Introduction

The global energy sector is rapidly evolving through digitalisation, supported by significant technological advancements and robust investment. Global investment in the energy transition reached an all-time high of $2.3 trillion in 2023, representing an 8% increase from the previous year. This surge underscores a shift towards smarter, more connected systems, particularly in renewable energy, energy storage, and smart grids. Energy system digitalisation refers to the integration of technologies such as Internet of Things (IoT) devices, advanced analytics, artificial intelligence (AI), and blockchain. These tools facilitate essential processes including real-time monitoring, predictive maintenance, and decentralised energy production.

Digitalisation – a global picture

Different regions are embracing digitalisation at varying speeds. North America and Europe are at the forefront of smart grid investments, while emerging markets in Asia and Africa are progressively implementing digital solutions to facilitate renewable integration. North America leads in market maturity for smart electricity meters with a 77% penetration rate, followed by APAC at 49% and Europe at 47%. In the UK, smart meter installations have reached over 41 million units, representing more than 71% of households. Globally, over 1.06 billion smart meters were installed by 2024, with penetration expected to rise from 43% to 54% by 2030. In 2022, 11 billion devices were connected to automated controls, a figure projected to exceed 25 billion by 2030.

The driving forces behind digitalisation

Several factors underpin the surge in digitalisation. Stringent global commitments to mitigate climate change have pushed for a transition to renewable energy, which digital tools support by ensuring grid stability. Economic efficiency is another key driver; digitalisation can lower operational costs through predictive maintenance and reduce electricity consumption by up to 30%. Standards such as BS ISO EN 50001 (Energy management systems) help organisations translate digital insights into carbon reductions. Technological advancements in AI and IoT, coupled with decreasing costs, accelerate adoption. Furthermore, modern consumers demand greater control and transparency, while the integration of Distributed Energy Resources (DERs) like solar PV and electric vehicles (EVs) in homes creates complex datasets requiring sophisticated management.

Digital energy system components

Smart grids are foundational to digitalising energy systems, incorporating sensors and automation to control electricity flows in real-time. IoT and big data provide granular insights into consumption patterns, while AI and machine learning algorithms enhance predictive maintenance and detect anomalies. In the UK, one nuclear facility operator used AI to reduce 90% of its administrative burden, while another utilised a combination of digital twins and machine learning to extract up to a 30% reduction in maintenance costs. Blockchain technology provides secure, decentralised solutions for peer-to-peer energy trading between prosumers.

Role of digital twins and the Common Information Model (CIM)

A digital twin is a virtual replica of a real asset created using IoT sensors and AI, allowing for risk-free testing and performance optimisation. The CIM acts as a universal language for the energy sector, ensuring that participating systems speak the same data language. National Grid ESO’s Virtual Energy System in the UK uses the CIM to create digital copies of the grid. A trial run between 2022 and 2023 achieved approximately 3.3 GW hours of peak energy reduction. The UK government estimates that demand-side response (DSR) could reduce electricity system operating costs by £10 billion annually by 2050, with cumulative savings projected to range from £30 billion to £70 billion.

Benefits of digital twins and the CIM

The integration of the CIM enables digitalisation at scale across the energy system. Key benefits include real-time monitoring and predictive maintenance, which simulate the behaviour of physical assets to identify issues before they occur. It also assists in asset design and optimisation through scenario analysis and enhances cybersecurity by aiding early threat detection. Furthermore, digital twins simulate distribution for optimal renewable energy management and contribute to significant cost reductions by minimising downtime.

Case studies

In Australia, the Australian Energy Market Operator (AEMO) developed a digital platform to streamline DER registration. This contributed to an 18% increase in renewable energy generation in 2020-21, and DERs are expected to deliver a $19 billion boost to the Australian economy by 2040. In the UK, Ofgem mandated the CIM as a licence requirement for network data in 2023. BSI was appointed as the GB CIM Governance Body to maintain and evolve these standards, with over 100 organisations now contributing to the initiative to improve data quality and innovation.

Challenges of digital twins and the CIM

Despite the benefits, several implementation challenges exist. Data accuracy and reliability remain significant hurdles, as integrating data from various sources is difficult. High upfront investment and the complexity of integrating with legacy systems can be a barrier. Furthermore, the adoption of these technologies requires a cultural shift and specialized skills, addressing a notable skill gap in data science. Heightened cybersecurity and data privacy concerns also require robust security measures.

The role of standards in energy digitalisation

Standards provide a foundation for interoperability, reliability, and security. Standardised digital twin technology can enhance operational efficiency and reduce maintenance costs by up to 18%. Key standards include the BS ISO 23247 series for manufacturing and BS EN IEC 61850 for substation automation. Automation standards like the BS EN 61508 series ensure infrastructure safety, while IT and cybersecurity standards like the BS ISO/IEC 27000 series provide frameworks for managing information security. Automation in the energy sector has the potential to boost efficiency by 22-30%.

Conclusion

The global energy sector is undergoing a transformation fuelled by digitalisation, contributing to sustainability and energy security. Standards available in BSI Knowledge offer frameworks to ensure technologies are implemented effectively. Organizations are encouraged to benchmark against international best practices, such as BS EN 61850 and BS ISO/IEC 30173, and adopt a standards-led approach to ensure interoperability and the safe integration of emerging technologies.