Amna Mujahid is a senior analyst in GlobalData’s Thematic Intelligence team. She contributes to the analysis of technologies across various sectors, notably mining, power, agriculture, packaging, and tourism sectors. She takes a keen interest in themes such as cybersecurity, geopolitics, Gen Z, robotics, social media, and supply chains.
Lara Virrey: What are the most exciting developments in robotics for the power industry today?
Amna Mujahid: Robotics has many exciting developments and uses emerging across the power sector from industrial co-bots to inspection and maintenance robots. And developments of AI technologies, most notably machine learning, is integral to further innovations in intelligent industrial robots. These devices can, for example, anticipate and adapt to situations based on the interpretation of data derived from an array of sensors (e.g., 3D cameras, ultrasound transmitters, force sensors, and obstacle detectors).
Further advances are still needed in certain AI technologies, including computer vision, conversational platforms, and context-aware computing, to take industrial automation and robotics to the next level. This will then enable new robotics use cases in the power sector, such as inspection robots that can go from just spotting faults to fixing them and even predicting them (the shift from reactive maintenance to predictive and prescriptive maintenance).
Lara Virrey: What are the key challenges in the power sector that robotics can help with?
Amna Mujahid: Robotics is of growing importance across multiple industries, including the power sector. It is a crucial tool for keeping the operations of power companies functional and optimised in the face of industry challenges. For example, robots enabled the remote monitoring of power infrastructures at the height of the Covid-19 pandemic.
Moreover, robots address the growing hurdles presented by an aging workforce in the power sector and are increasingly undertaking disruptive applications, such as speeding up the installation of renewable energy infrastructures and carrying out maintenance in hazardous spaces.
Regarding the aging workforce, a retirement crunch will happen in the power sector over the coming decade as baby boomers begin to retire. A 2020 study by the UK National Grid found that one-fifth of the UK’s energy sector workforce will retire by 2030. There is a gap between the employees exiting the power sector and those entering.
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By GlobalDataThe geographically dispersed nature of power assets such as wind turbines, solar panels, and nuclear power stations creates an additional hurdle for aging or retired workers to travel to them for work or training purposes. The aging workforce impacts both the quality of hands-on training available to new hires and the overall access to productive workers. Robotics can address this decline in human capital by automating many processes in the power value chain, especially at the equipment manufacture and engineering, procurement, and construction stages.
The success of the energy transition is another vital challenge that robotics can assist with. The energy transition refers to a major structural shift in the global energy industry towards a cleaner energy mix as the world looks to combat climate change.
This transition has implications for all aspects of the industry. It involves reductions in fossil fuel use in favour of cleaner energy sources, improvements in energy efficiency, and many other aspects. Both government policy and technological development drive the transition, and companies within the power sector are increasingly looking to align their investment strategies with this market shift. Robotics plays a crucial role in the energy transition as robots can speed up the build-out and maintenance of renewable energy infrastructures.
For example, drones are already used to inspect offshore wind farms, spotting faults early and bypassing dangerous inspections by workers. Perhaps more impactful, industrial co-bots are used to install modules in solar farms. Power companies must increase their use of robots to prevent a slowdown of the energy transition due to tight labour markets and slow manual processes.
Lara Virrey: Which barriers to implementation of robotic technologies remain in the power industry, and how could they be overcome?
Amna Mujahid: There are always barriers to emerging technologies and increased digitalisation and robotics is no different. For example, robotics integration will make power companies more vulnerable to cyberattacks. Cyberattacks are frequent and increasingly complex. And while digitalisation in the power sector is fuelling productivity but comes at the cost of increased cyberattacks.
In the UK, IBM found that the energy sector was the top target for all cybersecurity incidents, amounting to 24% of all attacks in 2021. Robotics both addresses and adds to the challenge of cybersecurity. Robots form part of the interconnected system that may make power companies more vulnerable to cyberattacks. On the other hand, robots are protected from cyberattacks arising from social engineering, for example.
Beyond this specific challenge, power companies may experience slowdowns in digitalisation, including robotics, due to talent shortages or tightening of company budgets in the current economic climate. However, it is important to note that increased digitalisation in the power sector, for example via the use of robots, increases productivity even as companies deal with an aging workforce, economic downturns, and volatile geopolitical events.
Lara Virrey: Which companies are the leading adopters of robotic technologies in the power sector?
Amna Mujahid: Major companies are adopting robotics at differing rates, below is a sample of the leading adopters of robotics adopters in the power sector:
AES, CenterPoint Energy, China Yangtze Power, CK Infrastructure, CLP Holdings, Dominion Energy, Consolidated Edison, Duke Energy, Electricite de France, Endesa, Enel Americas, Engie, Korea Electric Power, National Grid, Naturgy Energy, SSE, Hydro-Quebec, Rosatom, Vattenfall, and Veolia Environment.
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