“Digitalisation of HVDC Interconnector Systems”

The IFA (Intertie France-Angleterre) interconnector system is a high-voltage direct current (HVDC) link that connects the electricity grids of France and England. The interconnector was first commissioned in 1986 and has a capacity of 2,000 MW, making it one of the largest HVDC interconnectors in Europe. The IFA interconnector system plays a critical role in ensuring the security of electricity supply in both France and England. With the increasing integration of renewable energy sources and the growing need for cross-border electricity trading, the IFA interconnector system is expected to play an even more important role in the future of European energy infrastructure.

The IFA interconnector system comprises two HVDC submarine cables that run across the English Channel between France and England. The cables are 73 kilometres in length and have a transmission capacity of 1,000 MW each. The cables terminate at converter stations in the coastal towns of Folkestone in England and near Dunkirk in France. The converter stations are responsible for converting the AC power from the local grid into DC power for transmission over the interconnector.

We explore how digitalisation can maximise IFA availability (say from 92/93% to 98%) and Reduce the amount of time taken for planned outages, reduce maintenance costs and finally created a roadmap / digital strategy which include the use of AI and machine learning for enhanced asset management.  We investigated various IoT Use Cases the Focus areas:

Digitalization of HVDC Interconnector Systems

High-voltage direct current (HVDC) interconnector systems are critical components of modern power grids, enabling efficient transmission of electricity over long distances and between different regions. The digitalization of HVDC interconnector systems is an emerging trend that involves the integration of advanced digital technologies, such as sensors, data analytics, and artificial intelligence, into the design and operation of these systems.

The digitalization of HVDC interconnector systems offers several benefits, including improved reliability, increased efficiency, and enhanced control and monitoring capabilities. For example, by integrating sensors and data analytics into the system, operators can gain real-time insights into the performance of the system, allowing them to identify and address issues before they lead to downtime or other disruptions.

Additionally, the digitalization of HVDC interconnector systems can enable more efficient and optimized power transmission, reducing energy losses and improving overall system performance. By leveraging advanced control and monitoring capabilities, operators can adjust the flow of electricity in real-time, ensuring that the system operates at maximum efficiency and avoiding unnecessary energy losses.

Another key advantage of digitalization in HVDC interconnector systems is the ability to enable remote monitoring and control, reducing the need for on-site personnel and improving safety. By leveraging advanced communication and networking technologies, operators can monitor and control the system from remote locations, reducing the need for personnel to be physically present at the site.

However, there are also challenges associated with the digitalization of HVDC interconnector systems, including the need for robust cybersecurity measures and the potential for data overload. As these systems become increasingly connected and reliant on digital technologies, the risk of cyber attacks and data breaches increases, making robust cybersecurity measures essential.

Overall, the digitalization of HVDC interconnector systems holds great promise for improving the performance and efficiency of these critical components of modern power grids. As the technology continues to evolve, we can expect to see more innovative applications in areas such as predictive maintenance, autonomous operation, and advanced energy management.

Transformer Asset Management Analytics

Transformer Asset Management Analytics is a data-driven approach to managing assets that leverages machine learning, artificial intelligence, and data analytics to improve asset performance, reduce costs, and increase profitability. The technology is based on the Transformer model, a deep learning architecture that has been widely used in natural language processing tasks and has since been adapted to other areas, including finance and asset management.

In asset management, the Transformer model can be used to analyze large amounts of data, including historical asset performance data, market data, and other relevant information, to identify patterns and insights that can inform investment decisions and optimize asset performance. For example, the technology can be used to identify assets that are likely to outperform or underperform in a particular market condition and adjust investment strategies accordingly.

One of the main advantages of Transformer Asset Management Analytics is its ability to process and analyze unstructured data, such as news articles and social media posts, which can provide valuable insights into market sentiment and help inform investment decisions. Additionally, the technology can be used to monitor asset performance in real-time and provide alerts when certain conditions are met, allowing asset managers to take proactive measures to mitigate risks and optimize performance.

However, there are also challenges associated with implementing Transformer Asset Management Analytics in finance and asset management. One of the main challenges is data quality and availability, as the technology relies on accurate and up-to-date data to provide meaningful insights. Additionally, there is a need for careful validation and testing of the technology to ensure that it is accurate and reliable.

Despite these challenges, Transformer Asset Management Analytics holds great promise for improving asset performance and transforming the way we manage investments. As the technology continues to evolve, we can expect to see more innovative applications in areas such as portfolio optimization, risk management, and asset allocation.

Tapchanger Usage Analytic

IoT and AI can play a significant role in the maintenance of converter transformer tap changers by providing real-time monitoring and analysis of the tap changer’s performance. This can help identify potential issues before they escalate into more significant problems, allowing for proactive maintenance and avoiding unplanned downtime.

One way IoT can help with tap changer maintenance is by installing sensors on the transformer to monitor various parameters such as oil level, temperature, and vibration. This data can be transmitted in real-time to a central control system, allowing operators to monitor the transformer’s performance and detect any abnormalities or trends that could indicate a potential problem.

AI algorithms can be applied to this data to analyse patterns and predict future issues before they occur. This can include using predictive maintenance algorithms to identify when maintenance is required or to predict when a component may fail. These algorithms can also be used to optimize the tap changer’s performance by adjusting the voltage levels and switching patterns to minimize wear and tear on the components.

In addition to predictive maintenance, AI can also be used for fault diagnosis and troubleshooting. By analysing sensor data and other relevant information, AI algorithms can quickly identify the root cause of a problem and provide recommendations for remediation.

Overall, IoT and AI can help to reduce the cost and time required for maintenance of converter transformer tap changers, while also improving the reliability and safety of the system. By providing real-time monitoring, predictive maintenance, and advanced analytics, these technologies can help operators identify issues before they become significant problems and ensure that the system operates at maximum efficiency.

Asset Management Index for Sellindge Assets

The IFA interconnector system plays a critical role in ensuring the security of electricity supply in both France and England. The IFA interconnector system is owned and operated by RTE (Réseau de Transport d’Electricité), the French electricity transmission system operator, and National Grid, the UK electricity transmission system operator. Both operators work closely together to ensure the safe and reliable operation of the interconnector. By enabling the exchange of electricity between the two countries, the interconnector helps balance electricity supply and demand and can help prevent blackouts and power outages. The interconnector also allows for the exchange of renewable energy between France and England, helping both countries to achieve their renewable energy targets.

In order to improve the availability of the IFA interconnector system, there has been renewals and enhancement of equipment, such as new transformers, thyristor valve with water cooling, filters and high-voltage switchgear. To ensure we optimise the systems availability, we investigated the digitisation of the interconnector systems which may include upgraded with advanced digital technologies, such as IoT sensors and AI algorithms, to improve monitoring and maintenance and ensure maximum reliability.