PNNL

Sohom Datta has been a power systems research engineer with the Electricity Infrastructure and Buildings Division at Pacific Northwest National Laboratory (PNNL) since 2019. In this role, he has spearheaded numerous projects in power systems modeling and simulation, phasor measurement units data analysis, and energy market data analysis for pivotal initiatives such as the Department of Energy’s HydroWires, Advanced Grid Modeling, Advanced Research Projects Agency-Energy (ARPAe), and the Bureau of Ocean Energy Management’s National Offshore Wind Research and Development Consortium.

Before joining PNNL, Datta worked with the California Independent System Operator (CAISO) from 2017 to 2019 as a market validation and quality analyst in the Market Quality and Renewable Integration division. He primarily focused on energy market data analysis with an emphasis on the Energy Imbalance Market, ancillary services, flexible ramping products, and price spikes. Datta also has experience working as a power systems planning consultant with Siemens Power Technology International (Siemens PTI), USA where he was responsible for developing steady-state and dynamic models to perform North American Electric Reliability Corporation model validation (NERC MOD 25/26/27), transmission risk assessment, and contingency analysis for upcoming wind and solar generation projects in the United States. He has also worked with Kalkitech, India, as an analyst developing advanced tools and software for power systems and power plant applications for electric utilities using machine learning.

Datta earned his BS degree in electrical engineering from the Maulana Abul Kalam Azad University of Technology, India in 2009, an MS degree in power systems engineering from the Indian Institute of Technology Delhi in 2011, and his PhD in electrical engineering from the Arizona State University in 2017. During his doctoral studies, he made significant contributions to the field through his work on a National Science Foundation-funded project with Power Systems Engineering Research Center. This project explored the efficacy of using risk-based techniques for dynamic assessment of the electricity grid with high penetration of renewable generation, a topic of utmost importance in today's energy landscape.

• Power system stability, resilience, and security assessment
• Impact of extreme weather events (wildfires, heatwaves, cold snaps, etc.) on grid resilience
• Applications of artificial intelligence/machine learning methods in power systems applications

• Data analytics
• Energy markets
• Modeling and simulation
• Machine learning
• Optimization techniques
• Power system operations and stability

• PhD in Electrical Engineering, Arizona State University, 2017
• MS in Power Systems Engineering, Indian Institute of Technology Delhi, 2011
• BS in Electrical Engineering, Maulana Abul Kalam Azad University of Technology, India, 2009

• IEEE Senior Member, IEEE Power and Energy Society Member, IEEE Young Professionals Member, CIGRE U.S. National Committee Member
• Reviewer with IEEE PES Transactions on Power Systems, Open Access Journal for Power and Energy

• Reinforcement Learning for Voltage Control (iEdison No. 0685901-22-0056 - ARPA-E)
• An ML Framework to Deconstruct the Primary Drivers for Electricity Market Price Events (iEdison No. 0685901-22-0248)
• Wildfires Risk Evaluation of the System Framework Tool (iEdison No. 0685901-23-0068)
• Hydropower Modeling Gap Tools (iEdison No. 0685901-23-0073)
• ARPAE HADREC GUI (ARPA-E 12/CJ000/09/02, iEdison No. 0685901-24-0112)

2025

• Datta S., Z. Hou, M. Jain, and S. Naqvi. 2025. "Artificial Intelligence and Machine Learning Applications in Modern Power Systems." In Smart Cyber-Physical Power Systems: Solutions from Emerging Technologies, edited by A. Parizad, H.R. Baghaee and S. Rahman. Piscataway, New Jersey:IEEE. PNNL-SA-193473. doi:10.1002/9781394334599.ch2
• Douville T.C., S. Datta, J.T. Barlow, S. Bhattacharya, P.R. Maloney, S. Naqvi, and S.A. Siddiqui, et al. 2025. Assessment of Regional Interconnections to Meet Southeast Asia's Renewable Energy Targets. PNNL-37245. Richland, WA: Pacific Northwest National Laboratory. Assessment of Regional Interconnections to Meet Southeast Asia's Renewable Energy Targets
• Oikonomou K., P.R. Maloney, S. Bhattacharya, J.T. Holzer, O.P. Anderson, X. Ke, and J.K. Westman, et al. 2025. "Energy Storage Planning for Enhanced Resilience of Power Systems Against Wildfires and Heatwaves." Journal of Energy Storage 119:116074. PNNL-SA-200219. doi:10.1016/j.est.2025.116074

