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Development.
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Clean baseload solutions
This technology has the potential to store and generate electricity on a large scale by using seawater as a means of energy storage, enabling the integration of intermittent renewable sources like wind and solar into the grid.
Sea water pumped storage can provide a consistent source of electricity, stabilise the grid, and reduce our reliance on fossil fuels, thus playing a pivotal role in mitigating climate change and ensuring a resilient and sustainable energy future.
Machine learning.
By integrating machine learning algorithms with remote sensing data and vector data outlining geographical boundaries, the software aims to revolutionize the process of generating potential site options for client countries. It empowers users to specify project size and cost criteria, and then systematically employs machine learning to sift through available data sources, rapidly presenting alternative locations that align with the specified parameters.
Algo decisions.
This cutting-edge software not only identifies potential sites but also provides comprehensive justifications for its selections, thus serving as a valuable decision-making tool for energy sector stakeholders. In addition, the software's machine learning capabilities extend to ranking these preferred choices, enabling a comparative assessment of the identified sites based on their suitability for seawater pumped storage projects.
Integration of tech.
This research marks a pivotal step in the integration of machine learning into the energy sector, promising to significantly enhance the efficiency and precision of site selection processes. Ultimately, it plays a pivotal role in accelerating the adoption of this sustainable energy technology and contributing to the global shift towards cleaner and more reliable energy sources.