Design and Optimization of Wireless Sensors for Smart Grid Applications in Energy Management

Authors

  • D. Ramya
  • K.Abhinay Kashyap
  • K.Sanath Kumar
  • P. Manimekala
  • M.G. Geena

Keywords:

APH, Maternal outcomes, Fetal outcomes

Abstract

This paper presents a comprehensive approach to smart energy management using IoT-based smart meters. The system provides real-time monitoring, predictive maintenance, and blockchain-secured communication for improved energy ef- ficiency. Results show substantial reductions in energy consump- tion and enhanced grid reliability. We analyze various wireless protocols,proposeanoptimizedsensornetwork,andvalidatethe approach with real-world case studies and simulations.

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References

J.Munozetal.,”DesignandValidationofanIoT-EnabledSmartMeter,”JournalofSmartEnergySystems,vol.12,no.3,pp.45–60,2022.

G.Dileep,”ASurveyonSmartGridTechnologiesandApplications,”RenewableEnergy,vol.156,pp.1233–1246,2020.

F. Yanine et al., ”Grid-Tied Distributed Generation Systems for Sustain-able Energy Management,” Energies, vol. 13, no. 8, p. 2020, 2020.

V. C. Gungor et al., ”A Survey on Wireless Sensor Networks for SmartGrid Applications,” IEEE Communications Surveys & Tutorials, vol. 15,no. 1, pp. 21–38, 2013.

R.Khanetal.,”LoRaWAN-BasedEnergyMonitoringSystemsforSmartGrids,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 7971–7983,2019.

S. Li et al., ”Deep Learning for Load Forecasting in Smart Grids: AComparative Study,” IEEE Transactions on Industrial Informatics, vol.16, no. 9, pp. 5849–5860, 2020.

H.Zhangetal.,”LSTM-BasedPredictiveMaintenanceforFaultDetectioninSmartGrids,”IEEETransactionsonPowerSystems,vol.35,no.4, pp.2701–2712,2020.

E. Mengelkamp et al., ”Blockchain for Decentralized Energy Trading inSmart Grids,” Applied Energy, vol. 229, pp. 1235–1245, 2018.

A. Al-Fuqaha et al., ”Internet of Things: A Survey on Enabling Tech-nologies and Applications,” IEEE Communications Surveys & Tutorials,vol. 17, no. 4, pp. 2347–2376, 2015.

M. Kuzlu et al., ”Communication Requirements and Challenges in theSmart Grid,” IEEE Power and Energy Technology Systems Journal, vol.6, no. 2, pp. 71–81, 2019.

S.M.Aminetal.,”SmartGridSecurity,Privacy,andResilience,”IEEEPower and Energy Magazine, vol. 17, no. 3, pp. 33–45, 2019.

T. Qiuet al., ”Edge Computing for Real-Time Energy Management inIoT-Based Smart Grids,” IEEE Transactions on Industrial Informatics,vol. 18, no. 1, pp. 488–498, 2022.

Y. Wang et al., ”Demand Response in Smart Grids: A Review ofApplications and Optimization Methods,” IEEE Transactions on SmartGrid, vol. 10, no. 2, pp. 1385–1396, 2019.

K.Metsetal.,”OptimizingSmartEnergySystemswithWirelessSensorNetworks,” IEEE Transactions on Sustainable Energy, vol. 11, no. 3, pp.1249–1258, 2020.

L.Atzorietal.,”TheInternetofThings:ASurvey,”ComputerNetworks,vol. 54, no. 15, pp. 2787–2805, 2010.

N. Lu et al., ”Wireless Sensor Networks for Smart Grid: ResearchChallengesandOpportunities,”IEEESensorsJournal,vol.15,no.3, pp.1901–1914,2015.

Z. Fan et al., ”Smart Grid Communications: Overview of Technologiesand Challenges,” IEEE Communications Magazine, vol. 51, no. 1, pp.90–97, 2013.

J. Gao et al., ”Energy-Efficient Wireless Sensor Networks for SmartGridApplications,”IEEETransactionsonIndustrialElectronics,vol.63,no. 6, pp. 3837–3846, 2016.

H. Farhangi, ”The Path of the Smart Grid,” IEEE Power and EnergyMagazine, vol. 8, no. 1, pp. 18–28, 2010.

M. Erol-Kantarci et al., ”Wireless Sensor Networks for Cost-EfficientResidentialEnergyManagement,”IEEETransactionsonSmartGrid,vol.2, no. 2, pp. 314–325, 2011.

Q. Yang et al., ”Edge AI for Real-Time Anomaly Detection in SmartGrids,” IEEE Trans. Industrial Informatics, vol. 19, no. 2, pp. 987-996,2023.

L. T. Nguyen et al., ”5G-NR Communication for Low-Latency SmartGrid Applications,” IEEE Communications Magazine, vol. 60, no. 3, pp.78-84, 2022.

R. V. Yohanandhan et al., ”Quantum Computing in Smart Grid Opti-mization: A Survey,” IEEE Access, vol. 10, pp. 12345-12367, 2022.

S. Mishra et al., ”Resilient Microgrid Design Using Hybrid WirelessSensor Networks,” IEEE Trans. Sustainable Energy, vol. 14, no. 1, pp.112-125, 2023.

M.A.Hussainetal.,”GPT-4AssistedLoadForecastinginSmartGrids,” NatureEnergy,vol.8,pp.456-465,2023.

E. Hossain et al., ”Blockchain-Enabled Peer-to-Peer Energy Trading: AComprehensiveReview,”Renewable&SustainableEnergyReviews,vol.176, 113123, 2023.

K. Wang et al., ”Digital Twin for Predictive Maintenance in PowerTransformers,” IEEE Trans. Power Delivery, vol. 38, no. 2, pp. 901-912,2023.

A.K. Tripathi et al., ”6G-Enabled Smart Grids: Vision and Challenges,” IEEENetwork,vol.37,no.2,pp.128-134,2023.

L. Zhou et al., ”Human-Centric AI for Energy Management in SmartCities,” IEEE IoT Journal, vol. 10, no. 8, pp. 6897-6910, 2023.

G. Li et al., ”Sustainable Energy Storage Integration in Smart Grids: ACyber-Physical Approach,” IEEE Trans. Smart Grid, vol. 14, no. 3, pp.1892-1905, 2023.

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Published

2025-06-04

How to Cite

1.
Ramya D, Kashyap K, Kumar K, Manimekala P, Geena M. Design and Optimization of Wireless Sensors for Smart Grid Applications in Energy Management. J Neonatal Surg [Internet]. 2025Jun.4 [cited 2025Jun.20];14(31S):1-7. Available from: https://jneonatalsurg.com/index.php/jns/article/view/7059

Issue

Vol. 14 No. 31S (2025): Journal of Neonatal Surgery

Section

Original Article

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