is a digital simulation model that behaves in the same way as its real system. To realize a digital twin …

1. We have to prepare the same simulation model as the real system.
2. We need a computing facility which is fast enough for our purpose.

• The development of GriSim and another system for transmission systems has been documented in the article (right).
• The development of GriSim has been carried out from Apr. 2016 to Mar. 2021.
• GriSim is used by seven T&D companies mainly for the assessment of renewable energy integration.
• The system for transmission systems is under development with all T&D co.’s.

• We have thousands of different distribution feeders. For each feeder, the topology changes. No fixed topology can be assumed.
• Rather than a real-time simulator, a “flexible” computing facility such as Amazon’s EC2 (elastic computing cloud) is preferred.
• Do we need hard real time for distribution simulations? We need a “fast” computing facility but not a hard real-time simulator.
• So, what we need is a “flexible” and “fast” computing facility so that any feeder can be simulated with a sufficiently fast speed.
• Now, Amazon’s EC2 can achieve a simulation speed which is faster than real time. It means that we can create a Cloud Digital Twin.

• We would like to propose the following Cloud Digital Twin concept for distribution systems.
• By specifying a feeder, a simulation data case is automatically generated by extracting data from existing DBs. For this, we have developed GriSim with the seven T&D companies.
• The simulation data case generated is reproduced on a cloud computing facility such as Amazon’s EC2 as a digital twin.
• A control system supplied by a distribution facility vendor is tested in the “Cloud Digital Twin,” before deploying in an actual distribution system thus leading to a faster deployment.

■ T. Noda, T. Tadokoro and T. Dozaki, “Automatic Generation of Power System Simulation Data Cases From Utility Databases: Introducing a new technology,” IEEE Electrification Magazine, vol. 11, no. 4, pp. 79-85, Dec. 2023, doi: 10.1109/MELE.2023.332052.
https://doi.org/10.1109/MELE.2023.3320521

■ T. Tadokoro, T. Noda, K. Ishimoto, N. Okada, S. Uemura and Y. Shumuta, “Automatic Generation of Input Data for Distribution System Simulation Programs,” 2018 IEEE Innovative Smart Grid Technologies – Asia (ISGT Asia), Singapore, 2018, pp. 25-29, doi: 10.1109/ISGT-Asia.2018.8467719.
https://doi.org/10.1109/ISGT-Asia.2018.8467719

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