Renewable Energy and Energy Storage Systems

Renewable power, often referred to as clean energy, comes from natural sources or processes that are constantly replenished. For example, sunlight and wind keep shining and blowing, even if their availability depends on time and weather. While renewable energy is often thought of as a new technology, harnessing nature’s power has long been used for heating, transportation, lighting, and more. Energy storage is going to be a quintessential part of the new power system architecture as it not only helps to balance out the variability in generation but could also enable consumption of a higher proportion of self-generated renewable power by consumers and reduce the need to feed excess electricity back into the grid.

Sub-Topics

  • Renewable Energy 

Renewable energy often referred to as clean energy, is the energy derived from natural resources or processes that are constantly replenished. Solar, wind, hydro etc. are few such sources that are constantly being replenished. Energy generation using renewable-based sources creates far lower carbon emissions compared to non-renewable fossil fuel-based energy generation techniques. We work mainly on solar PV and wind energy systems. Research topics include:

  • Maximum power extraction i.e. MPPT through proper control and power electronic converters.
  • Hybridization of energy sources and storage for optimal energy management etc.
  • Energy efficient scheduling and control of hybrid renewable energy systems.
  • Application of machine learning techniques to solve energy scheduling problems
  • Energy enhancement from the renewable energy sources like wind turbine generators, solar PV systems etc.. by continuous monitoring and fault diagnosis.
  • Energy Storage

Although renewable energy sources are essential for sustainable development, the primary issue with them is their dependence on the weather and inability to store and send power when required. This calls for energy storage systems to make the energy available when and where it is required.

Batteries are the most commonly used energy storage in transportation systems and portable devices. Fuel cells are another option having high energy density but low power density like batteries. On the other hand, supercapacitors/ultracapacitors/EDLCs have high power density and low energy density in comparison to both batteries and fuel cells.   We work on the broad areas of renewable energy systems including energy storage and the application of control techniques in addressing the challenges faced by this sector. Specifically, 

  • Energy storage (battery, supercapacitor) modelling
  • Battery health diagnostics
  • Energy management of battery and supercapacitors
  • Electric vehicle / e-mobility
  • Battery-Fuel cell hybrid systems
  • Vanadium redox flow batteries

A multidisciplinary approach for fabrication and characterization of EDLCs is being done in the department. Carbon and nitrogen based electrode material development and testing as SuperCapacitors has shown interesting results. Apart from structural and morphological characterizations, electrochemical impedance spectroscopy, charge/discharge, voltammetry/amperometry tests are investigated & analysed. The primary goal of these investigations is mostly to improve charge density of capacitors/supercapacitors and to enhance power density of batteries. The overall vision is development of environmentally friendly materials for efficient energy storage systems for a sustainable future.

  • Modelling and Optimisation of Solar Cells

Design and fabrication of any electrochemical system for optimal performance is a complex task as multiple variables are involved. There is a need to design the electrochemical system for the highest possible efficiency by designing the variables satisfying the constraints. Development of mathematical models satisfying physics involved in the solar cells helps in analysing the cells for different operating conditions and extract the best possible performance. We mostly work on new generation Solar cells – DSSC, Perovskite solar cells, etc.

  • Condition monitoring for Renewable Energy Systems 

The utility of renewable energy resources, such as wind turbines, solar panels, biofuel combustors etc. has grown rapidly throughout the globe in the past few decades. It is very essential to keep its operation in good working condition to uphold its efficiency and enhance its energy extraction. The conventional monitoring systems often fail to monitor its operation due to the lack of intelligence and hence can result low production and breakdown.
Recently, sensors and related measurement technologies enabled huge progress in the research topics of condition monitoring in both online and offline. The application of data-driven approaches using IIoT, machine learning and artificial intelligence has offered many innovative solutions to the condition monitoring issues surrounding the renewable energy system.

