Real time operation of microgrid with variation of distribution generation source to IEEE 13 bus system

Sunil Kumar, Ikbal Ali, Anwar Shahzad Siddiqui

Abstract


As the world energy sector shifts to renewable energy sources (RES), microgrids (MGs) are becoming more important for providing reliable and efficient power. MGs can effectively integrate distributed renewable generation in the grid connected and islanded modes and ensure system reliability. This paper presents a new type of Master-Slave (MS) allocation algorithm for distributed generation (DG) planning in microgrids. Unlike the conventional methods in which all DG units operate at unity power factor (UPF), the MS is implemented with one DG as a master (operating at non-unity power factor) and two DGs as slaves (operating at UPF). This setup optimizes the allocation of DG and minimizes power losses under variable loading conditions. The proposed MS-based model is integrated with the Particle Swarm Optimization (PSO)-Fast Decoupled Load Flow (FDLF) algorithm in order to find optimal placement of master and slave DGs. Simulation on IEEE-13 bus test system reveals that the proposed scheme decreases real power losses up to 77% compared to the base case without DG and 45% compared to PSO-NR optimization. In addition, the minimum bus voltage is increased from 0.90 p.u. (without DG) to 0.973 p.u. (with PSO-FDLF), thus satisfying the voltage stability constraints in all load scenarios. Validation in the RTDS/RSCAD platform shows that the optimized MS configuration is able to guarantee voltage deviation within ± 3% of nominal values with significant reduction of active power losses as well as reactive power losses. These results show that the proposed MS-based optimization framework offers a robust and scalable solution for the improvement of microgrid performance, which is of direct interest for utility operators operating in renewable embedded environments.

 

Received: 14 August 2025

Accepted: 23 October 2025

Published: 06 November 2025


Keywords


Distributed Generation; Microgrid; Renewable Energy Source; Real Time Digital Simulator; Variable Loads

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References


A. Muntaser, H. Ragb, and I. Elwrfalli, “DC Microgrid Based on Battery, Photovoltaic, and Fuel Cells; Design and Control,” Dec. 28, 2022. doi: 10.20944/preprints202212.0527.v1.

K. Nagaraju, S. Sivanagaraju, T. Ramana, and V. Ganesh, “Enhancement of Voltage Stability in Distribution Systems by Optimal Placement of Distribution Generator,” Distributed Generation & Alternative Energy Journal, vol. 27, no. 2, pp. 25–41, Apr. 2012, doi: 10.1080/21563306.2012.10505410.

L. F. Grisales, A. Grajales, O. D. Montoya, R. A. Hincapie, and M. Granada, “Optimal location and sizing of Distributed Generators using a hybrid methodology and considering different technologies,” in 2015 IEEE 6th Latin American Symposium on Circuits & Systems (LASCAS), IEEE, Feb. 2015, pp. 1–4. doi: 10.1109/LASCAS.2015.7250486.

S. M. Abu, M. A. Hannan, M. Mansor, P. J. Ker, and C. Yaw Long, “Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future,” in 2023 IEEE International Conference on Energy Technologies for Future Grids (ETFG), IEEE, Dec. 2023, pp. 1–7. doi: 10.1109/ETFG55873.2023.10407475.

S. Kumar, S. Sharma, I. Ali, and A. S. Siddiqui, “Real-Time Performance Assessment of Electric Vehicle Charging Stations with RTDS,” in 2025 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), IEEE, Jan. 2025, pp. 1–6. doi: 10.1109/SCEECS64059.2025.10940406.

Y. Wang, H. Ji, R. Luo, B. Liu, and Y. Wu, “Energy Optimization Strategy for Wind–Solar–Storage Systems with a Storage Battery Configuration,” Mathematics, vol. 13, no. 11, p. 1755, May 2025, doi: 10.3390/math13111755.

J. J. Kim and J. H. Park, “A Novel Structure of a Power System Stabilizer for Microgrids,” Energies (Basel), vol. 14, no. 4, p. 905, Feb. 2021, doi: 10.3390/en14040905.

