Skip to content
1887
Volume 69, Issue 4
  • ISSN: 2056-5135
file format pdf download PDF

Abstract

The increase in population and need for energy in the world’s fastest developing economies like India make it critical to increase the supply of energy and augment its utilisation. According to most energy projections, the expected future global demand patterns of energy are not sustainable. Thus, India will soon run out of its non-renewable energy sources. As per the study analysis, India receives 657.4 MW of solar radiation which when converted to power can be utilised to attain the energy demand of India. Solar hotspots represent geographical areas that receive abundant solar energy and offer significant prospects for commercial energy generation. Our study reveals that approximately 58% of India’s geological zones qualify as sun-based hotspots. Furthermore, we propose an economically viable setup of solar plants based on the identified hotspots. To analyse these solar hotspots in India, we have employed a density-based three-dimensional (3D) clustering approach. In our research, we have substantially enhanced the efficiency of the 3D density-based spatial clustering of applications with noise (DBSCAN) spatial clustering method by incorporating K-dimensional (KD) trees and spatial indexing for 3D data. We conducted a comparative analysis between two techniques: 3D DBSCAN using the Euclidean distance as the distance metric and 3D DBSCAN spatial clustering with KD trees as the distance function, aiming to optimise nearest neighbour searches. Our analysis demonstrates that, particularly when evaluating solar hotspots, utilising 3D DBSCAN spatial clustering with KD trees yields more accurate results, especially when considering statistical parameters like the Silhouette score and Dunn index.

© 2025 Johnson Matthey
This is an Open Access article distributed in accordance with the Creative Commons Attribution (CC BY 4.0) license. You are free to: share: copy and redistribute the material in any medium or format; adapt: remix, transform, and build upon the material for any purpose, even commercially. Under the following terms: attribution: you must give appropriate credit, provide a link to the license, and indicate if changes were made. See: https://creativecommons.org/licenses/by/4.0/
Loading

Article metrics loading...

/content/journals/10.1595/205651325X17422272151557
2025-10-01
2025-09-07
Loading full text...

Full text loading...

/deliver/fulltext/jmtr/69/4/Rathi_13a_Imp.html?itemId=/content/journals/10.1595/205651325X17422272151557&mimeType=html&fmt=ahah

