subscribe Support our award-winning journalism. The Premium package (digital only) is R30 for the first month and thereafter you pay R129 p/m now ad-free for all subscribers.
Subscribe now
Effectively harnessing AI can be a game-changer for SA’s energy ecosystem and green transition. Picture: 123RF
Effectively harnessing AI can be a game-changer for SA’s energy ecosystem and green transition. Picture: 123RF

Solving power outages requires creativity, innovation and a long-term approach. This is where the potential of artificial intelligence (AI) could shine through.

AI replicates human intelligence in machines, enabling them to handle tasks that typically rely on human cognitive abilities, such as learning, reasoning, problem-solving and decision-making — but at lightning speed.

Effectively harnessing AI can be a game-changer for SA’s energy ecosystem and green transition.

By tapping into the potential of AI, SA can better manage and source its energy supply, paving the way for a brighter, greener and more prosperous country. To make this a reality, clear and forward-looking AI adoption policies should be prioritised, with strategic investments in AI education and training programmes.

At the Wesgro inaugural Business Outlook conference the urgency of finding solutions to the pressing energy challenges took centre stage, with a clear focus on harnessing green alternatives and using new technologies. 

Martin Svensson, CEO of AI Sweden, emphasised the immense potential of AI to transform and stabilise a country’s energy ecosystem. With a vision that could reshape demand optimisation and energy trading, he presented a unique opportunity to confront energy deficits head-on, while propelling sustainability efforts forward. By seizing this opportunity, SA can pave the way for a greener, more resilient future, ultimately ensuring its prosperity.

Sweden stands on the precipice of transforming its energy planning through the implementation of an AI-driven national platform, said Svensson. This initiative strives to predict future energy demand with unmatched accuracy, granting authorities the power to shape the nation’s energy landscape with strategic precision.

Demand management

Australia and China are leveraging AI and advanced technologies to expand their energy grids and enhance efficiency.

SA can draw valuable lessons from these nations and leverage AI to ensure that no community is left in the dark. Our energy challenge mostly centres on demand management. As the population grows, electricity demand is poised to surge further. 

Conventional demand forecasting methods fall short in a fast-changing world. By analysing extensive historical data, AI algorithms can predict consumption patterns with unmatched precision. Its predictive prowess empowers utilities to anticipate peak demand and optimise energy distribution, curbing load-shedding.

Various commentators and experts have studied how AI can aid the green transition particularly. However, AI alone is not the answer. Aggressive political and corporate commitments to emission reduction and sustainable energy supply are indispensable. Yet, amid the urgent, vast, and intricate energy crisis SA faces, every available tool must be used. If wielded effectively, AI will foster innovation and play a key role in the drive to establish a secure, resilient, and affordable clean energy system.

A resilient energy infrastructure relies on a robust and adaptable grid. AI can optimise grid operations and maintenance, detecting faults, and scheduling pre-emptive maintenance to enhance reliability. AI also enables real-time grid balancing, integrating renewable sources for uninterrupted electricity supply.

AI can potentially address energy challenges in SA by improving grid access and capacity. AI-driven planning tools could identify areas with limited energy access, enabling efficient deployment of power generation and transmission infrastructure. This targeted approach connects remote communities, fostering socioeconomic growth through smart investments.

Adjusts automatically

Imagine a future in which every home and business forms a connected grid, sharing data and insights. AI algorithms can efficiently process this information, optimising energy supply to avoid peak-time overloads. This could cut load-shedding and reduce overall energy consumption, paving the way for a greener, sustainable future.

Picture an intelligent energy management system that automatically adjusts electricity usage in industries and households during peak hours. AI-powered demand response mechanisms incentivise users to cut back during critical periods, easing the strain on the grid and minimising load-shedding. By encouraging energy conservation through smart metering and AI-driven insights, citizens can actively participate in stabilising SA’s energy ecosystem. 

During the Wesgro Business Outlook conference, Kadri Nassiep, City of Cape Town executive director for energy, emphasised their pursuit of solutions to maintain essential services for commercial customers during the day while ensuring residential customers’ basic needs are protected.

The city has been invited to join a national pilot programme, which involves sequentially switching off nonessential loads such as swimming pool pumps and air conditioning, and gradually reducing energy usage in households to preserve key essentials such as lighting, plugs, and basic security and food requirements. AI can significantly contribute to this endeavour.

To effectively address the energy crunch and embrace cutting-edge technologies, substantial capital and a skilled workforce are required, making partnerships essential.

• Stander is CEO of Wesgro, the official tourism, trade and investment promotion agency for Cape Town and the Western Cape.

subscribe Support our award-winning journalism. The Premium package (digital only) is R30 for the first month and thereafter you pay R129 p/m now ad-free for all subscribers.
Subscribe now

Would you like to comment on this article?
Sign up (it's quick and free) or sign in now.

Speech Bubbles

Please read our Comment Policy before commenting.