X. Lu, J. Wang, and L. Guo, “Using microgrids to enhance energy security and resilience,” The Electricity Journal, vol. 29, no. 10, pp. 8–15, Dec. 2016, doi: 10.1016/j.tej.2016.11.013.

A. Firdaus and M. Molinas, “Design and Expansion Planning of Parallel Inverter Based AC Microgrids - An Approach for Improved Stability Margins,” Sep. 02, 2020. doi: 10.36227/techrxiv.12894926.v1.

M. Mahdavi, A. Awaafo, K. Schmitt, M. Chamana, F. Jurado, and S. Bayne, “An Effective Formulation for Minimizing Distribution Network Costs Through Distributed Generation Allocation in Systems With Variable Loads,” IEEE Trans Ind Appl, vol. 60, no. 4, pp. 5671–5680, Jul. 2024, doi: 10.1109/TIA.2024.3382255.

I. P. Nikolakakos, H. H. Zeineldin, M. S. El-Moursi, and N. D. Hatziargyriou, “Stability Evaluation of Interconnected Multi-Inverter Microgrids Through Critical Clusters,” IEEE Transactions on Power Systems, vol. 31, no. 4, pp. 3060–3072, Jul. 2016, doi: 10.1109/TPWRS.2015.2476826.

X. Tang, W. Deng, and Z. Qi, “Investigation of the Dynamic Stability of Microgrid,” IEEE Transactions on Power Systems, vol. 29, no. 2, pp. 698–706, Mar. 2014, doi: 10.1109/TPWRS.2013.2285585.

J. He, Y. W. Li, R. Wang, and C. Zhang, “Analysis and Mitigation of Resonance Propagation in Grid-Connected and Islanding Microgrids,” IEEE Transactions on Energy Conversion, vol. 30, no. 1, pp. 70–81, Mar. 2015, doi: 10.1109/TEC.2014.2332497.

A. Micallef, M. Apap, C. Spiteri-Staines, and J. M. Guerrero, “Mitigation of Harmonics in Grid-Connected and Islanded Microgrids Via Virtual Admittances and Impedances,” IEEE Trans Smart Grid, pp. 1–11, 2015, doi: 10.1109/TSG.2015.2497409.

A. Khodaei, S. Bahramirad, and M. Shahidehpour, “Microgrid Planning Under Uncertainty,” IEEE Transactions on Power Systems, vol. 30, no. 5, pp. 2417–2425, Sep. 2015, doi: 10.1109/TPWRS.2014.2361094.

S. Ganguly and D. Samajpati, “Distributed Generation Allocation on Radial Distribution Networks Under Uncertainties of Load and Generation Using Genetic Algorithm,” IEEE Trans Sustain Energy, vol. 6, no. 3, pp. 688–697, Jul. 2015, doi: 10.1109/TSTE.2015.2406915.

X. Zong and Y. Yuan, “Two-stage robust optimization of regional integrated energy systems considering uncertainties of distributed energy stations,” Front Energy Res, vol. 11, Mar. 2023, doi: 10.3389/fenrg.2023.1135056.

E. I. El-sayed, M. M. Al-Gazzar, M. S. Seif, and A. M. A. Soliman, “Energy management of renewable energy sources incorporating with energy storage device,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 13, no. 2, p. 883, Jun. 2022, doi: 10.11591/ijpeds.v13.i2.pp883-899.

A. S. Chaitra and H. R. Sudarshana Reddy, “Improving Reliability in Distribution Systems through Optimal Allocation of Distributed Generators, Network Reconfiguration and Capacitor Placement,” SN Comput Sci, vol. 5, no. 5, p. 456, Apr. 2024, doi: 10.1007/s42979-024-02753-0.

S. Ahmad and A. ul Asar, “Reliability Enhancement of Electric Distribution Network Using Optimal Placement of Distributed Generation,” Sustainability, vol. 13, no. 20, p. 11407, Oct. 2021, doi: 10.3390/su132011407.

D. Yu, J. Hao, J. Wang, J. Zhu, Y. Gao, and M. Shaker, “Optimal planning of Microgrids using portfolio optimization with considering uncertainty,” Sustainable Energy Technologies and Assessments, vol. 58, p. 103323, Aug. 2023, doi: 10.1016/j.seta.2023.103323.

