How Energy Companies Are Leveraging AI to Tackle New Challenges
Artificial Intelligence (AI) has demonstrated its transformative potential across various industries, including the energy sector. The sector stands to greatly benefit from AI in addressing significant challenges brought on by changes in consumption patterns and the need for sustainability.
The energy sector encounters numerous operational challenges, from limitations in energy storage to the complexities of grid management, which significantly affect an organization's resilience and journey toward decarbonisation. The demand for advanced technologies in this sector is undeniable, and unsurprisingly, energy companies are among the first to adopt AI innovations, often through strategic partnerships with startups.
According to Allied Market Research, AI in the energy market was valued at $4 billion in 2021 and is projected to reach $19.8 billion by 2031, growing at a CAGR of 17.4% from 2022 to 2031. This growth indicates that large energy companies will continue to hire machine learning and data scientists, while AI-focused startups will keep forming strategic partnerships.
Challenges and Opportunities
AI presents many benefits for the energy sector, enabling it to solve long-standing problems and capitalise on new opportunities. Key areas include:
- Smart Grids
These advanced electrical systems use digital technology to monitor energy consumption and enhance the sustainability of energy distribution. AI analyses energy usage patterns, optimises resources, and improves reliability. It forecasts consumption trends, allocates resources efficiently, and enhances electricity distribution. Additionally, AI detects and rectifies faults, reducing service interruptions and bolstering grid reliability.
- Demand Response Management
This crucial aspect of energy management benefits considerably from AI, which facilitates real-time responses to energy demand fluctuations. By analysing data from various sources and predicting energy demand changes, AI helps adjust the energy supply, enhancing efficiency and reducing costs.
- Energy Storage
AI utilises data analysis to maximise the use of renewable energy sources by optimising their storage and distribution. This approach reduces dependence on unpredictable weather, ensuring consistent power availability even during peak times or when natural resources are scarce. For example, AI can balance solar panel output at night and wind turbine output during calm periods to maintain a steady energy flow.
- Predictive Maintenance
This approach uses machine learning algorithms and predictive analytics to foresee potential equipment issues, allowing for timely maintenance and repairs. AI analyses sensor data, performance metrics, and maintenance records to predict equipment failures, leading to reduced downtime, lower maintenance costs, and enhanced safety.
- Energy Efficiency
AI improves energy efficiency in buildings, vehicles, appliances, and industrial processes by analysing data to provide insights and recommendations on reducing energy consumption and waste. For instance, AI can optimise building energy use by automatically managing cooling and lighting systems.
Collaborations with AI Startups
Startups focused on AI innovation are becoming change catalysts, offering advanced solutions for energy storage and resilient grids. These startups develop innovative solutions that tackle the sector’s challenges, shaping a sustainable energy future.
According to PitchBook, 1,153 deals (financing, M&A, IPO) have been completed globally in the energy tech sector over the last ten years across 676 startups. The total capital invested is $7.0 billion, with a median post-money valuation of $12.5 million. Indicative examples of successful collaboration between corporates and startups in the energy sector include:
SolarCity, now part of Tesla, showcased a successful collaboration to promote residential solar energy use and create a clean energy powerhouse. SolarCity overcame the high upfront costs associated with solar installations and introduced the concept of solar as a service. Tesla found an excellent ally to address its need to help clients overcome rising energy costs.
In Denmark, Salling Group aims to cut energy use across its stores by partnering with AI startup Ento Labs. Similarly, Octopus Energy partnered with Salzgitter Group to provide 126,000MWh of solar energy yearly, aiming to make German steel production more eco-friendly.
Schneider Electric has acquired several innovative solutions startups in the last few years, with EV Connect being one example. EV Connect developed a creative, open charging platform for electric vehicles that matched Schneider Electric's vision for a more sustainable and resilient world.
Energy Innovation unveils
Qualco Group monitors the developments in the energy sector, especially keeping an eye on the innovations that startups are working on that harness the latest AI technologies to enhance energy production, distribution, consumption efficiency, reliability, and sustainability. Through our Innovation Hub, we highlight the importance of embracing new technologies and fostering a culture of innovation and continuous improvement, which are vital for addressing the energy sector’s complex challenges.
AI thrives in data-rich industries, presenting a unique opportunity for the energy sector to utilise its vast data resources to tackle the challenges of volatile demand, operational disruptions, and decarbonisation. Openness to synergies with AI startups allows established energy companies to implement innovative solutions and explore new digital future concepts.