2024

• Anderson A.A., S. Datta, T. Vu, T. Ahmad, Y. Chen, C.H. Allwardt, and P. Sharma, et al. 2024. "Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration." In IEEE Power & Energy Society General Meeting (PESGM 2024), July 21-25, 2024, Seattle, WA, 1-5. Piscataway, New Jersey:IEEE. PNNL-SA-192145. doi:10.1109/PESGM51994.2024.10688844
• Datta S., V.H. Chalishazar, J.K. Westman, T.M. Saltiel, J.M. Deines, S.A. Siddiqui, and K.A. Tamaddun, et al. 2024. "Enhancing Grid Resilience during Wildfires in Socioeconomic Vulnerable Regions using Powered and Non-Powered Hydro Dams." In IEEE Power & Energy Society General Meeting (PESGM 2024), July 21-25, 2024, Seattle, WA, 1-5. Piscataway, New Jersey:IEEE. PNNL-SA-192289. doi:10.1109/PESGM51994.2024.10688862
• He L., S.A. Siddiqui, S. Nekkalapu, S. Datta, T.C. Douville, K. Oikonomou, and M. Maharjan. 2024. "Multi-temporal Analysis and Techno-Economic Evaluation of Offshore Wind Energy Integration to the Western Interconnection." IEEE Open Access Journal of Power and Energy 11, no. _:383 - 395. PNNL-SA-194209. doi:10.1109/OAJPE.2024.3440173
• Huang Q., R. Huang, T. Yin, S. Datta, X. Sun, Z. Hou, and J. Tan, et al. 2024. "Towards Intelligent Emergency Control for Large-scale Power Systems: Convergence of Learning, Physics, Computing and Control." Electric Power Systems Research 235, no. _:Art. No. 110648. PNNL-SA-190811. doi:10.1016/j.epsr.2024.110648
• Kim J., M. Maharjan, W. Kim, B. Vyakaranam, S. Datta, J.K. Westman, and Q.H. Nguyen, et al. 2024. "Quantified Fast Frequency Response of Inverter-Based Resources for Bulk-Power System Study." In IEEE Power & Energy Society General Meeting (PESGM 2024), July 21-25, 2024, Seattle, WA, 1-5. Piscataway, New Jersey:IEEE. PNNL-SA-192153. doi:10.1109/PESGM51994.2024.10688466
• Kincic, S., N.A. Samaan, S. Datta, A. Somani, H. Yuan, J. Tan, R. Bhattarai, et al. 2023. Hydropower Modeling Gaps in Planning and Operational Studies. PNNL-33836. Richland, WA: Pacific Northwest National Laboratory. 
• Mitra, B., S. Datta, S. Kincic, N. Samaan, and A. Somani. 2024. "Gaps in Representations of Hydropower Generation in Steady-State and Dynamic Models." 2024 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2024, pp. 1–5. http://dx.doi.org/10.1109/ISGT59692.2024.10454207. 
• Nguyen Q.H., S. Seo, W. Kim, E. Muljadi, N.A. Samaan, W. Du, and M. Maharjan, et al. 2024. "Optimal Droop Setting for Congestion Reduction in a 100% Grid-Forming Inverter-based Power System." In IEEE Power & Energy Society General Meeting (PESGM 2024), July 21-25, 2024, Seattle, WA, 1-5. Piscataway, New Jersey:IEEE. PNNL-SA-192119. doi:10.1109/PESGM51994.2024.10688786
• Wang, D., B. Mitra, S. Nekkalapu, S. Datta, B. Mathew, R. Meyur, H. Wang, and S. Kincic. 2024. "Hy-DAT: A Tool to Address Hydropower Modeling Gaps Using Interdependency, Efficiency Curves, and Unit Dispatch Models." 2024 IEEE Green Technologies Conference (GreenTech), Springdale, AR, USA, 2024.

