Relevant bibliographies by topics / Power system small-signal stability

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Power system small-signal stability'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Power system small-signal stability"

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Shirvani, Mojtaba, Ahmad Memaripour, Meysam Eghtedari, and Hasan Fayazi. "Small signal stability analysis of power system following different outages." International Journal of Academic Research 6, no. 2 (March 30, 2014): 268–72. http://dx.doi.org/10.7813/2075-4124.2014/6-2/a.38.

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Khederzadeh, Mojtaba, and Mahdi Ehsan. "Power-system small-signal stability and maximum loadability." Canadian Journal of Electrical and Computer Engineering 21, no. 2 (April 1996): 81–85. http://dx.doi.org/10.1109/cjece.1996.7102130.

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Choo, Y. C., K. M. Muttaqi, and M. Negnevitsky. "Evaluation of small signal stability of a power system." Australian Journal of Electrical and Electronics Engineering 4, no. 3 (January 2008): 227–37. http://dx.doi.org/10.1080/1448837x.2008.11464189.

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Verma, Mayank Singh, Poonam Khatarkar, and Kumar Prabhakar. "Power System Small Signal Stability Analysis Using Facts Pod." International Journal of Computer Trends & Technology 67, no. 07 (July 25, 2019): 57–61. http://dx.doi.org/10.14445/22312803/ijctt-v67i7p109.

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Yousin Tang and A. P. S. Meliopoulos. "Power system small signal stability analysis with FACTS elements." IEEE Transactions on Power Delivery 12, no. 3 (July 1997): 1352–61. http://dx.doi.org/10.1109/61.637014.

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Jia, Hongjie, Xiaodan Yu, Yixin Yu, and Chengshan Wang. "Power system small signal stability region with time delay." International Journal of Electrical Power & Energy Systems 30, no. 1 (January 2008): 16–22. http://dx.doi.org/10.1016/j.ijepes.2007.06.020.

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Xu, Yan, Fushuan Wen, Hongwei Zhao, Minghui Chen, Zeng Yang, and Huiyu Shang. "Stochastic Small Signal Stability of a Power System with Uncertainties." Energies 11, no. 11 (November 1, 2018): 2980. http://dx.doi.org/10.3390/en11112980.

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The ever-increasing penetration of wind power generation and plug-in electric vehicles introduces stochastic continuous disturbances to the power system. This paper proposes an analytical approach to analyze the influence of stochastic continuous disturbances on power system small signal stability. The noise-to-state stability (NSS) and NSS Lyapunov function (NSS-LF) are adopted for stability analysis with respect to the magnitude of uncertainties in a power system. The power system is modeled as a set of stochastic differential equations (SDEs). The supremum of the norm of the covariance is employed to characterize the influence of magnitudes of uncertainties on the power system. Then the relationship between the magnitudes of stochastic variations and probabilistic stability is explicitly identified by NSS. The proposed method can assess the stochastic stability of the power system by checking some algebraic expressions. Hence, it has high computation efficiency compared with the well-established Monte Carlo based method. Besides, since the magnitudes of the stochastic variations are integrated into the definition of the stochastic stability, the proposed method provides theoretical explanations for the impacts of uncertainties.
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Dey, Prasenjit, Aniruddha Bhattacharya, and Priyanath Das. "Tuning of power system stabilizer for small signal stability improvement of interconnected power system." Applied Computing and Informatics 16, no. 1/2 (December 29, 2017): 3–28. http://dx.doi.org/10.1016/j.aci.2017.12.004.

