VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene





Integration VRE, ZIP dynamic models loads, Automatic Frequency Restoration Reserve (aFRR), Power System Stabilizers (PSS), Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO), PIAT grid


The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.


Download data is not yet available.

Author Biography

Ali Abderrazak Tadjeddine, École Nationale Polytechnique d'Oran

SCAMRE Laboratory

Department of Technology, Technological Institute, University Center Nour Bachir El Bayadh, Algeria


R. Yan, Q. Xing, and Y. Xu, “Multi agent safe graph reinforcement learning for PV inverter s based real-time de centralized volt/VAR control in zoned distribution networks,” IEEE Transactions on Smart Grid, pp. 1–1, 2023. doi:10.1109/tsg.2023.3277087

Y. Rao et al., “A frequency control strategy for multimicrogrids with V2G based on the improved robust model predictive control,” Energy, vol. 222, p. 119963, 2021. doi:10.1016/j.energy.2021.119963

P. Fan et al., “A Load Frequency coordinated control strategy for multimicrogrids with V2G based on improved Ma-DDPG,” International Journal of Electrical Power & Energy Systems, vol. 146, p. 108765, 2023. doi:10.1016/j.ijepes.2022.108765

A. M. Ewais et al., “Adaptive frequency control in smart microgrid using controlled loads supported by real-time implementation,” PLOS ONE, vol. 18, no. 4, 2023. doi:10.1371/journal.pone.0283561

A. Tadjeddine, A. Chaker and all, “Optimal Intelligent Energy Management to integrate a photovoltaic park into electricity grid using a real-time objective function—application to the naâma park,” ICREEC 2019, pp. 77–84, 2020. https://doi.org/10.1007/978-981-15-5444-5_10.

Harrouz, I. COLAK, and K. KAYISILI, “Control strategy of PMSG generator in small wind turbine system,” Algerian Journal of Renewable Energy and Sustainable Development, vol. 4, no. 01, pp. 69–83, 2022. doi:10.46657/ajresd.2022.4.1.7

A. Tadjeddine, R. I. Bendjillali and all, “Advanced dynamic stability system developed for nonlinear load,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 11, no. 4, p. 265, 2023. https://doi.org/10.11591/ijpeds.v11.i4.pp265-271.

M. Leinakse, G. Andreesen, P. Tani, and J. Kilter, “Estimation of exponential and zip load model of aggregated load with distributed generation,” 2021 IEEE 62nd International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), 2021. doi:10.1109/rtucon53541.2021.9711702

M. F. Dynge, P. Crespo del Granado, N. Hashemipour, and M. Korpås, “Impact of local electricity markets and peer-to-peer trading on low-voltage grid operations,” Applied Energy, vol. 301, p. 117404, 2021. doi:10.1016/j.apenergy.2021.117404

M. Nour, J. P. Chaves-Ávila, M. Troncia, A. Ali, and Á. Sánchez-Miralles, “Impacts of community energy trading on low voltage distribution networks,” IEEE Access, pp. 1–1, 2023. doi:10.1109/access.2023.3278090

E. J. Smith, D. A. Robinson, and A. P. Agalgaonkar, “A secondary strategy for unbalance consensus in an Islanded Voltage Source converter-based microgrid using cooperative gain control,” Electric Power Systems Research, vol. 210, p. 108097, 2022. doi:10.1016/j.epsr.2022.108097

P. Fan et al., “A frequency–pressure cooperative control strategy of multi-microgrid with an electric–gas system based on MADDPG,” Sustainability, vol. 14, no. 14, p. 8886, 2022. doi:10.3390/su14148886

Y. Wen et al., “An optimal scheduling strategy of a microgrid with V2G based on Deep Q-Learning,” Sustainability, vol. 14, no. 16, p. 10351, 2022. doi:10.3390/su141610351

H. Abubakr et al., “Adaptive LFC incorporating modified virtual rotor to regulate frequency and tie-line power flow in multi-area microgrids,” IEEE Access, vol. 10, pp. 33248–33268, 2022. doi:10.1109/access.2022.3161505

J. Young, W. Weaver, D. G. Wilson, and R. D. Robinett III, “The optimal control of type-4 wind turbines connected to an electric microgrid,” 20th International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants (WIW 2021), 2021. doi:10.1049/icp.2021.2625

T. M. Le et al., “Optimal Power Flow Solutions to power systems with wind energy using a highly effective meta-heuristic algorithm,” International Journal of Renewable Energy Development, vol. 12, no. 3, pp. 467–477, 2023. doi:10.14710/ijred.2023.51375

T. Binkowski, “Synchronization of the photovoltaic converter with on-board high frequency grid,” 2021 Selected Issues of Electrical Engineering and Electronics (WZEE), 2021. doi:10.1109/wzee54157.2021.9577012

Li et al., “Modeling Integrated Power and transportation systems: Impacts of power-to-gas on the deep decarbonization,” IEEE Transactions on Industry Applications, vol. 58, no. 2, pp. 2677–2693, 2022. doi:10.1109/tia.2021.3116916

F. Aboshady, O. Ceylan, A. F. Zobaa, A. Ozdemir, G. Taylor, and I. Pisica, “Sequentially coordinated and cooperative volt/VAR control of PV inverters in Distribution Networks,” Electronics, vol. 12, no. 8, p. 1765, 2023.

