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Dr. KIRAN TEEPARTHI

ABOUT
NAME: Dr. KIRAN TEEPARTHI

M.TECH: NIT Jamshedpur

E- MAIL: kiran.t39@nitandhra.ac.in

POSITION: Assistant Professor

PhD: NIT Warangal

PHONE: +91 9533938371


AREAS OF INTEREST: Power System Security and Stability; Power System Operation and Control; Renewable Energy integration issues; Power System Optimization; Artificial Intelligence (AI) applications to Power Systems

PROFILE

Professional( Teaching/Research) Experience:

  1.   Assistant Professor, NIT AP (November 2019 to till date)
  2.  Ad-hoc faculty, NITAP(July 2017 to November 2019)
  3. Three years of research experience (July 2014 to June 2017)
  4. AssistantProfessor, SNIST Hyderabad (Dec 2012-June 2014).

Course Taught:

1. Basic Electrical Engineering

2. Circuit Theory-I

3. Circuit Theory-II

4.  Network Analysis

5. Power Systems-II

6. Digital Signal Processing 

7. Soft Computing Techniques

Research Publications

Refereed Journals:
  1. Kiran Teeparthi and D.M. Vinod Kumar, “Security constrained optimal power flow with wind and thermal power generators using fuzzy adaptive artificial physics optimization algorithm”, Neural Computing and Applications, Springer, Vol: 29, Pg. nos:855–871 (2018). (DOI: 10.1007/s00521-016-2476-4)
  2. Kiran Teeparthi and D.M. Vinod Kumar, “Multi-Objective Hybrid PSO-APO Algorithm based Security Constrained Optimal Power Flow with Wind and Thermal Generators”, Engineering Science and Technology, an International Journal, Elsevier, Vol: 20, Pg. nos:411–426 (2017). (DOI: 10.1016/j.jestch.2017.03.002)
  3. Kiran Teeparthi and D.M. Vinod Kumar, “Dynamic security assessment and enhancement using a new hybrid PSO-APO algorithm”, Engineering, Technology & Applied Science Research, Vol: 7, Pg. nos:2124–2131 (2017). (DOI: 10.48084/etasr.1477)
  4. Kiran Teeparthi and D.M. Vinod Kumar, “Power System Security Assessment and Enhancement: A Bibliographical Survey”, Institution of Engineers (India): Series B, Springer, Vol: 101, Pg. nos:163–176 (2020). (DOI: 10.1007/s40031-020-00440-1)
  5. Kiran Teeparthi and D.M. Vinod Kumar, “An Improved Artificial Physics Optimization Algorithm Approach for Static Power System Security Analysis”, Institution of Engineers (India): Series B, Springer, Vol: 101, Pg. nos: 347–359 (2020). (DOI: 10.1007/s40031-020-00457-6)
  6. Sreenadh Batchu and Kiran Teeparthi , "A Preventive Transient Stability Control Strategy Through Individual Machine Equal Area Criterion Framework," in IEEE Access, vol. 9, pp. 167776-167794, 2021. (DOI: 10.1109/ACCESS.2021.3136593)
  7. Vishalteja Kosana, Santhosh M, Kiran Teeparthi, " A novel hybrid deep learning framework for wind speed forecasting using autoencoder based convolutional long short-term memory neural network”, International Transactions on Electrical Energy Systems, Wiley, Vol: 31, 2021. (DOI: https://doi.org/10.1002/2050-7038.13072)
  8. Vishalteja Kosana, Kiran Teeparthi, Santhosh Madasthu, Santosh Kumar, "A novel reinforced online model selection using Q-learning technique for wind speed prediction", Sustainable Energy Technologies and Assessments, Elsevier, Volume 49, 2022.  (DOI:https://doi.org/10.1016/j.seta.2021.101780).
  9. Vishalteja Kosana, Kiran Teeparthi, Santhosh Madasthu, "Hybrid wind speed prediction framework using data pre-processing strategy based autoencoder network", Electric Power Systems Research,  Elsevier, Volume 206, 2022. (DOI: https://doi.org/10.1016/j.epsr.2022.107821)
  10. Kosana V., Kiran Teeparthi,  & Madasthu S, "Hybrid convolutional Bi-LSTM autoencoder framework for short-term wind speed prediction", Neural Computing and Applications, Springer, 2022. (DOI: https://doi.org/10.1007/s00521-022-07125-4)
  11. Vishalteja Kosana, Santhosh Madasthu,  Kiran Teeparthi, Santosh Kumar, "A novel dynamic selection approach using on-policy SARSA algorithm for accurate wind speed prediction," Electric Power Systems Research,  Elsevier, 2022.  (DOI:https://doi.org/10.1016/j.epsr.2022.108174).
  12. Sreenadh Batchu and Kiran Teeparthi, "Transient Stability Enhancement Through Individual Machine Equal Area Criterion Framework Using an Optimal Power Flow" in IEEE Access, vol. 10, pp. 149433 - 49444, 2022. (DOI: 10.1109/ACCESS.2022.3173422)
  13. Sreenadh Batchu and Kiran Teeparthi, "A new method for operating point free power system transient stability situational awareness based on single machine equivalent approach" Engineering Reports, Wiley, 2022. (DOI: https://doi.org/10.1002/eng2.12519)
  14. Vishalteja Kosana, Kiran Teeparthi, and Santhosh Madasthu, "A novel and hybrid framework based on generative adversarial network and temporal convolutional approach for wind speed prediction", Sustainable Energy Technologies and Assessments, Elsevier, Volume 53, 2022.  (DOI:https://doi.org/10.1016/j.seta.2022.102467).
  15. Y.Raghuvamsi, Kiran Teeparthi, and Vishalteja Kosana, "A novel deep learning architecture for distribution system topology identification with missing PMU measurements", Results in Engineering,  Elsevier, 2022.  (DOI:https://doi.org/10.1016/j.rineng.2022.100543).