References

  1. K. Yenneti, Curr. Sci., 2014, 106, (5), 665 LINK https://www.currentscience.ac.in/Volumes/106/05/0665.pdf
    [Google Scholar]
  2. S. P. Long, E. A. Ainsworth, A. Rogers, D. R. Ort, Annu. Rev. Plant Biol., 2004, 55, 591 LINK https://doi.org/10.1146/annurev.arplant.55.031903.141610
    [Google Scholar]
  3. M. Bhambu, ‘Innovations that Can Change Energy Scenario in India’, 22nd March, 2015 LINK https://doi.org/10.2139/ssrn.2583370
  4. A. Mani, Reson. J. Sci. Educ., 2008, 13, (11), 1082 LINK https://www.ias.ac.in/article/fulltext/reso/013/11/1082-1086
    [Google Scholar]
  5. A. Kumar, K. Kumar, N. Kaushik, S. Sharma, S. Mishra, Renew. Sustain. Energy Rev., 2010, 14, (8), 2434 LINK https://doi.org/10.1016/j.rser.2010.04.003
    [Google Scholar]
  6. J. Sawin, E. Martinot, ‘Renewables 2010: Global Status Report’, REN21, Paris, France, 2010
    [Google Scholar]
  7. D. Palit, A. Chaurey, Energy Sustain. Dev., 2011, 15, (3), 266 LINK https://doi.org/10.1016/j.esd.2011.07.004
    [Google Scholar]
  8. S. Pandey, V. S. Singh, N. P. Gangwar, M. M. Vijayvergia, C. Prakash, D. N. Pandey, Renew. Sustain. Energy Rev., 2012, 16, (6), 3593 LINK https://doi.org/10.1016/j.rser.2012.03.012
    [Google Scholar]
  9. F. C. Robert, S. Gopalan, ‘Environmental Friendly and Cost Effective Approach to Provide Highly Reliable Electric Supply to Rural Business and Industries’, International Conference on Technological Advancements in Power and Energy (TAP Energy), Kollam, India, 21st–23rd December, 2017, IEEE, Piscataway, USA, pp. 1–6 LINK https://doi.org/10.1109/tapenergy.2017.8397344
    [Google Scholar]
  10. M. F. Ansari, R. K. Kharb, S. Luthra, S. L. Shimmi, S. Chatterji, Renew. Sustain. Energy Rev., 2013, 27, 163 LINK https://doi.org/10.1016/j.rser.2013.07.002
    [Google Scholar]
  11. K. Kapoor, K. K. Pandey, A. K. Jain, A. Nandan, Renew. Sustain. Energy Rev., 2014, 40, 475 LINK https://doi.org/10.1016/j.rser.2014.07.118
    [Google Scholar]
  12. T. Muneer, M. Asif, S. Munawwar, Renew. Sustain. Energy Rev., 2005, 9, (5), 444 LINK https://doi.org/10.1016/j.rser.2004.03.004
    [Google Scholar]
  13. N. S. Lewis, Science, 2007, 315, (5813), 798 LINK https://doi.org/10.1126/science.1137014
    [Google Scholar]
  14. G. R. Timilsina, L. Kurdgelashvili, P. A. Narbel, Renew. Sustain. Energy Rev., 2012, 16, (1), 449 LINK https://doi.org/10.1016/j.rser.2011.08.009
    [Google Scholar]
  15. L. Vignesh, R. Ramkumar, S. Kaliappan, ‘Embedded Based Vegetable Cleaning Process Using Solar PV Cell’, International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS), Coimbatore, India, 17th–18th March, 2017, IEEE, Piscataway, USA, pp. 1–3 LINK https://doi.org/10.1109/iciiecs.2017.8275985
    [Google Scholar]
  16. S. R. Park, A. K. Pandey, V. V. Tyagi, S. K. Tyagi, Renew. Sustain. Energy Rev., 2014, 30, 105 LINK https://doi.org/10.1016/j.rser.2013.09.011
    [Google Scholar]
  17. S. C. Bhattacharya, C. Jana, Energy, 2009, 34, (8), 981 LINK https://doi.org/10.1016/j.energy.2008.10.017
    [Google Scholar]
  18. A. Rabl, C. E. Nielsen, Sol. Energy, 1975, 17, (1), 1 LINK https://doi.org/10.1016/0038-092x(75)90011-0
    [Google Scholar]
  19. K. Ravindra, M. N. Rao, V. S. N. K. Chaitanya, ‘Renewable Energy Source Allocation of Air-Conditioner Using Fuzzy Logic’, International Conference on Intelligent Computing and Control (I2C2), Coimbatore, India, 23rd–24th June, 2017, IEEE, Piscataway, USA, pp. 1–5 LINK https://doi.org/10.1109/i2c2.2017.8321813
    [Google Scholar]
  20. M. Alsharif, Energies, 2017, 10, (4), 429 LINK https://doi.org/10.3390/en10040429
    [Google Scholar]
  21. A. Singh, P. Marathey, I. Mukhopadhyay, ‘Energy Positive Solar LED Streetlight System’, International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), Chennai, India, 1st–2nd August, 2017, IEEE, Piscataway, USA, pp. 765–768 LINK https://doi.org/10.1109/icecds.2017.8389541