P. Singh, N. K. Singh, and A. K. Singh, “Intelligent hybrid method to predict generated power of solar PV system,” Renewable Energy and Sustainable Development, vol. 11, no. 1, p. 141, May 2025, doi: 10.21622/resd.2025.11.1.1264.

R. T. Moyo, M. Dewa, H. F. M. Romero, V. A. Gómez, J. I. M. Aragonés, and L. Hernández-Callejo, “An adaptive neuro-fuzzy inference scheme for defect detection and classification of solar PV cells,” Renewable Energy and Sustainable Development, vol. 10, no. 2, p. 218, Sep. 2024, doi: 10.21622/resd.2024.10.2.929.

R. T. Moyo and M. Dewa, “The role of computational intelligence techniques in the advancements of solar photovoltaic systems for sustainable development: a review,” Renewable Energy and Sustainable Development, vol. 8, no. 2, p. 52, Dec. 2022, doi: 10.21622/resd.2022.08.2.052.

S. A. Arefifar and Y. A.-R. I. Mohamed, “DG Mix, Reactive Sources and Energy Storage Units for Optimizing Microgrid Reliability and Supply Security,” IEEE Trans Smart Grid, vol. 5, no. 4, pp. 1835–1844, Jul. 2014, doi: 10.1109/TSG.2014.2307919.

M. Abbasi, M. Hedayatpour, and A. G. Garganeev, “Microgrid Voltage and Frequency Control Using Droop Control Based on Master/Slave Method,” in 2020 21st International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM), IEEE, Jun. 2020, pp. 367–373. doi: 10.1109/EDM49804.2020.9153493.

A. M. Pasha, H. H. Zeineldin, E. F. El‐Saadany, and S. S. Alkaabi, “Optimal allocation of distributed generation for planning master–slave controlled microgrids,” IET Generation, Transmission & Distribution, vol. 13, no. 16, pp. 3704–3712, Aug. 2019, doi: 10.1049/iet-gtd.2018.5872.

S. Oviedo-Carranza, J. S. Artal-Sevil, and J. A. Domínguez-Navarro, “Optimal Operation of a Distributed Generation Microgrid based on the Multi-Objective Genetic Algorithms,” Renewable Energy and Power Quality Journal, vol. 20, pp. 789–794, Sep. 2022, doi: 10.24084/repqj20.436.

S. M. R. H. Shawon, X. Liang, and M. Janbakhsh, “Optimal Placement of Distributed Generation Units for Microgrid Planning in Distribution Networks,” IEEE Trans Ind Appl, vol. 59, no. 3, pp. 2785–2795, May 2023, doi: 10.1109/TIA.2023.3236363.

S. He and J. Liu, “Optimal Allocation Stochastic Model of Distributed Generation Considering Demand Response,” Energies (Basel), vol. 17, no. 4, p. 795, Feb. 2024, doi: 10.3390/en17040795.

P. Kant, P. Singhal, S. Kumar, and S. Gupta, “DC microgrid designed for the integration of wind and solar energy sources,” 2023, p. 020077. doi: 10.1063/5.0122979.

Y. Khalid Hamad, A. Nasser Hussain, Y. N. Lafta, A. Al-Naji, and J. Chahl, “Multi-Objective Optimization of Renewable Distributed Generation Placement and Sizing for Technical and Economic Benefits Improvement in Distribution System,” IEEE Access, vol. 12, pp. 164226–164247, 2024, doi: 10.1109/ACCESS.2024.3492119.

S. Kumar, R. Agarwal, and H. Subhadra, “Adaptive bayesian sparse polynomial chaos expansion for voltage balance of an isolated microgrid at peak load,” Renewable Energy and Sustainable Development, vol. 11, no. 1, p. 161, Jun. 2025, doi: 10.21622/resd.2025.11.1.1281.