National/ International Conferences:

  1.  Kiran Teeparthi and D.M. Vinod Kumar, “Grey wolf optimization algorithm based dynamic securityconstrainedoptimalpowerflow”, 19thNational Power System Conferenc e(NPSC-2016), IIT Bhubaneswar,19-21Dec-2016, pp.1-6.
  2. Kiran Teeparthi and D.M. Vinod Kumar, “Dynamic security enhancement using an improved artificialphysicsoptimizationmethod”, National Systems Conference (NSC-2016), NITWarangal, 4-6Nov2016,pp. 1-6
  3. Vishal K and Kiran Teeparthi, “Efficient Epileptic seizure prediction based on IoT and machine learning methods”, International conf. on Distributed Computing and Internet tech. (11th student research symposium 2021),KIITBhubaneswar,7-10January2021.
  4. Sreenadh Batchu, Raghuvamsi Yarlagadda, and Kiran Teeparthi, "An intelligent system design and analysis for transient stability assessment using four sample input feature vector approach", IEEE International Conference on Intelligent Systems, Smart and Green Technologies (ICISSGT), 2021, IEEE Vizag Bay Section.
  5.  Vishalteja Kosana, Santhosh M, Kiran Teeparthi, A hybrid wind speed forecasting model using complete ensemble empirical decomposition with adaptive noise and convolutional support vector machine”, 9th IEEE International Conference on Power Systems (ICPS), 2021, IIT Kharagpur.

  6. Y.Raghuvamsi, Vishalteja Kosana, Kiran Teeparthi, “Power System State Estimation and Forecasting using CNN based Hybrid Deep Learning Models”, IEEE International Conference on Technology, Research, and Innovation for BEtterment of Society (TRIBES – 2021), IIIT Naya Raipur.

Ph.D. Supervision (Ongoing): 05

S.No.

Nameofstudent

Reg. Year &status (FT/PT)

ThesisTitle


Completed/ Ongoing

1.

S M k Patnaik

Dec-2019, Part-time scholar

 

Power System Inertia estimation using measured frequency transients


Ongoing

2.

Sreenadh Batchu

July-2020, Full-time scholar

 

Dynamic Security Assessment and Enhancement in Power system


Ongoing

3.

Yarlagadda Raghuvamsi

July-2020, Full-time scholar

 

Investigations of Uncertainties in Distribution System State Estimation using Deep Learning Approaches


Ongoing

 4.

Bala Saibabu Bommidi

July-2020, Part-time scholar

 

Data-Driven Models for Wind Speed Forecasting


Ongoing

 5.

Parri Srihari

July-2020, Part-time scholar

 

Data-Driven Models for Wind Speed Forecasting

 

Ongoing

Workshop/Faculty Development Programme organized:

  1. Organized Five Days Online FDP on Emerging Trends in Artificial Intelligence Methods to Power Systems, Signal Processing, and Control, by Dept. of Electrical Engineering, NIT Andhra Pradesh during 02 – 06, November 2020.
  2. Organized Five Days Online FDP under AICTE Training and Learning (ATAL) Academy on Data-Driven Strategies in Smart Power System and Control -2021, by Dept. of Electrical Engineering, NIT Andhra Pradesh during 22 – 26, November 2021.

Additional Responsibilities:

  1. Associate Dean, Alumni Affairs
  2. Associate Dean, Student Welfare(Physical Education & Sports Activities)
  3. Faculty In-charge Sports & Games
  4. Coordinator, Career Development & Placements (PG)
  5. Warden NIT Hostels