Improvement of power quality in grid-connected hybrid system with power monitoring and control based on internet of things approach




renewable energy source, photovoltaic system, power quality, internet of things, hybrid grid connected system


Purpose. This article proposes a new control monitoring grid connected hybrid system. The proposed system, improvement of power quality is achieved with internet of things power monitoring approach in solar photovoltaic grid system network. The novelty of the proposed work consists in presenting solar power monitoring and power control based internet of things algorithm, to generate DC voltage and maintain the constant voltage for grid connected hybrid system. Methods. The proposed algorithm which provides sophisticated and cost-effective solution for measuring the fault and as maximum power point tracking assures controlled output and supports the extraction of complete power from the photovoltaic panel. The objective of the work is to monitor and control the grid statistics for reliable and efficient delivery of power to a hybrid power generation system. Internet of things is regarded as a network comprising of electronic embedded devices, physical objects, network connections, and sensors enabling the sensing, analysis, and exchange of data. The proposed control technique strategy is validated using MATLAB/Simulink software and real time implementation to analysis the working performances. Results. The results obtained show that the power quality issue, the proposed system to overcome through monitoring of fault solar panel and improving of power quality. The obtained output from the hybrid system is fed to the grid through a 3ϕ voltage source inverter is more reliable and maintained power quality. The power obtained from the entire hybrid setup is measured by the sensor present in the internet of things-based module. In addition to that, the photovoltaic voltage is improved by a boost converter and optimum reliability is obtained with the adoption of the perturb & observe approach. The challenges in the integration of internet of things – smart grid must be overcome for the network to function efficiently. Originality. Compensation of power quality issues, grid stability and harmonic reduction in distribution network by using photovoltaic based internet of things approach is utilized along with sensor controller. Practical value. The work concerns a network comprising of electronic embedded devices, physical objects, network connections, and sensors enabling the sensing, analysis, and exchange of data. In this paper, internet of things sensors are installed in various stages of the smart grid in a hybrid photovoltaic –wind system. It tracks and manages network statistics for safe and efficient power delivery. The study is validated by the simulation results based on MATLAB/Simulink software and real time implementation.

Author Biographies

P. Balakishan, Annamalai University

Research Scholar, Department of Electrical and Electronics Engineering

I. A. Chidambaram, Annamalai University

Professor, Department of Electrical and Electronics Engineering

M. Manikandan, Jyothishmathi Institute of Technology and Science



Qazi A., Hussain F., Rahim N.A., Hardaker G., Alghazzawi D., Shaban K., Haruna K. Towards Sustainable Energy: A Systematic Review of Renewable Energy Sources, Technologies, and Public Opinions. IEEE Access, 2019, vol. 7, pp. 63837-63851. doi:

Humada A.M., Darweesh S.Y., Mohammed K.G., Kamil M., Mohammed S.F., Kasim N.K., Tahseen T.A., Awad O.I., Mekhilef S. Modeling of PV system and parameter extraction based on experimental data: Review and investigation. Solar Energy, 2020, vol. 199, pp. 742-760. doi:

Fadhel S., Delpha C., Diallo D., Bahri I., Migan A., Trabelsi M., Mimouni M.F. PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system. Solar Energy, 2019, vol. 179, pp. 1-10. doi:

Kumar N., Hussain I., Singh B., Panigrahi B.K. MPPT in Dynamic Condition of Partially Shaded PV System by Using WODE Technique. IEEE Transactions on Sustainable Energy, 2017, vol. 8, no. 3, pp. 1204-1214. doi:

Bataineh K. Improved hybrid algorithms‐based MPPT algorithm for PV system operating under severe weather conditions. IET Power Electronics, 2019, vol. 12, no. 4, pp. 703-711. doi:

Mosaad M.I., abed el-Raouf M.O., Al-Ahmar M.A., Banakher F.A. Maximum Power Point Tracking of PV system Based Cuckoo Search Algorithm; review and comparison. Energy Procedia, 2019, vol. 162, pp. 117-126. doi:

Rahmann C., Vittal V., Ascui J., Haas, J. Mitigation Control Against Partial Shading Effects in Large-Scale PV Power Plants. IEEE Transactions on Sustainable Energy, 2016, vol. 7, no. 1, pp. 173-180. doi:

Batzelis E.I., Papathanassiou S.A., Pal B.C. PV System Control to Provide Active Power Reserves Under Partial Shading Conditions. IEEE Transactions on Power Electronics, 2018, vol. 33, no. 11, pp. 9163-9175. doi:

Babu V., Ahmed K.S., Shuaib Y.M., Manikandan M. Power Quality Enhancement Using Dynamic Voltage Restorer (DVR)-Based Predictive Space Vector Transformation (PSVT) With Proportional Resonant (PR)-Controller. IEEE Access, 2021, vol. 9, pp. 155380–155392. doi:

Babu V., Ahmed K.S., Shuaib Y.M., Mani M. A novel intrinsic space vector transformation based solar fed dynamic voltage restorer for power quality improvement in distribution system. Journal of Ambient Intelligence and Humanized Computing, 2021, vol. 7, no. 1, pp. 173-180. doi:

Ahmed J., Salam Z. An Accurate Method for MPPT to Detect the Partial Shading Occurrence in a PV System. IEEE Transactions on Industrial Informatics, 2017, vol. 13, no. 5, pp. 2151-2161. doi:

Abdulrazzaq A.A., Hussein Ali A. Efficiency Performances of Two MPPT Algorithms for PV System With Different Solar Panels Irradiancess. International Journal of Power Electronics and Drive Systems (IJPEDS), 2018, vol. 9, no. 4, pp. 1755-1764. doi:

Wang F., Zhu T., Zhuo F., Yi H. An Improved Submodule Differential Power Processing-Based PV System With Flexible Multi-MPPT Control. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2018, vol. 6, no. 1, pp. 94–102. doi:

Yilmaz U., Kircay A., Borekci S. PV system fuzzy logic MPPT method and PI control as a charge controller. Renewable and Sustainable Energy Reviews, 2018, vol. 81, pp. 994-1001. doi:

Pradhan A., Panda B. A Simplified Design and Modeling of Boost Converter for Photovoltaic System. International Journal of Electrical and Computer Engineering (IJECE), 2018, vol. 8, no. 1, pp. 141-149. doi:

Nzoundja Fapi C.B., Wira P., Kamta M., Badji A., Tchakounte H. Real-Time Experimental Assessment of Hill Climbing MPPT Algorithm Enhanced by Estimating a Duty Cycle for PV System. International Journal of Renewable Energy Research, 2019, vol. 9, no. 3, pp. 1180-1189. doi:

Gouda E.A., Kotb M.F., Elalfy D.A. Modelling and Performance Analysis for a PV System Based MPPT Using Advanced Techniques. European Journal of Electrical Engineering and Computer Science, 2019, vol. 3, no. 1, pp. 1-7. doi:

Ali M.N., Mahmoud K., Lehtonen M., Darwish M.M.F. An Efficient Fuzzy-Logic Based Variable-Step Incremental Conductance MPPT Method for Grid-Connected PV Systems. IEEE Access, 2021, vol. 9, pp. 26420-26430. doi:

Li S., Li J. Output Predictor-Based Active Disturbance Rejection Control for a Wind Energy Conversion System With PMSG. IEEE Access, 2017, vol. 5, pp. 5205-5214. doi:

Kushwaha A., Gopal M., Singh B. Q-Learning based Maximum Power Extraction for Wind Energy Conversion System With Variable Wind Speed. IEEE Transactions on Energy Conversion, 2020, vol. 35, no. 3, pp. 1160-1170. doi:

Afghoul H., Krim F., Babes B., Beddar A., Kihel A. Design and real time implementation of sliding mode supervised fractional controller for wind energy conversion system under sever working conditions. Energy Conversion and Management, 2018, vol. 167, pp. 91-101. doi:

Reddy D., Ramasamy S. Design of RBFN Controller Based Boost Type Vienna Rectifier for Grid-Tied Wind Energy Conversion System. IEEE Access, 2018, vol. 6, pp. 3167-3175. doi:

Sattar A., Al-Durra A., Caruana C., Muyeen S.M. Testing the Performance of Battery Energy Storage in a Wind Energy Conversion System. 2018 IEEE Industry Applications Society Annual Meeting (IAS), 2018, pp. 1-8. doi:

Cheddadi Y., Cheddadi H., Cheddadi F., Errahimi F., Es-sbai N. Design and implementation of an intelligent low-cost IoT solution for energy monitoring of photovoltaic stations. SN Applied Sciences, 2020, vol. 2, no. 7, pp. 1165. doi:

Li Y., Cheng X., Cao Y., Wang D., Yang L. Smart Choice for the Smart Grid: Narrowband Internet of Things (NB-IoT). IEEE Internet of Things Journal, 2018, vol. 5, no. 3, pp. 1505-1515. doi:

Pawar P., Vittal K.P. Design and development of advanced smart energy management system integrated with IoT framework in smart grid environment. Journal of Energy Storage, 2019, vol. 25, pp. 100846. doi:

Hussain M., Beg M.M. Fog Computing for Internet of Things (IoT)-Aided Smart Grid Architectures. Big Data and Cognitive Computing, 2019, vol. 3, no. 1, pp. 8. doi:

Bera B., Saha S., Das A.K., Vasilakos A.V. Designing Blockchain-Based Access Control Protocol in IoT-Enabled Smart-Grid System. IEEE Internet of Things Journal, 2021, vol. 8, no. 7, pp. 5744-5761. doi:




How to Cite

Balakishan, P., Chidambaram, I. A., & Manikandan, M. (2022). Improvement of power quality in grid-connected hybrid system with power monitoring and control based on internet of things approach. Electrical Engineering & Electromechanics, (4), 44–50.



Power Stations, Grids and Systems