Guosheng: The high increase in power demand in data centers is driving the simultaneous rise in demand and price of geothermal energy.
Trump calls for US tech giants' data centers to be self-sufficient in power, or to catalyze the demand for off-grid power systems for US data centers.
Guosheng published a research report stating that recently, Trump demanded that American technology giants' data centers be self-sufficient in electricity, or catalyze the construction demand for off-grid power supply systems for American data centers. Looking at the potential for geothermal power generation, the global geothermal potential is about 162GW, nearly 10 times the installed capacity, with the potential geothermal capacity in the US and Asia (mainly Indonesia) being about 35.0GW/74.3GW. Currently, Meta (META.US) and Google (GOOGL.US) have deployed several hundred MW-level geothermal power generation projects, and the next generation of enhanced geothermal technology is expanding the applicable scenarios for geothermal energy. The purchase price of geothermal power for AI data centers has risen to $100/MWh, an increase of over 45% from 2024.
Guosheng's main points are as follows:
- The cumulative installed capacity of geothermal power globally and in the US is 16.5GW and 3.9GW, respectively, with a potential geothermal space of about 10 times.
- Most of the global geothermal resources are distributed near the Pacific Ring of Fire. According to Oramt, as of August 2025, the cumulative installed capacity of geothermal power globally is about 16.5GW, with the US accounting for approximately 24% of that. Looking at other major regions, Asia (mainly Indonesia) and Europe have cumulative installed capacities of about 4.9GW and 3.6GW, respectively, accounting for approximately 31% and 23% of global geothermal energy, respectively. In terms of geothermal power potential, the global geothermal potential is about 162GW, almost 10 times the installed capacity, with the potential geothermal capacity in the US and Asia (mainly Indonesia) being about 35.0GW/74.3GW.
- Geothermal power in the US: High demand for power in data centers is driving demand and prices for geothermal power installations.
- quantity: Meta and Google have already deployed several hundred MW-level geothermal power generation projects, with the next generation of enhanced geothermal technology expanding the applicable scenarios for geothermal energy. 1) Meta: In 2024, Meta signed a 150MW geothermal power purchase agreement with SageGeosystems, with the first phase expected to be online by 2027. In June 2025, Meta signed a 150MW geothermal power purchase agreement with XGSEnergy to secure power for its data center in New Mexico, expected to be completed by 2030.
2) Google: In 2024, Alphabet Inc. Class C signed a 115MW geothermal energy agreement with Fervo Energy and NVEnergy to supply its data center in Nevada. The next generation of enhanced geothermal (EGS) technology is suitable for areas with dry hot rocks and no natural fluid flow, further expanding the applicable scenarios for geothermal energy.
- price: The purchase price for geothermal power for AI data centers has risen to $100/MWh, an increase of over 45% from 2024. Ormat's financial report shows that the company is in talks with super-large-scale cloud service providers and data centers for geothermal projects with a scale of approximately 250MW, with a PPA purchase price above $100/MWh, representing a growth of over 45% from 2024 (reference to Kaishan Group's 2024 operating projects in the US).
- Focus target: Kaishan Group (300257.SZ)
As of the end of 2024, Kaishan Group disclosed four geothermal projects under construction in the US, totaling approximately 62-79MW, which is estimated to contribute revenue of $0.5-0.7 billion based on a purchase price of $100/MWh. Considering that the data has not been updated to the latest, Kaishan Group may have more geothermal projects in the US.
- Risk warning
Lower-than-expected demand for data centers, intensified industry competition risk, policy change risk, and risk related to calculation assumptions.
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