Wind power resource assessment and wind-hydrogen generation potential: a case study

ABSTRACT

A case study of assessing wind power generation potentials for seven locations in a district of India is presented in the paper with special focus on small wind turbines with low cut in speeds operating in hybrid complementary mode with a hydrogen generation system. The major motivation for the study is to accelerate the efforts for the region toward carbon neutral status. The wind speeds are obtained for one hour time intervals for all days for 20 years during the time period 2001–2020 for the seven locations from European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA-5) data. Mean wind speeds for the period are analyzed and wind rose diagrams are generated using the WindroseAxes library in Python environment. Wind power potential assessment has been carried out using the data. From the analysis, it has been noted that the coastal and southern regions of the district get higher wind speeds and have higher power generation potential. Analysis has shown that based on the Beaufort scale, usually the available wind speed is in the calm to moderate breeze types (<0.3–8 m/s). Study has shown that deployment of small wind turbines may be beneficial, to potentially facilitate decentralized power generation. A small wind turbine with cut-in speed 2.5 m/s and cutoff speed 15.5 m/s is selected for the study. The region has a generic upper speed availability of 8 m/s. The corresponding wind power potential values are 0.84 and 27.58 kW. Hydrogen, considered as an energy carrier, and a clean fuel for the future, is proposed as an option for complementary energy storage. Hydrogen, generated from wind energy through electrolysis, may be stored and used to meet the peak power demands. A preliminary analysis of the hydrogen generation potential of the region via the power-to-gas route is also presented. The analysis also points to the necessity for developing small wind turbines, which can generate power at lower cut-in speeds, for maximum utilization of wind power generation potential. The methodology can be adapted to other regions.

KEYWORDS:

• Wind power generation
• small wind turbine
• wind power potential assessment
• hydrogen energy
• energy storage

Nomenclature

Table

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Rakesh Narayana Sarma

Rakesh Narayana Sarma received his PhD in 2020 from Indian Institute of Science, Bengaluru, India. He had received his B. Tech. in Mechanical Engineering from Government Engineering College, Barton Hill, Thiruvananthapuram, University of Kerala, India, in 2010, and M. Tech. in Mechanical Engineering (Energy Engineering and Management) from National Institute of Technology Calicut, Kozhikode, India, in 2012, respectively. His research interests include energy systems, renewable energy, thermal science and engineering, and fluid dynamics.

Vineeth Kumar

Vineeth Kumar received his Bachelor of Computer Applications degree in 2018 from Amrita Vishwa Vidyapeetham, Amrita University, Amritapuri, Kerala, India. He is currently pursuing Master of Computer Applications from College of Engineering Trivandrum, APJ Abdul Kalam Technological University, Kerala, India. His research interests include Data Analytics and Machine Learning.

Suresh Lal S R

Suresh Lal S R received his Master’s degree in Mechanical Engineering in 2018 from Indian Institute of Technology Madras, Chennai, India. He had received his B. Tech degree in Mechanical Engineering from the College of Engineering, Trivandrum, University of Kerala, India, in 2004. He is currently a full time member of the faculty at College of Engineering Trivandrum. His research interests include energy efficiency, renewable energy, wind energy, solar - wind hybrid energy systems, additive manufacturing.

Minu Reghunath

Minu Reghunath is currently an Assistant Professor at College of Engineering Trivandrum and pursuing her Ph.D from the Department of Engineering Design, Indian Institute of Technology, Madras, India. She received her Master of Science in Cyber Security from Georgia Institute of Technology, Atlanta, USA in 2021 and M. Tech in Information Technology from PSG College of Technology, Anna University, Coimbatore, India in 2011. She completed her B. Tech in Information Technology from Government Engineering College, Trivandrum, University of Kerala in 2007. Her research interests include Machine Learning and Optimization, Cyber Security and Computational Geometry.

Arya Jayan

Arya Jayan received her Bachelor of Electronics degree in 2020 from CHMM College for Advanced Studies, Chavarcode, Kerala University, Kerala, India. She is currently pursuing Master of Computer Application from College of Engineering Trivandrum, APJ Abdul Kalam Technological University, Kerala, India. She is interested in research with a focus on Machine Learning.

Abhilash Suryan

Abhilash Suryan received his Ph.D. in 2012 from Andong National University, South Korea. He had received his B. Tech. and M. Tech. degrees in Mechanical Engineering from the College of Engineering, Trivandrum, University of Kerala, India, in 1995 and 1997, respectively. He is currently a full time member of the faculty at College of Engineering Trivandrum. His research interests include energy efficiency, renewable energy, aerospace engineering, propulsion engineering, and fluid dynamics.