Shintai, T., Miura, Y., & Ise, T. (2014). Oscillation damping of a distributed generator using a virtual synchronous generator. *IEEE Transactions on Power Delivery,* *29*, 668–676.

Google Scholar

E.M.Electricity, annual report of New and renewable energy Egyptian authority, Egypt, 2019, pp. 11, Available from: http://nrea.gov.eg/Content/reports/English%20AnnualReport%202019.pdf

Chen, J., Liu, M., Oloughlin, C., Milano, F., & Odonnell, T. (2018). Modelling, simulation and hardware-in-the-loop validation of virtual synchronous generator control in low inertia power system. In *20th Power systems computation conference, PSCC 3*.

Anderson, P. M., & Fouad, A. A. (2003). *Power system control and stability* (pp. 699–782). New York: Wiley.

Google Scholar

Bourles, H., & Margotin, T. (1998). Analysis and design of robust coordinated AVR/PSS. *IEEE Transaction on Power Systems,* *13*, 568–575.

Google Scholar

Kundur, T. (1994). *Power system stability and control*. McGraw-Hill.

Google Scholar

Bu, L., Xu, W., Wang, L., Howell, F., & Kundur, P. (2003). *A PSS tuning toolbox and its applications*. IEEE Power Engineering Society General Meeting.

Google Scholar

Talaq, J. (2012). Optimal power system stabilizers for multi machine systems. *International Journal of Electrical Power and Energy Systems,* *43*, 793–803.

Google Scholar

Ray, P. K., & Paital, S. R. (2018). A robust power system stabilizer for enhancement of stability in power system using adaptive fuzzy sliding mode control. *Applied Soft Computing,* *73*, 471–481.

Google Scholar

Chaubey, P., Lather, J. S., Yelisetti, S., Manda, S., & KumarYadav, N. (2019). Robust power system stabilizer based on static output feedback approach to enhance power system stability. *Energy Procedia,* *158*, 2960–2965.

Google Scholar

Matsukawa, Y., Watanabe, M., Takahashi, H., & Mitani, Y. (2018). Optimal design of power system stabilizer using remote signal considering the transport delay. *IFAC-PapersOnLine,* *51*(28), 91–96.

Google Scholar

Zea, A. A. (2013). *Power system stabilizers for the synchronous generator*. Sweden: Chalmers University of Technology.

Google Scholar

IEEE. (2005). *IEEE recommended practice for excitation system models for power system stability Studies*. IEEE Press.

Google Scholar

Arco, S., Suul, J. A., & Fosso, O. B. (2015). A virtual synchronous machine implementation for distributed control of power converters in smart grids. *Electric Power Systems Research,* *122*, 180–197.

Google Scholar

Acro, S., Suul, J. A., & Fosso, O. B. (2014). Small-signal modelling and parametric sensitivity of a virtual synchronous machine. In *2014 Power systems computation conference (PSCC)*, Wroclaw, Poland (pp. 18–22).

Acro, S., Suul, J. A., & Fosso, O. B. (2013). Control system tuning and stability analysis of virtual synchronous machines. In *Energy conversion congress and exposition (ECCE)*, Denver, CO, USA (pp. 15–19).

Cheng, D., Xu, Y., & Huang, A. Q. (2017). Integration of DC microgrids as virtual synchronous machines into the AC grid. *IEEE Transaction Industrial Electron,* *64*, 7455–7466.

Google Scholar

Nogami, S., Yokoyama, A., Amano, H., & Daibu, T. (2018). Virtual synchronous generator model based control of PV for power system stability improvement in a large-scale power system with a massive integration of PVs. *Journal of International Council on Electrical Engineering,* *8*, 112–118.

Google Scholar

Yn, Y. (1983). *Electric power system dynamics* (1st ed.). McGraw-Hill.

Google Scholar

Muqabel, A. B., & Abido, M. (2006). Review of conventional power system stabilizer design methods. In *GCC conference* (pp. 1–7). Manama: IEEE.

Nogueira, F. G., Junior, W. B., Costa, C. T., & Lana, J. J. (2018). LPV-based power system stabilizer: Identification, control and field tests. *Control Engineering Practice,* *72*, 53–67.

Google Scholar

Oliveira, R. V., Ramos, R. A., & Bretas, N. G. (2010). An algorithm for computerized automatic tuning of power system stabilizers. *Control Engineering Practice,* *18*(1), 45–54.

Google Scholar

Peres, W., Coelho, F. C. R., & Costa, J. N. N. (2020). A pole placement approach for multi-band power system stabilizer tuning. *International Transactions on Electrical Energy Systems,* *30*(10), 1–26.

Google Scholar

Gomes, S., Guimarães, C. H. C., & Martins, N. (2018). Damped nyquist plot for a pole placement design of power system stabilizers. *Electric Power Systems Research,* *158*, 158–169.

Google Scholar

Gomes, S., Guimarães, C. H. C., Martins, N., & Tarantoc, G. N. (2018). Damped nyquist plot for a pole placement design of power system stabilizers. *Electric Power Systems Research,* *158*, 158–169.