Associated Faculty Members

Significant Publications

  1. Kushwah K., Sahoo S., Joshuva A, “Health Monitoring of Wind Turbine Blades Through Vibration Signal Using Machine Learning Techniques”, Lecture Notes in Networks and Systems, vol 170, 2021, Springer, Singapore. 
  2. P.S. Pravin, Jaswin Zhi Ming Tan, Ken Shaun Yap, Zhe Wu, “Hyperparameter optimization strategies for machine learning-based stochastic energy efficient scheduling in cyber-physical production systems”, Digital Chemical Engineering, vol. 4, pp. 100047, 2022.
  3. P.S. Pravin, Zhiyao Luo, Lanyu Li, Xiaonan Wang, “Learning-based Scheduling of Industrial Hybrid Renewable Energy Systems”, Computers & Chemical Engineering, vol. 159, pp. 107665, 2022.
  4. Manu Suvarna, Apoorva Katragadda, Ziying Sun, Yun Bin Choh, Qianyu Chen, P.S. Pravin, Xiaonan Wang, “A machine learning framework to quantify and assess the impact of COVID-19 on the power sector: An Indian context”, Advances in Applied Energy, vol. 5, pp. 100078, 2021.
  5. S. Misra, P.S. Pravin, Gudi, R.D., Bhartiya, S., “Integration of supply and demand side management using renewable power sources: Application on an Air Separation Plant”, Industrial & Engineering Chemistry Research, vol. 60 (9), pp. 3670-3686, 2021.
  6. P.S. Pravin, S. Misra, Bhartiya, S., Gudi, R.D., “A Reactive Scheduling and Control framework for Integration of Renewable Energy Sources with a Reformer-based Fuel Cell system and an Energy Storage Device”, Journal of Process Control, vol. 87, pp. 147-165, 2020.
  7. P.S. Pravin, Bhartiya, S., Gudi, R.D., “Modeling and Predictive Control of an Integrated Reformer- Membrane- Fuel Cell- Battery Hybrid Dynamic System”, Industrial & Engineering Chemistry Research, vol. 58, 11392-11406, 2019. 
  8. P.S. Pravin, Gudi, R.D., Bhartiya, S., “Dynamic Modeling and Control of an Integrated Reformer-Membrane-Fuel Cell System”, Processes, vol. 6(9), pp. 169, 2019. 
  9. Chakraborty, Soumik, Ranjith G. Nair, and Lalu Seban. “Development and validation of an improved model for Dye-Sensitized Solar Cell and estimation of the optimum design parameters for maximum performance”. Optik, Elsevier, 2022. (Accepted)
  10. Sebina Yesmin, Inamul Hussain, Meghali Devi, Rajdeep Dasgupta, Siddhartha S.Dhar, “Exploration of Cu/g-C3N4 Nanocomposites as a Cost-Effective High-Performance Asymmetric Supercapacitor Electrode Material”, IEEE Transactions on Nanotechnology, Volume 21, pg. 474-480, 2022.
  11. Sebina Yesmin, Meghali Devi, Rajdeep Dasgupta, Siddhartha S.Dhar, “CoFe2O4 nanocubes over Cu/graphitic carbon nitride as electrode materials for solid-state asymmetric supercapacitors”, Chemical Engineering Journal, vol. 446, Part 1, pp. 136540, 2022.
  12. Sebina Yesmin, Meghali Devi, Inamul Hussain, Rajdeep Dasgupta, Siddhartha S.Dhar, “In-situ grafting of Au and Cu nanoparticles over graphitic carbon nitride sheets and unveiling its superior supercapacitive performance as a hybrid composite electrode material”, Journal of Energy Storage, vol. 44, Part A, pp. 103308, 2021.
  13. S. Bansal, P. Nambisan, P. Saha, and M. Khanra, “Effect of Supercapacitor Modelling and Unit Cell Capacitance Selection Towards Economic Sizing of Energy Storage System in Electric Vehicle”, Journal of Energy Storage, vol.51, 2022.
  14. P. Nambisan and M. Khanra, “Optimal Energy Management of Battery Supercapacitor aided Solar PV Powered Agricultural Feed Mill using Pontryagin’s Minimum Principle,” IEEE Transactions on Power Electronics, 2021.
  15. P. Nambisan, P. Saha, and M. Khanra, “Real-Time Optimal Fast Charging of Li-ion batteries with Varying Temperature and Charging Behaviour Constraints,” Journal of Energy Storage, vol. 41, 2021.
  16. P. Saha, V. Ramadesigan, M. Khanra, “An Experimental Study on the Effectiveness of Conventional State-of-Health Diagnosis Schemes for Second-use Supercapacitors”, Journal of Energy Storage, vol. 4, pp. 102968, 2021.
  17. S. Bansal, S. Dey, and M. Khanra, “Energy Storage Sizing in Plug-in Electric Vehicles: Driving Cycle Uncertainty Effect Analysis and Machine Learning Based Sizing,” Journal of Energy Storage, vol. 41, 2021.
  18. P. Saha, S. Dey, and M. Khanra, “Second-Life Applications of Supercapacitors: Effective Capacitance Prognosis and Aging,” Journal of Power Sources, vol. 496, 2021.
  19. S. Dey and M. Khanra, “Cybersecurity of Plug-in Electric Vehicles:Cyber Attack Detection During Charging,”IEEE Trans. on Industrial Electronics, 2020.
  20. P. Saha, S. Dey, and M. Khanra, “Accurate estimation of state-of-charge of supercapacitor under uncertain leakage and open circuit voltage map,”Journal of Power Sources, vol. 434, 2019.
  21. P.Saha, S. Dey, and M. Khanra, “Modeling and State-of-Charge Estimation of Supercapacitor Considering Leakage Effect,”IEEE Trans. on Industrial Electronics, 2019.