Building a more intelligent grid for a more complex energy future

The future of grid reliability will depend on how utilities harness data, intelligence, and engineering expertise to anticipate and manage grid complexity.

Artificial intelligence (AI) is reshaping the energy sector in more ways than one. Demand for reliable power is rising rapidly as AI, data centres, advanced manufacturing and the wider electrification of the economy continue to grow, compounded by the need to advance the energy transition. At the same time, AI is providing utilities with sophisticated tools to manage a more dynamic and decentralised energy system.

For utilities, the challenge is not simply keeping pace with demand growth. It is maintaining reliability, supporting economic development whilst ensuring critical infrastructure remains secure and resilient.

At SP Group, this is driving a broader transformation in how the grid is planned, operated and maintained.

“AI is changing both sides of the equation. It is adding new demand on the grid and is also the enabler to manage the increased complexity. The opportunity lies in using AI to maintain reliability, improve resilience and advance the energy transition, all at the same time,” said Stanley Huang, Group CEO of SP Group, in an interview with Asian Power. 

SP Group is taking a long-term approach to this shift. This means working with government agencies and industry partners to plan grid investments around Singapore’s current and future needs. Beyond investing in physical infrastructure, it is building the digital capabilities needed to manage a grid that is more interconnected, data-driven and responsive.

This includes technologies such as Digital Twins, Distributed Energy Resource Management Systems (DERMS), Virtual Power Plants, and AI-enabled analytics, which allow operators to better anticipate demand, manage distributed energy resources and maintain system stability as renewable energy integration increases.

As the grid evolves beyond a physical network into a more intelligent and adaptive system, SP Group's focus is on turning operational data into actionable insights. This includes strengthening how it anticipates risks, prioritises investments, allocates resources, and improves decisions across planning, operations, and maintenance.

For Huang, however, technology adoption is a means to an end. The priority is ensuring AI delivers meaningful operational value whilst maintaining the standards of reliability, safety, and accountability expected of critical infrastructure operators.

From reactive maintenance to anticipatory operations

Traditionally, utilities have relied on periodic inspections, scheduled maintenance, and engineering judgement to manage assets and network performance. Increasingly, AI and advanced analytics are allowing utilities to augment these approaches with real-time insights, predictive capabilities and risk-based decision-making.

For instance, the company has an AI-enabled power quality fault diagnosis capability that can automatically identify the likely cause and type of unusual voltage or power-quality disturbances. What once required engineers to manually review complex waveform data for several hours can now be completed within minutes.

More importantly, faster fault categorisation enables earlier interventions and more targeted operational responses, to help identify emerging issues before they escalate into wider reliability concerns.

SP Group is also applying similar predictive capabilities across its gas network through its Gas Anomaly Detection System. By analysing pressure-sensor data to identify subtle deviations from normal operating conditions, anomalies can be detected earlier, enabling more proactive network management. The goal is to anticipate faults rather than react to them.

Beyond day-to-day operations, SP Group is using digital twin technology to support more informed infrastructure investment decisions. Together with AI and predictive analytics, Digital Twin technology is helping the company move from reactive asset management to anticipatory operations, allowing timely interventions before issues impact customers. This enables a shift from age-based replacement cycles towards a more condition- and risk-based approach. This helps prioritise maintenance resources, optimise asset lifecycles and plan future grid investments with greater confidence.

“The primary outcome is optimisation. Our priority is to maximise the useful life of equipment and cables to maintain reliability by understanding their actual condition, performance, and criticality,” Huang said.

Equipping people for an AI-enabled energy system

SP Group sees workforce readiness as equally critical to the future of grid operations. As utilities transform through digitalisation, the workforce must evolve alongside it. Future grid operations will require a combination of deep power system expertise with capabilities in AI, data analytics, cybersecurity, and digital technologies. Building this engineering bench strength is just as important as investing in infrastructure.

Through FUSION.AI – the next phase of its workforce transformation journey – SP Group is equipping employees with the capabilities, confidence and tools to apply AI responsibly and streamlining operational workflows to deliver meaningful value.

In field operations, AI-assisted scheduling has improved job allocation efficiency and reduced task execution time. SP Group is also in the process of developing an AI-powered assistant that allows field workers to retrieve operational procedures, safety information, asset data, and work records using natural-language queries. 

SP Group is also applying AI to strengthen workplace safety. With more than 200 worksites monitored by multiple CCTV cameras, safety officers traditionally review video footage to identify unsafe practices and behaviours. Given the large volume of footage gathered daily, not all the footage can be reviewed in time. To improve coverage and effectiveness, a Safety Specialist Agent was developed that combines computer vision and vision-language models to take on this manual role. The pilot successfully detected safety non-conformances including those specific to SP Group’s safety practices and policies. For Huang, this is about enhancing human expertise and not replacing it.

As a critical infrastructure operator, SP Group's approach to AI is deliberate and disciplined. It has established an AI Governance Framework and a risk assessment process to evaluate applications before deployment. Cybersecurity is also being strengthened as AI becomes more integrated into grid operations. These measures help ensure that AI is deployed safely, responsibly and in ways that complement human judgement.

Huang chairs the company’s AI Taskforce, which brings together expertise from technology, cybersecurity, operations, human resources, and business leadership.

“Human oversight remains at the core. AI can provide recommendations and insights, but accountability for critical operational decisions continues to rest with our power grid teams,” Huang said. Having this balance is important as AI capabilities advance.

Looking ahead, SP Group's focus is on bringing together its growing suite of AI and analytics capabilities into a more integrated operating environment. The objective is to provide grid teams with a more comprehensive and real-time view of network conditions, asset health and operational risks. 

“The future grid will need to be smarter, and able to anticipate, adapt, and respond to an increasingly fluid operating environment,” Huang added.

As Singapore advances towards a more digital and low-carbon economy, AI will be a key enabler. Its success will depend on strong governance, a skilled workforce, and sound engineering fundamentals. By reinventing utilities through digitalisation, SP Group is strengthening reliability and resilience whilst preparing the grid to support Singapore’s future growth and energy transition.

To know more about SP Group, visit https://www.spgroup.com.sg/.