Zanskar's Vision: Unlocking the Untapped Potential of Geothermal Energy
The Earth's crust holds an untapped treasure of energy, and Zanskar is on a mission to unlock it. With a bold vision, Zanskar's co-founder and CEO, Carl Hoiland, believes that the potential of geothermal power is being significantly underestimated. The Department of Energy estimates that geothermal energy could generate a staggering 60 gigawatts, or nearly 10% of U.S. electricity, by 2050. However, Hoiland argues that this figure is conservative, especially when considering the untapped potential of conventional geothermal energy.
The conventional approach to geothermal energy, which relies on naturally fractured hotspots, has been stagnant, generating only 4 gigawatts in the United States. This is in stark contrast to the enhanced geothermal methods, which have been making strides with the use of fracking techniques to access hot rock deep underground. Companies like Fervo and Sage Geosystems are leading the way in this field, and experts agree that it has immense potential. But Hoiland believes that the conventional approach, often overlooked, holds the key to unlocking a terawatt-scale opportunity.
Zanskar is leveraging AI to revolutionize conventional geothermal energy. By employing supervised machine learning models, they have successfully resuscitated a dormant power plant in New Mexico and identified two new sites with a combined potential of over 100 megawatts. This breakthrough has not gone unnoticed, attracting a substantial $115 million Series C funding round led by Spring Lane Capital, with participation from prominent investors.
The company's AI-driven approach addresses a critical challenge in geothermal exploration: the difficulty in identifying potential sites. Hoiland explains that many potential geothermal sites have been overlooked because people have been searching for surface indicators like hot springs or volcanoes. However, about 95% of geothermal systems lack such visible signs. Zanskar's AI algorithms, trained on a range of data including past accidental discoveries, have proven effective in identifying promising sites.
To develop these sites, Zanskar employs a Bayesian evidential learning (BEL) approach, which uses existing data to build assumptions and then models to falsify those hypotheses, providing probabilities for each. Additionally, they have developed a geothermal simulator to fill in any data gaps. So far, their strategy has been successful, with three out of three explored sites considered successful.
Zanskar's ambitious goal is to support at least a gigawatt of generating capacity. With a focus on the U.S. West, which has the most potential, they aim to secure project finance investors, who offer lower-cost capital compared to venture capitalists. By achieving this, Zanskar believes they can navigate the 'valley of death' that has challenged many climate tech startups.
While Hoiland acknowledges that Zanskar has not solved all challenges in geothermal resource exploration, he remains optimistic about their progress. He confidently states, 'We now know this is the future of exploration. This is going to change geothermal in very short order.'
As Zanskar continues to push the boundaries of geothermal energy, the industry awaits the results of their innovative approach, eager to see if they can unlock the true potential of this sustainable energy source.
