The rapid escalation of electricity demand driven by artificial intelligence (AI) technologies poses significant implications for commercial energy bills and the broader energy market. The International Energy Agency (IEA) forecasts a potential doubling of power consumption related to AI, cryptocurrency, and the associated data centres by the year 2026. This surge, which aligns with the increasing integration of automation in various sectors, is resulting in heightened pressure on global power supplies.
Tom Roberts, Director of Commercial Energy Services Engineering at IGS Energy, highlights that rising electricity consumption is not solely attributable to AI advances. Factors such as power plant retirements and changes in market infrastructure are also critical drivers of increasing energy prices. He emphasises the need for facility managers to devise strategies that can mitigate the financial burden arising from these trends.
The complexity of the energy market reveals several key elements impacting energy pricing. First, as demand increases, a tighter balance between supply and consumption can lead to market volatility and heightened prices due to scarcity. Additionally, the costs associated with the fuels used to generate electricity, which are also rising due to increased demand, further influence pricing. To adapt to these changes, utilities should invest in new generation capacity, enhance transmission lines, and advance distribution infrastructure, all while integrating renewable energy sources that necessitate further infrastructure development.
In light of these challenges, facility managers are urged to consider actionable steps to manage energy expenditure effectively. Establishing a relationship with an experienced energy supplier is crucial. An adept supplier can guide businesses through market fluctuations, minimising risks while leveraging opportunities tailored to specific organisational needs.
Moreover, facility managers are encouraged to explore operational efficiency measures that can significantly reduce electricity demand. These measures include setting energy benchmarking targets, which can help organisations collect and analyse usage data effectively. Invoking programmes that incentivise shifts in electricity consumption away from peak hours, known as demand response, presents another viable strategy for reducing energy costs while lessening grid strain.
Roberts suggests that understanding an organisation’s energy footprint is essential for identifying when and how energy is consumed, alongside evaluating the financial implications of such usage. By employing a rigorous data-driven approach, businesses can pinpoint trends, assess the operational influences on energy consumption, and implement strategic changes to enhance efficiency.
Overall, as the energy landscape continues to evolve under the influence of AI and other technologies, commercial entities must adapt proactively to maintain manageable energy expenses and secure their operational viability in an increasingly automated future.
Source: Noah Wire Services