Texas Tech University

Suhas Pol, Ph.D.

Director and Assistant Professor
Renewable Energy

Email: suhas.pol@ttu.edu

Phone: (806) 834-4515

Dr. Suhas Pol is the Director of the Renewable Energy Program at Texas Tech University. His research is focused on advancing innovations to improve wind farms' performance, exploring the use of Data Science for Renewable Energy applications, and identifying technological and policy changes to promote Distributed Energy. As an administrator, he works on curriculum development and enhancement to meet Renewable Energy workforce needs. Furthermore, he actively participates in external service activities. Most notably, he is the Education Committee Chair for the North American Wind Energy Association, Energy Policy Advisory Committee member for PowerHouse TX, and member of the Distributed Wind Monitoring working group.

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Research Interests

Dr. Pol is the Principal Investigator for the Renewable Energy Technology Laboratory at TTU (Texas Tech University). His research can be classified broadly in the following areas:

  • Wind farm wakes: Strategies to mitigate adverse wind turbine wakes are currently under development. These are validated at the Hyper Accelerated Wake Simulation (HAWKS) simulation platform, which is a wind tunnel-based platform consisting of fully controllable model turbines that emulate full-scale wind turbine controls and their impact on wakes.
  • Distributed Energy: Solutions for distributed wind energy challenges of improper site selection, wind resource forecasting and its impact on low return on investment, and lack of policy and regulation are being researched under this area.
  • Data Science in Renewable Energy: Forecasting is a major challenge in the renewable energy industry. Forecasting challenges are also experienced when predicting the Local Marginal Price (LMP) of electricity. Data Science in Renewable Energy research is being pursued to devise novel forecasting models to forecast production and market pricing.
Additionally, Dr. Pol is exploring commercial potential of technologies developed and translating engineering techniques to healthcare applications.

Education

  • 2010: Ph.D. in Mechanical Engineering, Arizona State University, USA.
  • 2006: M.S. in Mechanical Engineering, University of Utah, USA.
  • 2002: B.E. in Mechanical Engineering, VJTI, University of Mumbai, India.

Teaching

Undergraduate Graduate
  • RE 1110:− Renewable Energy Analytical Modeling Lab
  • RE 2310:− Methods for Renewable Energy Resource Characteristics
  • RE 3300:− Renewable Energy Science and Technology I
  • RE 3301:− Renewable Energy Science and Technology II
  • RE 4320:− Independent Study in Renewable Energy, Wind and Hydro Power applications
  • RE 3303:− Data Science in Renewable Energy
  • RE 5302:− Renewable Energy Systems
  • RE 5304:− Applications of Applied Renewable Energy Technology

Awards & Honors

  • R&D 100 Award, as part of collaborative team consisting of Texas Tech U, Sandia National Lab, and AeroMINE Inc., for developing AeroMINE a novel wind energy harnessing device, December 2021.
  • State of Texas GLEAMM SPARK iLaunch Award (2nd place), given to Tissue Kinematics Quantification team, April 2018.
  • TTU Presidents Innovation Award, given to Tissue Kinematics Quantification team, January 2018.
  • TTU Accelerator Award, sponsored by Market Lubbock, Inc. & Lubbock Economic Development Corporation (LEDA), given to Tissue Kinematics Quantification team, June 2017.
  • IEEE best paper award 13th LACCEI Annual International Conference, Santo Domingo, Dominican Republic., July 2015.
  • Spot Award Los Alamos National Laboratory, to recognize going beyond job requirements during the construction of the LANL wind turbine field site, July 2012.

Renewable Energy