Optimal and Robust Power System Stabilizers in a Multi Machine System
Source abstract
Abstract
One method for eliminating oscillations in power systems is using stabilizers. By applying an appropriate control signal in the excitation system of a generator, a power system stabilizer improves the dynamic stability of power systems. However, the issue that is of high importance is the correct design of these stabilizers. These stabilizers must be designed to have proper performance when operating conditions change. When designed incorrectly, not only they do not improve the stability margin, but also increase the oscillations. In this paper, the robust design of power system stabilizers on a four-machine power system has been performed. For this purpose, the differential evolution algorithm has been used. The studies have been repeated as three scenarios by producing different loading conditions for the generators. The performances of the conventional stabilizer and the optimized one have been compared. Simulation results indicate that the designed robust stabilizer outperforms other stabilizers in different conditions and has damped the inter-area and intra-area oscillation modes in the shortest time with minimum amplitude.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Power System Optimization and Stability · Energy Load and Power Forecasting · Optimal Power Flow Distribution
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (66)
Show source-provided references
1. An integrated approach for optimal placement and tuning of power system stabilizer in multi-machine systems10.1016/j.ijepes.2014.05.072 ↗
2. Power system oscillations and control: Cassifications and PSSs’ design methods: A review10.1016/j.rser.2017.05.103 ↗
3. Optimal design of power system stabilizer for power systems including doubly fed induction generator wind turbines10.1016/j.energy.2015.01.115 ↗
4. Power system stabilizer design based on optimal model reference adaptive system
5. Mode selective damping of power system electromechanical oscillations for large power systems using supplementary remote signals10.1524/auto.2011.0909 ↗
6. A multi objective vector evaluated improved honey bee mating optimization for optimal and robust design of power system stabilizers10.1016/j.ijepes.2014.05.010 ↗
7. Kundur · Power System Stability and Control · 1994
8. IEEE TF report. proposed terms and definitions for power system stability10.1109/TPAS.1982.317476 ↗
9. Definition and classification of power system stability: IEEE/CIGRE joint task force on stability terms and definitions10.1109/TPWRS.2004.825981 ↗
10. Power system stabilizers design for interconnected power systems10.1109/TPWRS.2009.2036778 ↗
11. Robust multi-machine power systems control via high order sliding modes10.1016/j.epsr.2011.03.014 ↗
12. Natke · Uncertainty: Models and Measures · 1996
13. Uncertainty in integrated assessment modelling - from positivism to pluralism10.1023/A:1015783803445 ↗
14. Principles of uncertainty: What are they? Why do we need them?10.1016/0165-0114(95)00032-G ↗
15. Dealing with uncertainty: A survey of theories and practices knowledge and data engineering10.1109/TKDE.2012.179 ↗
16. Dynamic fault tree analysis using monte carlo simulation in probabilistic safety assessment10.1016/j.ress.2008.09.007 ↗
17. Optimal location of FACTS devices in order to simultaneously improving transmission losses and stability margin using artificial bee colony algorithm10.1109/ACCESS.2021.3108687 ↗
18. Optimization of power system stabilizers using participation factor and genetic algorithm10.1016/j.ijepes.2013.10.026 ↗
19. Design and allocation of power system stabilizers using the particle swarm optimization technique for an inter connected power system10.1016/j.ijepes.2011.09.005 ↗
20. Hybrid BFOA–PSO approach for coordinated design of PSS and SSSC-based controller considering time delays10.1016/j.ijepes.2013.01.006 ↗
21. A hybrid particle swarm optimization and bacterial foraging for optimal power system stabilizer design10.1016/j.ijepes.2012.10.047 ↗
22. New coordinated design of SVC and PSS for multi-machine power system using BF-PSO algorithm10.1016/j.protcy.2013.12.163 ↗
23. Coordinated design of PSSs and SVC via bacterial foraging optimization algorithm in a multi-machine power system10.1016/j.ijepes.2012.02.016 ↗
24. Power system stability enhancement via bacteria foraging optimization algorithm10.1007/s13369-012-0423-y ↗
25. Coordinated tuning of PSS and TCSC to improve hopf bifurcation margin in multi machine power system by a modified bacteria foraging algorithm10.1016/j.ijepes.2014.10.022 ↗
26. Robust tuning of power system stabilizer for small signal stability enhancement using meta heuristic bat algorithm10.1016/j.ijepes.2014.03.050 ↗
27. Optimization of power system stabilizers using BAT search algorithm10.1016/j.ijepes.2014.04.007 ↗
