Digital Twin in Smart Grids

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September 22, 2022


Renewable Energy


Digital Twin in Smart Grids

Digital Twins (DT) have seen a lot of technical advancements in the recent years. From NASA’s Apollo program, where identical space vehicles were built to mirror the flight conditions, to various fields like production engineering, aerospace engineering and automotive engineering, digital twins are expanding their horizons. And now, the power grid industry has realized the potential of this unique concept in Industry 4.0.

Energy generation and distribution sector is undergoing a tremendous change from traditional systems to support the use of renewables on the grid. To better operate, analyse and optimize the system, smart grids with smart devices are utilized. Now, the next evolutionary step is the use of digital twins in these smart grids for dynamic observability, assessment, and advance decision support. As digital twin is the exact virtual replica of the system, it allows testing and experimentation to predict and better understand the consequences and impacts of adoption of advanced technology. It is also used to evaluate future failures like line faults in electric network, observing the data and pre-plan accordingly, increasing the system efficiency. Other benefits include performance improvements, tracking system, risk management and product management.

Many companies are providing solutions based on digital twin technology in different fields of the energy sector.

Digital twins in renewable energy

The hazardous effects caused by the use of conventional energy sources on the environment are well known. Hence, in the recent years, the use of renewable energy and innovations related to renewable energy sources are on the rise. Companies are taking this opportunity to grow in renewable energy sector by offering solutions based on digital twins.

General Electric is a pioneer in Industrial Internet of Things. Digital Twins at GE Digital focus on Asset, Network and Process. GE Digital has already delivered Process Digital twins in the power generation industry through CSense Operations Performance Management (OPM) solutions. OPM uses AI/Machine Learning algorithms for more accurate predictions regarding the hourly capacity and the heat rate of their plants.

The Corporación Dominicana de Empresas Eléctricas Estatales (CDEEE) is partnering with GE Steam Power and GE Digital to help the country increase its use of renewable energy by 25% until 2025. GE will help the CDEEE team remotely monitor the site’s equipments to help predict operational issues through Predix Asset Performance Management (APM), while OPM will increase the efficiency of the plant.

Another multinational company, Microsoft Corporation, launched Azure Digital Twins in October 2018, in Orlando, Florida. It can be connected to the other Microsoft products to build IoT solutions. Azure Digital Twins provide solutions to customers to help them optimize the operations and costs. In the Energy sector, Azure has partnered with numerous companies including Allego, E. ON, Vattenfall, and Agder Energi.

Increased efficiency

Siemens, headquartered in Munich, Germany, has contributed towards the technology sector since 1847. To enable interoperable data exchange and synchronization, Siemens has developed Electrical Digital Twin. The data is synchronized and then standardized into one multi-user database. The Electrical Digital Twin is provided using one or more of Siemens portfolio elements like MindSphere, MindConnect, PSS®ODMS, PSS®MOD.

Finland’s transmission system operator, Fingrid, had partnered with Siemens in 2016 to introduce ELVIS, the digital grid model that supports their asset management, operation management along with infrastructure investment planning. In the past, 80 percent of the effort was taken on the data collection and verification, while only 20 percent of the effort was taken on actual analysis. Now, the data collection and verification process require less than 20 percent of the time, while 80 percent time is reserved for the crucial analysis task.

IBM has launched IBM Digital Twin Exchange where customers can get the required digital twins in minutes. It supports a wide range of products that customers can browse through, purchase and download. The downloadable materials include bill of materials, building information models, engineering manuals, 3D CAD files and more.


Pratiti Technologies is an Outsourced Product Development(OPD) and Digital Solutions company, that has its own patented Digital Twin IoT enabled Performance Intelligence & Health Analytics solution for the Renewable Energy Sector, known as APOLLO. It is for a system employing electrical digital twin for improving the process and performance of solar photovoltaic power plant. Another solution provided by Pratiti Technologies integrates Supervisory Control and Data Acquisition (SCADA) and delivers features such as benchmarking, root cause analysis for failures, intra-day power prediction, and performance forecasting.

Apart from data analysis, many start-ups like ROAV7,UrsaLeo, Tardid Technologies offer a full 360-degree view of workplace using digital twins. These virtual tours using 3D models increase the operational safety and reduce the operational time on several sites, such as nuclear sites, oil & Gas sites or industrial sites. These solutions also help to carry out maintenance follow-ups, extending the life of installations.

Future of Digital Twins in Smart Grids

In Industry 4.0, Digital Twin concept is bringing in infinite possibilities through technology, artificial intelligence (AI), the Internet of Things (IoT), and data analytics. Digital twins are continuously learning new skills and capabilities to increase productivity of the systems.

Currently, the most frequent applications of digital twins are anomaly detection, analysis and future prediction. In the future, digital twins won’t be limited to data acquisition and analysis. The system can be linked together as a single data-driven process. Every participant in the grid will use their own digital twin to get digitally represented. Even peer behaviour can be anticipated in the system. This will enable them to optimize their operation themselves and increase the overall efficiency of the system.

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