S. Kumar, I. Ali, and A. S. Siddiqui, “Energy management in a grid-connected microgrid using hybrid Golden Jackal optimization and gradient descent optimization and the concept of loadability,” e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 9, p. 100763, Sep. 2024, doi: 10.1016/j.prime.2024.100763.

M. Miller, J. L. Paternina, S. F. Contreras, C. A. Cortes, and J. M. A. Myrzik, “Optimal allocation of renewable energy systems in a weak distribution network,” Electric Power Systems Research, vol. 235, p. 110649, Oct. 2024, doi: 10.1016/j.epsr.2024.110649.

F. Agha Kassab, R. Rodriguez, B. Celik, F. Locment, and M. Sechilariu, “A Comprehensive Review of Sizing and Energy Management Strategies for Optimal Planning of Microgrids with PV and Other Renewable Integration,” Applied Sciences, vol. 14, no. 22, p. 10479, Nov. 2024, doi: 10.3390/app142210479.

M. Rahimian, L. D. Iulo, and J. M. P. Duarte, “A Review of Predictive Software for the Design of Community Microgrids,” Journal of Engineering, vol. 2018, pp. 1–13, 2018, doi: 10.1155/2018/5350981.

N. Ghanbari, H. Mokhtari, and S. Bhattacharya, “Optimizing Operation Indices Considering Different Types of Distributed Generation in Microgrid Applications,” Energies (Basel), vol. 11, no. 4, p. 894, Apr. 2018, doi: 10.3390/en11040894.

O. A. Afolabi, W. H. Ali, P. Cofie, J. Fuller, P. Obiomon, and E. S. Kolawole, “Analysis of the Load Flow Problem in Power System Planning Studies,” Energy Power Eng, vol. 07, no. 10, pp. 509–523, 2015, doi: 10.4236/epe.2015.710048.

L. Kumar, M. Pandey, and M. K. Ahirwal, “Parallel Global Best-Worst Particle Swarm Optimization Algorithm for solving optimization problems,” Appl Soft Comput, vol. 142, p. 110329, Jul. 2023, doi: 10.1016/j.asoc.2023.110329.

C. Shah, R. W. Wies, T. M. Hansen, R. Tonkoski, M. Shirazi, and P. Cicilio, “High-Fidelity Model of Stand-Alone Diesel Electric Generator With Hybrid Turbine-Governor Configuration for Microgrid Studies,” IEEE Access, vol. 10, pp. 110537–110547, 2022, doi: 10.1109/ACCESS.2022.3211300.

A. M. Haval and M. Afzal, “Power System Stability Improvement Through PV Integration and Unified Power Flow Control,” E3S Web of Conferences, vol. 564, p. 05018, Sep. 2024, doi: 10.1051/e3sconf/202456405018.

X. Chen, H. Dong, and Y. Zhang, “A New Power System Frequency Response Model with Different Types of Generator Units,” in 2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES), IEEE, Sep. 2022, pp. 121–127. doi: 10.1109/AEES56284.2022.10079681.

S. Kumar, I. Ali, and A. S. Siddiqui, “Performance Analysis of Different Solar Models Based on the Solar cell Parameters,” Indian Journal of Pure & Applied Physics, 2021, doi: 10.56042/ijpap.v59i3.67765.

G. N. Gusev, O. V. Zhdaneev, M. E. Gainullin, A. Y. Argastsev, and D. N. Lapkin, “Solar PV system with maximum power tracking,” Int J Hydrogen Energy, vol. 87, pp. 258–267, Oct. 2024, doi: 10.1016/j.ijhydene.2024.08.441.

S. Kumar, I. Ali, and A. S. Siddiqui, “Real Time Performance Assessment of Wind Turbine Model Under Ferro Resonance Conditions,” in 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN), IEEE, Dec. 2024, pp. 755–760. doi: 10.1109/CICN63059.2024.10847454.




DOI: https://dx.doi.org/10.21622/resd.2025.11.2.1572

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Copyright (c) 2025 Sunil Kumar, Ikbal Ali, Anwar Shahzad Siddiqui

Renewable Energy and Sustainable Development

E-ISSN: 2356-8569

P-ISSN: 2356-8518

 

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