28. Optimal design of damping controllers using a new hybrid artificial bee colony algorithm10.1016/j.ijepes.2013.03.012 ↗
29. A new coordination strategy of SSSC and PSS controllers in power system using SOA algorithm based on pareto method10.1016/j.ijepes.2014.12.020 ↗
30. Co-ordinated PSS tuning of large power systems by combining transfer function-eigen function analysis (TFEA), optimization, and eigenvalue sensitivity10.1109/TPWRS.2014.2314717 ↗
31. Time delay approach for PSS and SSSC based coordinated controller design using hybrid PSO–GSA algorithm10.1016/j.ijepes.2015.03.014 ↗
32. Small signal stability analysis of power systems with DFIG based wind power penetration10.1016/j.ijepes.2014.01.005 ↗
33. Voltage performance enhancement of DFIG-based wind farms integrated in large-scale power systems: Coordinated AVR and PSS10.1016/j.ijepes.2015.05.014 ↗
34. Robust wide-area TS fuzzy output feedback controller for enhancement of stability in multimachine power system10.1109/JSYST.2011.2165639 ↗
35. Observer-based nonlinear control of power system using sliding mode control strategy10.1016/j.epsr.2011.10.014 ↗
36. Transient stability enhancement of multimachine power systems using nonlinear observer-based excitation controller10.1016/j.ijepes.2014.01.009 ↗
37. Multiobjective evolution of the explainable fuzzy rough neural network with gene expression programming10.1109/TFUZZ.2022.3141761 ↗
38. Multi-branch deep residual learning for clustering and beamforming in user-centric network10.1109/LCOMM.2020.3005947 ↗
39. Learning from a complementary-label source domain: Theory and algorithms
40. Bridging the theoretical bound and deep algorithms for open set domain adaptation
41. Research on electric vehicle charging safety warning model based on back propagation neural network optimized by improved gray wolf algorithm10.1016/j.est.2022.104092 ↗
42. An adaptive control strategy for interfacing converter of hybrid microgrid based on improved virtual synchronous generator10.1049/rpg2.12293 ↗
43. A privacy-preserving aggregation scheme based on negative survey for vehicle fuel consumption data10.1016/j.ins.2021.05.009 ↗
44. Research on AI security enhanced encryption algorithm of autonomous IoT systems10.1016/j.ins.2021.06.016 ↗
45. An adaptive regeneration framework based on search space adjustment for differential evolution10.1007/s00521-021-05708-1 ↗
46. A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels10.1016/j.energy.2021.122302 ↗
47. Integration of hydrogen storage system and wind generation in power systems under demand response program: A novel P-robust stochastic programming10.1016/j.ijhydene.2021.10.027 ↗
48. Investigation of frequency-up conversion effect on the performance improvement of stack-based piezoelectric generators10.1016/j.renene.2021.03.064 ↗
49. Coupled thermo-hydro-mechanical mechanism in view of the soil particle rearrangement of granular thermodynamics10.1016/j.compgeo.2021.104272 ↗
50. Creating knowledge graph of electric power equipment faults based on BERT–BiLSTM–CRF model
51. Hybrid evolutionary-based sparse channel estimation for IRS-assisted MM wave MIMO systems10.1109/TWC.2021.3105405 ↗
52. Failure prediction, monitoring and diagnosis methods for slewing bearings of large-scale wind turbine: A review10.1016/j.measurement.2020.108855 ↗
53. A rough set-based bio-inspired fault diagnosis method for electrical substations10.1016/j.ijepes.2020.105961 ↗
54. A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies10.1016/j.engappai.2020.103680 ↗
55. Fatigue life analysis of aero-engine blades for abrasive belt grinding considering residual stress10.1016/j.engfailanal.2021.105846 ↗
56. A markov chain position prediction model based on multidimensional correction
57. H∞ optimal performance design of an unstable plant under bode integral constraint
58. Application of sum of squares method in nonlinear H∞ control for satellite attitude maneuvers
59. Research on image classification method based on improved multi-scale relational network10.7717/peerj-cs.613 ↗
60. Joint embedding VQA model based on dynamic word vector10.7717/peerj-cs.353 ↗
61. Knowledge base graph embedding module design for visual question answering model10.1016/j.patcog.2021.108153 ↗
62. Allocation of centrally switched fault current limiters enabled by 5G in transmission system10.1109/TPWRD.2020.3037193 ↗
63. A multi-state model for transmission system resilience enhancement against short-circuit faults caused by extreme weather events10.1109/TPWRD.2020.3043938 ↗
64. Algorithms and optimal choice for power plants based on m-polar fuzzy soft set decision making criterions10.26480/aem.01.2020.11.23 ↗
65. A robust 3-D medical watermarking based on wavelet transform for data protection10.32604/csse.2022.022305 ↗
66. Robust reversible audio watermarking scheme for telemedicine and privacy protection10.32604/cmc.2022.022304 ↗