2023

• Kincic, S., N. A. Samaan, S. Datta, A. Somani, H. Yuan, J. Tan, R. Bhattarai, et al. 2023. Hydropower Modeling Gaps in Planning and Operational Studies. PNNL-33836. Richland, WA: Pacific Northwest National Laboratory. 
• Chalishazar, V. H., J. Westman, J. Deines, S. Datta, et al. 2023. "Wildfire Risk Evaluation Framework for Grid Operations and Planning." 2023 IEEE Power & Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023, pp. 1–5. https://www.doi.org/10.1109/PESGM52003.2023.10252841.
• Jain, J., X. Sun, S. Datta, and A. Somani. 2023. "A Machine Learning Framework to Deconstruct the Primary Drivers for Electricity Market Price Events." 2023 IEEE Power & Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023, pp. 1–5. https://www.doi.org/10.1109/PESGM52003.2023.10252752.
• Sun, X., S. Datta, X. Li, Z. Hou, Q. Huang, R. Huang, and Y.Chen. 2023. "Smart Sampling-based Scenario Selection for Real Power System Data." 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2023, pp. 1–5. https://doi.org/10.1109/ISGT51731.2023.10066458.
• Seo, S., E. Muljadi, Q. Nguyen, S. Datta, N. Samaan, B. Vyakaranam, W. Du, Y. Liu, Y. Chen, J. Kim, and M. Maharajan. 2023. "Modified Steady-State Power Flow for Grid with High Penetration of Inverter-Based Resource." 2023 IEEE Energy Conversion Congress and Exposition (ECCE), Nashville, TN, USA, 2023, pp. 266–272. doi: 10.1109/ECCE53617.2023.10362225.
• Douville, T., M. Severy, S. Datta, S. Siddiqui, L. He, K. Oikonomou, S. Nekkalapu, et al. 2023. “An Offshore Wind Energy Development Strategy to Maximize Electrical System Benefits in Southern Oregon and Northern California - National Offshore Wind.” Richland, WA, United States: National Offshore Wind Research and Development Corporation (NOWRDC) and Bureau of Ocean Energy Management (BOEM). https://nationaloffshorewind.org/projects/an-offshore-wind-energy-development-strategy-to-maximize-electrical-system-benefits-in-southern-oregon-and-northern-california/.
• Levin, T., A. Somani, K. Oikonomou, S. Datta, N. Samaan, S. Platthotam, Z. Zhou, M. Mahalik, T. Veselka, Q. Ploussard, J. Kwon, H. Yang, A. M. Campbell, W. Hartini, G. Stark, and G. Brinkman. 2023. Hydropower Value Drivers. United States. https://doi.org/10.2172/1991482. https://www.osti.gov/servlets/purl/1991482.

2022

• Datta, S., A. Somani, M. E. Alam, X. Sun, V. Fotedar, and A. Banicki. 2022. "Changes in Hydropower Resource Operations Following Participation in the CAISO Energy Imbalance Market - A Case Study." In IEEE Power & Energy Society General Meeting (PESGM 2022), July 17–21, 2022, Denver, CO, 1–5. Piscataway, New Jersey: IEEE. PNNL-SA-168520. https://www.doi.org/10.1109/PESGM48719.2022.9916782.
• Kim, J., E. Muljadi, B. Vyakaranam, Q. H. Nguyen, M. Maharjan, A. Tbaileh, S. Datta, et al. 2022. "Enhanced Frequency Support Scheme of Generic Inverter-Based Resource Models for Renewable-Dominated Power Grids." In IEEE Energy Conversion Congress and Exposition (ECCE 2022), October 9–13, 2022, Detroit, MI, 1–7. Piscataway, New Jersey: IEEE. PNNL-SA-177207. https://www.doi.org/10.1109/ECCE50734.2022.9948100.
• Ren, L. A. Osman, F. Lin, N.-Y. Chiang, M. Sun, R. Melville, F. Koufogiannis, M. Moulin, T. Wagner, F. Li, Q. Zhang, K. Tomsovic, S. Louis, S. Jinyuan, A. Abhishek, S. Datta, X. Sun, M. Jain, and D. Bertagnolli. 2022. WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report). United States. https://doi.org/10.2172/1902136.  https://www.osti.gov/servlets/purl/1902136.

2021

• Hanif, S., S. Poudel, S. Datta, and V. H. Chalishazar. 2021. Modeling Framework for Evaluating Grid Disturbances. PNNL-32247. Richland, WA: Pacific Northwest National Laboratory. 
• Somani A., S. Datta, S. Kincic, V. H. Chalishazar, B. Vyakaranam, N. A. Samaan, A. Colotelo, et al. 2021. Hydropower's Contributions to Grid Reliability and Resilience. PNNL-30554. Richland, WA: Pacific Northwest National Laboratory. 
• Sun, X., X. Li, S. Datta, X. Ke, Q. Huang, R. Huang, and Z. Hou. 2021. "Smart sampling for reduced and representative power system scenario selection." IEEE Open Access Journal of Power and Energy 8. PNNL-SA-159391. https://doi.org/10.1109/OAJPE.2021.3093278.