AI and IoT: Helping or hindering the climate change journey?

Addressing climate change has become a top priority. Is emerging tech helping or hindering our progress?

With Extinction Rebellion making their presence felt in major cities around the globe recently, the conversation around climate change is heating up and every industry is expected to have an answer. The technology industry is no different, and in many ways technology has seen itself placed at the forefront of the climate change conversation, with new technologies being developed to help limit the impact that we are having on our environment.

As companies search for more sustainable ways to operate, the renewables sector is experiencing unprecedented growth. The creation of even more solar and wind farms, alongside investment in traditionally more complex power sources such as wave-energy, are helping businesses to meet their sustainability goals and limit our reliance on more high-pollutant forms of power generation. Encouraged by the increased interest in renewable power sources, technology companies are taking advantage and helping them to improve their energy efficiency, whether that be by automating parts of the manufacturing process or using advanced analytics and computational-approaches to highlight efficiency gaps in wind turbine design.

Emerging tech is powering renewables' efficiency

At present, there is a particular focus on the ability of emerging technologies such as AI, machine learning (ML), and the Internet of Things (IoT) to help increase renewable energy efficiency. Intel's recent survey with Concentrix sought to find out how emerging technologies can be applied to sustainable practices moving forward. 74% of respondents decided that AI will be used to overcome typical sustainability challenges, and 64% believed the same to be true of IoT projects. A further 90% agreed that emerging technology will have a positive effect on environmental sustainability by enabling broader toolsets which will allow specialists to interact and collaborate more effectively.

In practice, these technologies are already having an impact on the renewables sector. Solar fields and wind farms are incredibly complex projects that rely on IoT and sensor-based technology to function at maximum capacity. IoT accomplishes this by providing live, actionable data on each power station. Wind turbine and solar panel health can be assessed in real time, and the information gathered used to adjust to changing weather patterns and abnormal conditions. Moreover, IoT's ability to collect historical data for modelling purposes can help energy companies looking to increase the efficiency of their power stations and overall energy output.

IoT is also capable of facilitating better renewable energy management at the grid. Warren Westrup, director of business development, utilities, for Sierra Wireless claims that "with IoT, utilities can collect data and better manage their grid by detecting and restoring service outages quickly". Coined the ‘Internet of Energy', the application of IoT with power grids is allowing utilities to effectively monitor, control, and optimise the renewable power sources connecting to the grid. In turn, this has resulted in improved grid reliability, reduced energy costs, and an increase in the amount of renewable energy capable of being stored and used.

Matt Johnson, VP, Business Development at EnergyHub, discusses how AI and ML are able to address some of the challenges presented by renewable power. Energy grids are already highly complex systems, and as more renewable sources of power enter the grid each source "add[s] more endpoints and layers of complexity" for businesses to navigate. To combat this issue and increase the amount of renewable power on the grid, Johnson believes utilities companies should make use of "AI-powered software that allows them to coordinate the performance of millions of connected devices to make the grid more efficient, flexible, and responsive". Johnson continues that the sophisticated coordination required to provide energy generation, demand, and storage for renewable power sources in the grid can only be accomplished with AI-powered software.

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