Google Scholar

Kasilingam, G., & Pasupuleti, J. (2014). Auto tuning of PID controller of a synchronous machine connected to a linear and non linear load. In *2014 IEEE international conference on power and energy (PECon)* (pp. 71–76).

Nambu, M., & Ohsawa, Y. (1996). Development of an advanced power system stabilizer using a strict linearization approach. *IEEE Transactions on Power Systems,* *11*(2), 813–818.

Google Scholar

Scavoni, F. E. (2001). Design of robust power system controllers using linear matrix inequalities. In *2001 IEEE Porto power Technol Conference* 10th–13th Sep, Porto, Portugal.

Hasni, M., Touhami, O., Ibtiouen, R., Fadel, M., & Caux, S. (2008). Synchronous machine parameter identification by various excitation signals. *Electrical Engineering,* *90*, 219–228.

MATH
Google Scholar

Rao, P. S., & Sen, I. (1999). Robust tuning of power system stabilizers using QFT. *IEEE Transactions on Control Systems Technology,* *7*(4), 478–486.

Google Scholar

Ramirez, J. M., & Castillo, I. (2004). PSS & FDS simultaneous tuning. *EPSR,* *68*, 33–40.

Google Scholar

Hiyama, T., Kojima, D., Ohtsu, K., & Furukawa, K. (2005). Eigenvalue-based wide area stability monitoring of power systems. *Control Engineering Practice,* *13*(12), 1515–1523.

Google Scholar

Jin-ling, Y., Ru-cheng, H., Shao-juan, Y. & Ying-jun, Z. (2010). Design of a nonlinear power system stabilizer. In *2010 International conference on computational aspects of social networks* (pp. 683–686).

Matsukawa, Y., Watanabe, M., Takahashi, H., & Mitani, Y. (2018). Optimal placement and tuning approach for design of power system stabilizers and wide area damping controllers considering transport delay. *IFAC-PapersOnLine,* *51*(32), 534–539.

Google Scholar

Fusco, G., & Russo, M. (2011). Nonlinear control design for excitation controller and power system stabilizer. *Control Engineering Practice,* *19*(3), 243–251.

Google Scholar

Dasu, B., Kumar, M. S., & Rao, R. S. (2019). Design of robust modified power system stabilizer for dynamic stability improvement using particle swarm optimization technique. *Ain Shams Engineering Journal,* *10*(4), 769–783.

Google Scholar

Supriyadi, A. N. C., Takano, H., Murata, J., & Goda, T. (2014). Adaptive robust PSS to enhance stabilization of interconnected power systems with high renewable energy penetration. *Renewable Energy,* *63*, 767–774.

Google Scholar

Abido, M. A. (2002). Optimal design of PSSs using particle swarm optimization. *IEEE Transactions on Energy Conversion,* *17*(3), 406–413.

Google Scholar

Abido, M. A., & Magid, Y. L. (2002). Eigenvalue assignments in multimachine power systems using tabu search algorithm. *Computer and Electrical Engineering,* *28*, 527–545.

MATH
Google Scholar

Abido, M. A., & Magid, Y. L. (2003). Coordinated design of a PSS and an SVC-based controller to enhance power system stability. *EPSR,* *25*, 695–704.

Google Scholar

Magid, Y. L., & Abido, M. A. (2003). Optimal multiobjective design of robust PSSs using genetic algorithms. *IEEE Transactions on Power Systems,* *18*(3), 1125–1132.

Google Scholar

Zhao, P., & Malik, O. P. (2010). Design of an adaptive PSS based on recurrent adaptive control theory. *IEEE Transactions on Energy Conversion,* *24*(4), 884–892.

Google Scholar

Chaturvedi, D. K., & Malik, O. P. (2005). Generalized neuron-based adaptive PSS for multimachine environment. *IEEE Transactions on Power Systems,* *20*(1), 358–366.

Google Scholar

Eichmann, A., Kohler, A., Malik, O. P., & Taborda, J. (2000). *A prototype self-tuning adaptive power system stabilizer for damping of active power swings* (pp. 122–126). IEEE Power Engineering Society Summer Meeting.

Google Scholar

Liu, W., Venayagamoorthy, G. K., & Wunsch, D. C. (2003). A heuristic dynamic programming based power system stabilizer for a turbogenerator in a single machine power system. In *38th IAS annual meeting on conference record of the industry applications conference*, Salt Lake City, UT, USA (pp. 270–276).

Robak, S., Bialek, J. W., & Machowski, J. (2001). Comparison of different control structures for Lyapunov-based power system stabilizer, PICA 2001. In *Innovative computing for power - electric energy meets the market. 22nd IEEE power engineering society. International conference on power industry computer applications*, Sydney, NSW, Australia (pp. 229–234).

Abido, M. A. (2009). Power system stability enhancement using FACTS controllers: A review. *The Arabian Journal for Science and Engineering,* *34*(2), 153–172.

Google Scholar

Kazemi, A., & Sohrforouzani, M. V. (2006). Power system damping using fuzzy controlled FACTS devices. *Electrical Power and Energy Systems,* *28*, 349–357.

