Title: |
Artificial Intelligence Based Optimizing Solutions for the Geothermal Power Plants |
Authors: |
Namrata BIST, Gautami TRIPATHI, Anirbid SIRCAR, Kriti YADAV |
Key Words: |
Artificial Intelligence, optimization, power plant, future predictions, model, machine learning |
Conference: |
Stanford Geothermal Workshop |
Year: |
2021 |
Session: |
Emerging Technology |
Language: |
English |
Paper Number: |
Bist1 |
File Size: |
393 KB |
View File: |
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The geothermal power plant situated at Dholera, Gujarat like every power plant is designed for long term electricity generation. Hence it gets crucial to determine the present production flow rate in order to ascertain the future power demands. While designing the plant, the calculations and estimations are done based on the current future production predictions. These predictions come in handy while designing the surface equipments in order to make the plant cost effective. One of the most prudent problems related to geothermal power plants is inability to accurately estimate the future production rates and hence makes the plant operations inefficient. Artificial intelligence (AI) has the potential to empower the system with intelligent behavior, learning and informed decision making capabilities for the geothermal energy sector. These tools can be used to predict accurate future production prediction as they rely on reliable field data instead of assumptions. A predictive model is designed and the results are correlated with the past data. The results generated by this model are very encouraging. AI can also be developed as an alternative approach to conventional methods to eliminate dealing with uncertainties in the geothermal reservoirs.
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