P. Li, J. Hou, Y. Yang, and X. Bai, “Small signal stability constrained optimal power flow model based on trajectory optimization,” Energy Reports, vol. 9, pp. 489–499, 2023.

A. Lasheen, H. F. Sindi, M. Nour, M. Shaaban, A. Osman, and H. H. Zeineldin, “Impact of secondary control design on the microgrid domain of stability considering reactive power sharing,” IEEE Access, pp. 1–9, 2023.

H. Hichem, A. A. Tadjeddine, A. Iliace, and M . S. Bendelhoum, “A new robust Sida-PBC approach to control a DFIG,” Bulletin of Electrical Engineering and Informatics, vol. 12, no. 3, pp. 1310–1317, 2023.

O. E. Turgut and M. S. Turgut, “Local search enhanced Aquila optimization algorithm ameliorated with an ensemble of wavelet mutation strategies for complex optimization problems,” Mathematics and Computers in Simulation, vol. 206, pp. 302–374, 2023. doi:10.1016/j.matcom.2022.11.020

A. Kumar, V. M. Mishra, and R. Ranjan, “Control strategy for design and performance evaluation of Hybrid Renewable Energy System using neural network controller,” Applications of AI and IOT in Renewable Energy, pp. 211–223, 2022. doi:10.1016/b978-0-323-91699-8.00012-7

X. Irudayaraj et al., “An adaptive Zhang Neural Network Controller for frequency control of Renewable Energy Integrated System,” 2022 IEEE 10th Power India International Conference (PIICON), 2022. doi:10.1109/piicon56320.2022.10045183

V. Sharifi, A. Abdollahi, and M. Rashidinejad, “Flexibility-based generation maintenance scheduling in presence of uncertain wind power plants forecasted by deep learning considering demand response programs portfolio,” International Journal of Electrical Power & Energy Systems, vol. 141, p. 108225, 2022. doi:10.1016/j.ijepes.2022.108225

Q. Asadi, A. Ashoornezhad, H. Falaghi, and M. Ramezani, “Optimal repair crew and mobile power source scheduling for load restoration in Distribution Networks,” 2023 International Conference on Protection and Automation of Power Systems (IPAPS), 2023. doi:10.1109/ipaps58344.2023.10123318

Ranko Goić, Damir Jakus, and Eugen Mudnić, “Calculation of annual active energy losses in a distribution network with a connected wind power plant,” Journal of Energy - Energija, vol. 56, no. 6, pp. 676–699, 2022. doi:10.37798/2007566372

A. Alvarez Canabal, A. G. Loukianov, J. M. Cañedo Castañeda, and V. A. Utkin, “Adaptive power system stabilizer with sliding mode for Electric Power Systems,” SSRN Electronic Journal, 2022. doi:10.2139/ssrn.4111002

Q. Wu, Y. He, F. Jiang, L. Shi, and Y. Li, “Optimization of Energy Storage Assisted peak regulation parameters based on PSS/e,” Energy Reports, vol. 9, pp. 504–512, 2023. doi:10.1016/j.egyr.2023.03.059

Review for “Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm,” 2020. doi:10.1002/2050-7038.12657/v2/review2

R. Kumari and A. Kumar, “Power system stabilizer design for Ideal AVR using local measurements,” International Journal of Electrical Power & Energy Systems, vol. 150, p. 109061, 2023. doi:10.1016/j.ijepes.2023.109061

V. Snášel, R. M. Rizk-Allah, D. Izci, and S. Ekinci, “Weighted mean of vectors optimization algorithm and its application in designing the power system stabilizer,” Applied Soft Computing, vol. 136, p. 110085, 2023. doi:10.1016/j.asoc.2023.110085

Y. Yang et al., “Parameter coordination optimization of power system stabilizer based on similarity index of Power System State-BP Neural Network,” Energy Reports, vol. 9, pp. 427–437, 2023. doi:10.1016/j.egyr.2023.04.158

K. Tokumitsu, H. Amano, K. Kawabe, and T. Nanahara, “Analysis and improvement of cross-regional cooperation for Automatic Frequency Restoration Reserves,” Electric Power Systems Research, vol. 188, p. 106574, 2020. doi:10.1016/j.epsr.2020.106574

P. Maucher, S. Remppis, D. Schlipf, and H. Lens, “Control Aspects of the interzonal exchange of Automatic Frequency Restoration Reserves,” IFAC-PapersOnLine, vol. 55, no. 9, pp. 30–35, 2022. doi:10.1016/j.ifacol.2022.07.006

Pavic, T. Capuder, and H. Pandzic, “Analysis of AFRR and MFRR balancing capacity & Energy demands and bid curves,” 2022 IEEE 7th International Energy Conference (ENERGYCON), 2022. doi:10.1109/energycon53164.2022.9830433

S. Kim, “A novel preventive frequency stability constrained OPF considering wind power fluctuation,” 2022 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia), 2022. doi:10.1109/isgtasia54193.2022.10003619

S. Neelamkavil Pappachan, “Development of optimal placement and sizing of facts devices in power system integrated with wind power using modified krill herd algorithm,” COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, 2023. doi:10.1108/compel-12-2021-0502




How to Cite

Tadjeddine AA, Bendelhoum MS, Bendjillali RI, Hamiani H, Djelaila S. VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene. EAI Endorsed Trans Energy Web [Internet]. 2023 Jul. 31 [cited 2023 Sep. 22];10. Available from: https://publications.eai.eu/index.php/ew/article/view/3378