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This paper reports a new technique for achieving optimized design for power system stabilizers. In any large scale interconnected systems, disturbances of small magnitudes are very common and low frequency oscillations pose a major problem. Hence small signal stability analysis is very important for analyzing system stability and performance. Power System Stabilizers (PSS) are used in these large interconnected systems for damping out low-frequency oscillations by providing auxiliary control signals to the generator excitation input. In this paper, collective decision optimization (CDO) algorithm, a meta-heuristic approach based on the decision making approach of human beings, has been applied for the optimal design of PSS. PSS parameters are tuned for the objective function, involving eigenvalues and damping ratios of the lightly damped electromechanical modes over a wide range of operating conditions. Also, optimal locations for PSS placement have been derived. Comparative study of the results obtained using CDO with those of grey wolf optimizer (GWO), differential Evolution (DE), Whale Optimization Algorithm (WOA) and crow search algorithm (CSA) methods, established the robustness of the algorithm in designing PSS under different operating conditions.
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Lim Zhu Aun, Shalom, Marayati Bte Marsadek, and Agileswari K. Ramasamy. "Small Signal Stability Analysis of Grid Connected Photovoltaic." Indonesian Journal of Electrical Engineering and Computer Science 6, no. 3 (June 1, 2017): 553. http://dx.doi.org/10.11591/ijeecs.v6.i3.pp553-562.

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This paper primarily focuses on the small signal stability analysis of a power system integrated with solar photovoltaics (PV). The test system used in this study is the IEEE 39-bus. The small signal stability of the test system are investigated in terms of eigenvalue analysis, damped frequency, damping ratio and participation factor. In this study, various conditions are analyzed which include the increase in solar PV penetration into the system and load variation. The results obtained indicate that there is no significant impact of solar PV penetration on the small signal stability of large scaled power system.
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Sabati, Asghar, Ramazan Bayindir, Sanjeevikumar Padmanaban, Eklas Hossain, and Mehmet Rida Tur. "Small Signal Stability with the Householder Method in Power Systems." Energies 12, no. 18 (September 4, 2019): 3412. http://dx.doi.org/10.3390/en12183412.

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Voltage collapse in power systems is still considered the greatest threat, especially for the transmission system. This is directly related to the quality of the power, which is characterized by the loss of a stable operating point and the deterioration of voltage levels in the electrical center of the region exposed to voltage collapse. Numerous solution methods have been investigated for this undesirable degradation. This paper focuses on the steady state/dynamic stability subcategory and techniques that can be used to analyze and control the dynamic stability of a power system, especially following a minor disturbance. In particular, the failure of one generator among the network with a large number of synchronous generators will affect other synchronous generators. This will become a major problem and it will be difficult to find or resolve the fault in the network due to there being too many variables, consequently affecting the stability of the entire system. Since the solution of large matrices can be completed more easily in this complex system using the Householder method, which is a small signal stability analysis method that is suggested in the thesis, the detection of error and troubleshooting can be performed in a shorter period of time. In this paper, examples of different rotor angle deviations of synchronous generators were made by simulating rotor angle stability deviations up to five degrees, allowing the system to operate stably, and concluding that the system remains constant.
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Dissertations / Theses on the topic "Power system small-signal stability"

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singhvi, vikas. "Small Signal Stability of an Unregulated Power System." MSSTATE, 2002. http://sun.library.msstate.edu/ETD-db/theses/available/etd-11062002-140310/.

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Rotor angle stability is the ability of the interconnected synchronous machines of a power system to remain in synchronism. This stability problem is concerned with the behavior of one or more synchronous machine after they have been perturbed. These perturbations can be small or large depending upon the type of disturbances considered. The work presented in this thesis is focused on the power system behavior when subjected to small disturbances. The ?small signal? disturbances are considered sufficiently small for the linearization of system equations to be permissible for the purpose of the analysis. The first step in the small signal stability studies is to obtain initial steady state conditions using load flow solutions. After establishing initial conditions, an unregulated mathematical model of the power system is formed. The mathematical model obtained is a set of nonlinear coupled first order differential equations. The method of small changes, called the perturbation method, is used to linearize these nonlinear differential equations. The equations are then written in a linear state space model form. The eigenvalues and the participation factors are obtained from the state matrix and the contribution of a particular machine in a particular mode or oscillations (or eigenvalue) can be examined for the small signal stability studies.
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McIlhagger, David. "Acceleration of power system small signal stability analysis." Thesis, Queen's University Belfast, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486529.