    [Google Scholar]
  22. T. V. Arjunan, H. Ş. Aybar, N. Nedunchezhian, Renew. Sustain. Energy Rev., 2009, 13, (9), 2408 LINK https://doi.org/10.1016/j.rser.2009.03.006
    [Google Scholar]
  23. R. H. E. Hassanien, M. Li, W. Dong Lin, Renew. Sustain. Energy Rev., 2016, 54, 989 LINK https://doi.org/10.1016/j.rser.2015.10.095
    [Google Scholar]
  24. M. Santamouris, C. A. Balaras, E. Dascalaki, M. Vallindras, Sol. Energy, 1994, 53, (5), 411 LINK https://doi.org/10.1016/0038-092x(94)90056-6
    [Google Scholar]
  25. H. P. Garg, Sol. Energy, 1975, 17, (3), 167 LINK https://doi.org/10.1016/0038-092x(75)90055-9
    [Google Scholar]
  26. S. Zunft, M. Hänel, M. Krüger, V. Dreißigacker, Energy Procedia, 2014, 49, 1088 LINK https://doi.org/10.1016/j.egypro.2014.03.118
    [Google Scholar]
  27. R. K. Khanna, R. S. Rathore, C. Sharma, Desalination, 2008, 220, (1–3), 645 LINK https://doi.org/10.1016/j.desal.2007.01.060
    [Google Scholar]
  28. L. K. Wiginton, H. T. Nguyen, J. M. Pearce, Comput. Environ. Urban Syst., 2010, 34, (4), 345 LINK https://doi.org/10.1016/j.compenvurbsys.2010.01.001
    [Google Scholar]
  29. R. Singh, R. Banerjee, Sol. Energy, 2015, 115, 589 LINK https://doi.org/10.1016/j.solener.2015.03.016
    [Google Scholar]
  30. J. Mathur, S. Mathur, Anupma, Energy Build., 2006, 38, (10), 1156 LINK https://doi.org/10.1016/j.enbuild.2006.01.006
    [Google Scholar]
  31. N. K. Bansal, Renew. Energy, 1999, 16, (1–4), 618 LINK https://doi.org/10.1016/s0960-1481(98)00237-7
    [Google Scholar]
  32. R. Bhanja, K. Roychowdhury, Appl. Geogr., 2023, 154, 102893 LINK https://doi.org/10.1016/j.apgeog.2023.102893
    [Google Scholar]
  33. L. Mouton, D. Trigaux, K. Allacker, M. Röck, Energy Build., 2023, 282, 112678 LINK https://doi.org/10.1016/j.enbuild.2022.112678
    [Google Scholar]
  34. M. Dhimish, G. Badran, npj Mater. Degrad., 2023, 7, 14 LINK https://doi.org/10.1038/s41529-023-00331-y
    [Google Scholar]
  35. U. Pruthviraj, Y. Kashyap, E. Baxevanaki, P. Kosmopoulos, Remote Sens., 2023, 15, (7), 1914 LINK https://doi.org/10.3390/rs15071914
    [Google Scholar]
  36. Q. Yin, H. Liu, T. Zhou, Sustainability, 2023, 15, (15), 11502 LINK https://doi.org/10.3390/su151511502
    [Google Scholar]
  37. A. Fan, Y. Li, H. Liu, L. Yang, Z. Tian, Y. Li, N. Vladimir, J. Clean. Prod., 2023, 389, 135899 LINK https://doi.org/10.1016/j.jclepro.2023.135899
    [Google Scholar]
  38. T. Rahman, A. A. Mansur, M. S. H. Lipu, M. S. Rahman, R. H. Ashique, M. A. Houran, R. M. Elavarasan, E. Hossain, Energies, 2023, 16, (9), 3706 LINK https://doi.org/10.3390/en16093706
    [Google Scholar]
  39. A. Maalouf, T. Okoroafor, Z. Jehl, V. Babu, S. Resalati, Renew. Sustain. Energy Rev., 2023, 186, 113652 LINK https://doi.org/10.1016/j.rser.2023.113652
    [Google Scholar]
  40. Q. Zhang, J. Wang, G. Liu, J. Energy Chem., 2023, 86, 146 LINK https://doi.org/10.1016/j.jechem.2023.07.018
    [Google Scholar]
  41. M. Daszykowski, B. Walczak, D. L. Massart, Anal. Bioanal. Chem., 2004, 380, (3), 370 LINK https://doi.org/10.1007/s00216-004-2582-5
    [Google Scholar]
  42. H. Chen, M. Liang, W. Liu, W. Wang, P. X. Liu, Pattern Recognit., 2022, 124, 108431 LINK https://doi.org/10.1016/j.patcog.2021.108431
    [Google Scholar]
/content/journals/10.1595/205651325X17422272151557
Loading
Intelligent Retrieval Paradigm for Solar Sustainability
Johnson Matthey Technology Review 69, 569 (2025); https://doi.org/10.1595/205651325X17422272151557
/content/journals/10.1595/205651325X17422272151557
/content/journals/10.1595/205651325X17422272151557
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): data analysis; density-based clustering; machine learning; solar energy; solar hotspots

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test