Authors

C. Deepa Venkat

Cyber Security Department of Cyber Security, SRM Institute of Science and Technology, Trichy, Tamilnadu, India

D. Karpagam

Cyber Security Department of Cyber Security, SRM Institute of Science and Technology, Trichy, Tamilnadu, India

Abstract

Now a days, energy saving is one of the most important issue for development of smart grid. The utility companies have higher electric charge during peak periods, so smart grid emphasizes off-peak energy consumption. The Intelligent Load Management system (ILMS) shall play a very important role in realizing residential demand response in smart grid environment. Therefore, the ILMS system with Demand Response (DR) is proposed, in which different loads are used and corresponding priority is adjusted based on priority of user. The controller board is used, which makes a decision to switch ON/OFF action of the selected end use appliances based on utility signal as well as home owners load priority and preference setting. It also demonstrates that how each appliance will perform when it will be controlled by Intelligent Load Management System ILMS. The proposed system is also responsible for collecting electrical consumption data from all loads and provides an interface for homeowner to retrieve appliances status. It provides user to know the status of appliances though LCD display.

Keywords

Smart Grid Load Demand Management Intelligent Energy Management Demand Response Smart Energy Systems Power Load Optimization

Citation of this Article

C. Deepa Venkat, & D. Karpagam. (2026). Intelligent Load Demand Management in a Smart Grid Environment. International Current Journal of Engineering and Science (ICJES), 5(3), 1-4. Article DOI: https://doi.org/10.47001/ICJES/2026.503001

Licence Copyright (c) 2026 International Current Journal of Engineering and Science. This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International Licence.

References

  1. Fang Xing, Misra Satyajayant, Xue Guoliang, and Yang Dejun, “Smart Grid – The New and Improved Power Grid: A Survey,” IEEE Communications Surveys & Tutorials, vol. 14, no. 4, pp. 944–980, 2012.
  2. Amin Massoud and Wollenberg Bruce, “Toward a Smart Grid: Power Delivery for the 21st Century,” IEEE Power and Energy Magazine, vol. 3, no. 5, pp. 34–41, 2005.
  3. Palensky Peter and Dietrich Dietmar, “Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads,” IEEE Transactions on Industrial Informatics, vol. 7, no. 3, pp. 381–388, 2011.
  4. Gungor Vehbi C., Sahin Dilan, Kocak Taskin, Ergüt S., Buccella Cosimo, Cecati Carlo, and Hancke Gerhard, “Smart Grid Technologies: Communication Technologies and Standards,” IEEE Transactions on Industrial Informatics, vol. 7, no. 4, pp. 529–539, 2011.
  5. Vishwa Chetanbhai Lakhnakiya. (2025). Cognitive CloudOps: Integrating Generative AI for Predictive Infrastructure Management and Self-Optimizing DevOps Pipelines. International Current Journal of Engineering and Science (ICJES), 4(9), 30-38. Article DOI: https://doi.org/10.47001/ICJES/2025.409006
  6. Ali Khaled Alshurmani, Taha Mahmoud Radman, & Mohammed Fadhl Abdullah. (2026). IoT-Based Overcurrent Protection in Substations: A Case Study of New Enma Substation, Aden. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(1), 103-112. Article DOI https://doi.org/10.47001/IRJIET/2026.101012
  7. Mohsenian-Rad Amir-Hamed, Wong Vincent, Jatskevich Juri, Schober Robert, and Leon-Garcia Alberto, “Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid,” IEEE Transactions on Smart Grid, vol. 1, no. 3, pp. 320–331, 2010.
  8. Gellings Clark W., “The Concept of Demand-Side Management for Electric Utilities,” Proceedings of the IEEE, vol. 73, no. 10, pp. 1468–1470, 1985.
  9. Strbac Goran, “Demand Side Management: Benefits and Challenges,” Energy Policy, vol. 36, no. 12, pp. 4419–4426, 2008.
  10. Conejo Antonio J., Morales Juan M., and Baringo Luis, “Real-Time Demand Response Model,” IEEE Transactions on Smart Grid, vol. 1, no. 3, pp. 236–242, 2010.
  11. Kailas, V. Cecchi, and A. Mukherjee, Kailas, Aravind, Valentina Cecchi, and Arindam Mukherjee. “A survey of communications and networking technologies for energy management in buildings and home automation.” Journal of Computer Networks and Communications 2012 (2012).
  12. Ullah, M. N., et al. “A Survey of Different Residential Energy Consumption Controlling Techniques for Autonomous DSM in Future Smart Grid Communications.” arXiv preprint arXiv:1306.1134 (2013).
  13. M. A. Piette, D.Watson, N.Motegi, S. Kiliccote, and E. Linkugel, “Automated demand response strategies and commissioning commercial building controls,” in Proc. 14th Natl. Conf. Building Commissioning, San Francisco, CA, Apr. 2006.
  14. D. Han and J. Lim, “Design and implementation of smart home energy management systems based on ZigBee,” IEEE Trans. Consum. Electron., vol. 56, no. 3, pp. 1417–1425, 2010.
  15. Khaled Hassan Balhaf, Manal Abdul Aziz Al-Nahari, Alwiyah Ahmed Balhaf, Manal Omar Bawazir, Adnan Swailem Ba'adil, & Mohammed Fadhl Abdullah. (2026). A Hybrid Framework for Medical X-ray Image Enhancement and Segmentation Using K-Means, Fuzzy C-Means, and Fuzzy Connectivity. International Research Journal of Innovations in Engineering and Technology - IRJIET, 10(2), 1-8. Article DOI https://doi.org/10.47001/IRJIET/2026.102001
  16. Y. S. Son, T. Pulkkinen, K. Y. Moon, and C. Kim, “Home energy management system based on power line communication,” IEEE Trans. Consum. Electron., vol. 56, pp. 1380–1386, 2010.
  17. J. Li, J. Y. Chung, J. Xiao, J.W. Hong, and R. Boutaba, “On the design and implementation of a home energy management system,” in Proc. 6th Int. Symp.Wireless Pervasive Comput. (ISWPC), Feb. 23–25, 2011, pp. 1–6.