Ben Croxford, managing director of Eclipse Power Networks, explains how technology can be used to address the power challenges he accuses of causing them in the face of growing concern surrounding the energy demand (AI) of AI.
Artificial intelligence (AI) is a central part of the UK government’s plan to promote growth across the UK. Through the AI Opportunity Action Plan, the government intends to use AI to provide a broad plan of change, including its commitment to making the UK a clean energy superpower by 2030. Not my mind, AI can add the most profit.
In contrast to regular facilities that focus more on data storage, much has been possible about the increased energy demand for data centers that handle AI workloads. In April, the International Energy Agency issued a new report, predicting that data centre consumption would more than double by 2030. However, within the energy sector, AI can be used to fix problems accused of causing them from the perspective of electricity demand.
The challenge of power: the incredible demand for energy
ai stays here. Not only does the government think it can fix many of the UK’s problems, but it also sees AI as the next frontier. Data centers have been promoted to critical national infrastructure status, and local government decisions to prevent data centers from being built were rejected, creating a dedicated AI growth zone.
However, AI’s energy demand is notoriously high, and we expect the rate of growth to be steep, given the possibility of revolutionizing parts of our lives in ways we don’t know yet. According to the International Energy Agency (IEA), a single AI-focused data center may require as much power as 100,000 households. Globally, within the next two years, the AI industry will be able to use as much energy as a country of Japan’s size.
Solution: Use AI to cure yourself
Ironically, because of its capabilities, AI can be used to provide solutions to unique increased energy demand. Throughout the energy sector, AI is used to optimize generation, transmission, distribution and consumption. It is also a major way to decarbonize the sector and make net zero a reality.
AI thrives with data. The energy sector generates and consumes enormous amounts. Information generated by smart meters, remote monitoring sensors, electric vehicle charging and other digital assets supplies AI algorithms to enhance a proactively managed network that benefits the power industry at multiple levels.
Energy companies use AI to connect, optimize and control energy assets such as electric vehicles (EVs), heat pumps, and HVAC (heating, ventilation, air conditioning) systems. This allows suppliers to balance their load and shift in real time by encouraging changes in consumer behavior.
These demand-side response (DSR) programs reward people for adjusting when using power to balance grid loads. Platforms that allow this, such as Octopus Energy’s KrakenFlex, use AI to determine the amount of space required from a DSR program, when to invoke DSR events, and what incentives they provide. By allowing loads to be shifted and reshaped, AI allows power providers to create new energy products and tariffs, generating revenue for future investments in the network.
AI is used to manage both the generation and demand of commercial and industrial development. AI helps to optimize the use of distributed energy resources (DERs) such as batteries, solar and wind to meet peaks and troughs of grid demand. The vast amount of data from these assets, combined with weather forecasts and other key variables, is processed to predict and respond to fluctuations in energy supply and demand. In short, AI allows these resources to be managed more effectively, improving performance and ejecting or reducing them at the right time.
AI power optimization allows asset owners to increase value from their assets when the market situation is correct or when they may maximize financial gains. Second, this could encourage investment in new renewable assets.
Independence innovation
An important additional benefit for optimizing networks and assets using AI is that it helps to ensure that the new generation comes from renewable sources. Variable renewable energy (VRE) sources are inherently intermittent because weather conditions change production. By proactively managing these assets and networks, they can compensate for their intermittent by using a variety of assets with a variety of output profiles that can rise and fall depending on changing conditions. AI algorithms that can respond to voltage fluctuations in milliseconds help grid stability, allowing real-time load balancing and power flow optimization, reducing transmission losses.
AI offers even more exciting possibilities to expand and improve renewable energy. For example, as a tool for scientific discovery, AI appears likely to accelerate the pace of innovation in key technologies such as solar powered (PV) solar modules and battery storage. Improvements here could improve efficiency and performance, reduce the cost of technology, or provide other tangible benefits. So essentially, AI allows cleaner energy to drive its own consumption.
Why Idnos is a good place to lead
AI is not just about domestic infrastructure. It also increases efficiency at the distribution level. Independent distribution network operators (IDNOS) like Eclipse Power Networks are ideal for fast and focused adoption of AI tools. IDNOS can try and deploy targeted AI solutions across design, planning, operations and asset maintenance using more agile structures than traditional distribution network operators (DNOS).
AI supports faster connectivity, smarter adoption of existing networks, and predictive maintenance that minimizes disruptions and costs. During the planning stage, AI enables better demand forecasting and scenario modeling. Additionally, through data-driven asset management, AI will help you move from reactive to preventive maintenance strategies.
However, while the power industry may already be referring to success, it is not just about facing a significant shortage of AI skills across the UK. These add to the challenge of adapting to changes in energy use and growth, driven in part by increased demand for AI. But there is an increasing number of help, including free tools, fundraising opportunities, and knowledge mobility partnerships supported by Innovate UK. By investing in skills and reshaping AI as a strategic enabler across business functions, the power industry can continue to innovate in this area.
From condition to treatment
Despite some alarms regarding AI’s energy consumption, it has more potential than making up for its own energy needs. As a recent IEA report found, it could help reduce costs, increase competitiveness and reduce emissions across the sector.
By optimizing demand and generation using AI, there is no need to take a simple “add more to add more” approach. The intelligent AI-powered optimization of smart grids and proactively managed networks allows for many of the heavy lifting new hyperscale data centers to power clean energy infrastructure that benefits everyone.
Source link
