design of Work
The design of work is improved with front line worker and supervisor involvement in planning and risk assessments. Improved work design lowers risk to workers and typically provides a better balance between effectiveness and efficiency. Immersive visualisations enable highly contextual early involvement from the workers who will do the job, and cloud-based tools enable this to be done from anywhere.
Lower Probability of Maintenance Problems
Follow-on maintainability is improved when maintenance workers are involved in visualised planning and approvals and when workers can see the proposed final design in the context of the surrounding equipment/infrastructure/environment/roads, etc. While design for maintainability has been common for many years, it is also often not used well in small/upgrade/shutdown projects where budgets and schedules are very tight, and maintenance workers are often not available in the office to assist.
Other Use Cases
Grid Twins can be extended to other use cases, including:
Emergency response (with Situation twin capabilities)
Work Management (with Real Time Location, ERP, EAM, Work Order Completions, and Safety related inputs such as Planned/Active Permits data)
Network / Repairs response tradeoff (with Network/Controls, Economic models, and Work Management Planning)