Google Scholar

Bodhe, G. L., Porate, K., & Thakre, K. L. (2009). Voltage stability enhancement of low voltage radial distribution network using static var compensator: A case study. *WSEAS Transactions on Power Systems,* *4*, 32–41.

Google Scholar

Castoldi, M. F., Sanches, D. S., Mansour, M. R., Bretas, N. G., & Ramosb, R. A. (2014). A hybrid algorithm to tune power oscillation dampers for FACTS devices in power systems. *Control Engineering Practice,* *24*, 25–32.

Google Scholar

Arzeha, N., Mustafa, M., & Idris, R. M. (2018). Damping low frequency oscillations via FACTS-POD controllers tuned by bees algorithm, ELEKTRIKA-. *Journal of Electrical Engineering,* *17*, 6–14.

Google Scholar

Sreedivya, K. M., Jeyanthy, P. A., & Devaraj, D. (2021). Improved design of interval type-2 fuzzy based wide area power system stabilizer for inter-area oscillation damping. *Microprocessors and Microsystems,* *83*, 103957.

Google Scholar

Lu, C., Hsu, C., & Juang, C. (2013). Coordinated control of flexible AC transmission system devices using an evolutionary fuzzy lead-lag controller with advanced continuous ant colony optimization. *IEEE Transactions on Power Systems,* *28*, 385–392.

Google Scholar

Ibrahim, A., Marei, M., Mekhamer, S., & Mansour, M. (2011). An artificial neural network based protection approach using total least square estimation of signal parameters via the rotational invariance technique for flexible AC transmission system compensated transmission lines. *Electric Power Components and Systems,* *39*, 64–79.

Google Scholar

Huang, C., & Huang, Y. (2014). Hybrid optimisation method for optimal power flow using flexible AC transmission system devices. *IET Generation, Transmission and Distribution,* *8*, 2036–2045.

Google Scholar

Roy, P. K., Ghoshal, S. P., & Thakur, S. S. (2011). Optimal reactive power dispatch considering flexible AC transmission system devices using biogeography-based optimization. *Electric Power Components and Systems,* *39*, 733–750.

Google Scholar

Lipo, T. A. (2017). *Analysis of synchronous machines* (pp. 137–495). CRC Press.

Google Scholar

Force, W. (2012). WECC, generic solar photovoltaic system dynamic simulation model specification. Western Electricity Coordinating Council Modeling and Validation Work Group, Sandia Contract.

Askari, Q., Younas, I., & Saeed, M. (2020). Political optimizer: A novel socio-inspired meta-heuristic for global optimization. *Knowledge-Based Systems,* *195*, 205–240.

Google Scholar

Askari, Q., & Younas, I. (2021). Political optimizer based feedforward neural network for classification and function approximation. *Neural Processing Letters,* *1*, 80–111.

Google Scholar

Faramarzi, A., Heidarinejad, M., Stephens, B., & Mirjalili, S. (2020). Equilibrium optimizer: A novel optimization algorithm. *Knowledge-Based Systems,* *191*, 105190.

Google Scholar

__N.Shahraki__, S.__Taghian__, S.__Mirjalili__, An improved grey wolf optimizer for solving engineering problems, Expert Systems with Applications 166 (2021) 113917.

Sasahara, H., Ishizaki, T., Sadamoto, T., Masuta, T., Ueda, Y., Sugihara, H., Yamaguchid, N., & Imuraa, J. (2019). Damping performance improvement for PV-integrated power grids via retrofit control. *Control Engineering Practice,* *84*, 92–101.

Google Scholar

Kolodziejczyk, W., Zoltowska, I., & Cichosz, P. (2021). Real-time energy purchase optimization for a storage-integrated photovoltaic system by deep reinforcement learning. *Control Engineering Practice,* *106*, 104598.

Google Scholar

Paital, S. R., Ray, P. K., Mohanty, A., & Dash, S. (2018). Stability improvement in solar PV integrated power system using. *Optik,* *170*, 420–430.

Google Scholar

Ranaweera, I., & Midtgard, O. M. (2016). Optimization of operational cost for a grid-supporting PV system with battery storage. *Renewable Energy,* *88*, 262–272.

Google Scholar

Chen, X., Hu, J., Chen, K., & Peng, Z. (2016). Modeling of electromagnetic torque considering saturation and magnetic field harmonics in permanent magnet synchronous motor for HEV. *Simulation Modelling Practice and Theory,* *66*, 212–225.

Google Scholar

Babaei, M., Asgharei, R., & Ahmarinejad, A. (2016). Electromagnetic torque and speed estimators for permanent magnet synchronous motor drive systems. *Energy Procedia,* *100*, 291–296.

Google Scholar

Mondal, D., Chakrabarti, A., & Sengupta, A. (2014). *Power system small signal stability analysis and control, 1,2 vol* (3rd ed.). Academic Press.

Google Scholar

Dasu, B., Sivakumar, M., & Srinivasarao, R. (2019). Interconnected multi-machine power system stabilizer design using whale optimization algorithm. *Protection and Control of Modern Power Systems,* *4*(2), 1–11.

Google Scholar