Electricity Network Digital Twins Technology

Goals

To provide insights into the electricity digital twin global market with a focus on asset management and network designs. To also determine the key specifications, the applications and use cases, key market players, sales model and approach, and a rough price to install the digital twin models.

Early Findings

Insights

The Siemens Electrical Digital Twin

  • Siemens applies electric digital twin technology in managing power grids. The vast availability of digital data in digital twin technology enables utilities to plan, maintain, and operate the electric grid with a digitalized model of the physical world.
  • Trends like renewable and the decentralization of electric power make data complex to exchange and manage, and any small mistakes lead to serious grid consequences.
  • The Siemens electrical digital twin aligns the real and virtual scenarios by providing utilities with model data across the entire IT landscape. The electric network model facilitates grid simulation across all domains for efficient, reliable, and secure electrical system planning, maintenance, and operation. The electrical digital twin allows the simplification of the data exchange process and data maintenance. Data is synchronized and standardized into multi-user databases.

Key features

  • Electrical digital twins provide "an accurate single source of truth for data", spans distribution and transmission for integrated analysis, automates data and model synchronization in multiple domains. Electrical digital twins are standards-based and vendor-neutral. The diagrams that show Siemen's electrical digital twin simulation model can be found here.

Digital twin applications

Design

  • Electricity digital twin is used in the simulation and visualization during the design phase and can be used to verify and inspect the general 3-D design. The simulation comprises mechanical, electrical, and thermal aspects of the design.

System integration:

  • The 3-D visualization helps to verify the constraints in physical connections and spatial footprint. Connecting the digital twin of other components enables interactions to be simulated, including data transfer and control functions.

Diagnostics

  • VR glasses can enable field technicians with the overlay over the actual equipment to visualize parameters. The simulations of the digital twin can add non-observable data like temperature.

Prediction

  • Electricity digital twins help engineers predict the past and present sensor data and operational factors in combination with predictive algorithms, to provide insights into the conditions of equipment in the real world scenario. Shows the likelihood of failure, plan rational maintenance, and reduce unplanned downtime.

Key Players

  • Key Players in the global digital twin market include IBM, General Electric, and Microsoft, Oracle Corporation, Siemens AG, Amazon Web Services, and Dassault Systems.

Estimate Cost

  • The estimated cost of setting up a digital twin is around €50,000. According to a study, companies that use digital twin technology saves between 20% to 30% in development cost. It is economical for the creation of high tech systems that would normally cost over €150,000.

Proposed next steps:

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