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Electric power networks comprise large complex interconnections of generation and loads. The generators, and their controllers, are non-linear dynamic systems which on interconnection form a very complex control problem. Traditionally the models used to capture the small signal Rtability of these systems were not highly detailed. This waR jURtified Rince the generation was provided by large centralized power Rtations, however with the current trend towards small scale and diRtributed generation, as provided by.wind farmR and diesel genRetR, the power system modelR require a greater level of detail. This means that the stability assessment of theRe models involves greater detail and requires greater computation time, thus rendering near future predictions obsolete. ThiR thesis studies the methods that are Ilsed to determine • power system small signal stability, in order to provide acceleration to this analysis. A method based on wavelet approximations to provide an approximate solution was developed and its effectiveneRs against the traditional QR algorithm waR investigated. The method was applied to a four generator RyRtem and the IEEE New England 39 bus Rystem. Alternative methods to form accelerating polynomials for eigenvalue methodR were developed and evaluated against the IEEE New England 39 bus system. A new algorithm, called the polygon polynomial Arnoldi method (PPAM) was developed and tested against the implicitly restarted Arnoldi method (IRAM), from the linear algebra literature. The effectiveness of both theRe methods was tested against the IEEE New England 39 bus system and the one area IEEE reliability test system along with that for the QR algorithm.
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Rudraraju, Seetharama raju. "SMALL SIGNAL AND TRANSIENT STABILITY ANALYSIS OF MVDC SHIPBOARD POWER SYSTEM." MSSTATE, 2009. http://sun.library.msstate.edu/ETD-db/theses/available/etd-11052009-170217/.

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Recent developments in high power rated Voltage Source Converters (VSCs) have resulted in their successful application in Multi-Terminal HVDC (MTDC) transmission systems and also have potential in the Medium Voltage DC (MVDC) distribution systems. This work presents the findings of stability studies carried out on a zonal MVDC architecture for the shipboard power distribution system. The stability study is confined to rotor angle stability of the power system, i.e. the transient and small signal stability analysis. The MTDC ring structure similar to MVDC shipboard power system was implemented in MATLAB/Simulink to look at the transient behavior of the MVDC system. Small signal stability analysis has been carried out with the help of Power System Toolbox (PST) for both MVAC as well as MVDC architectures. Later, Participation Analysis has been carried out to address the small signal instability in the case of MVAC architecture and methods for enhancement were also presented.
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Gu, Qun. "Flexible control of electrical power system to enhance small signal stability /." Search for this dissertation online, 2004. http://wwwlib.umi.com/cr/ksu/main.

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Fourie, Gert. "Power system stabilizer and controlled series capacitor small-signal stability performance analysis." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/53013.

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Thesis (MScEng)--University of Stellenbosch, 2002.
ENGLISH ABSTRACT: This thesis presents results of a study on the small-signal stability of a single-machine infinite-bus power system. Conditions of generator loading and network impedance are identified that require additional stability support. Two methods of stability enhancement are investigated, namely the power system stabilizer and the controlled series capacitor. Both stabilizers employ the conventional (classic) control structure, and parameters are evaluated for optimum performance using an integral-of-the-squared-error-based method. Results for damping capability versus generator loading and system impedance were generated. The ability of the power system stabilizer and controlled series capacitor to provide stability support is compared. This comparison is based on (a) the ability to provide more damping torque when needed, and (b) the amount of damping torque contributed by the stabilizer.
AFRIKAANSE OPSOMMING: Hierin word die resultate van 'n studie op die klein-sein stabiliteit van 'n enkel-masjien oneindige-bus kragstelsel weergegee. Kondisies van generator belasting en netwerk impedansie waar dempings-ondersteuning benodig word, word geïdentifiseer. Twee metodes van stabiliteits-verbetering word ondersoek, naamlik die kragstelstel stabiliseerder en die beheerde serie kapasitor. Beide stabiliseerders maak gebruik van die konvensionele (klassieke) beheerstruktuur, waarvan parameters geëvalueer word deur gebruik te maak van 'n integraal-van-die-vierkant-fout-gebaseerde metode. Resultate vir dempingsvermoë teenoor generator belasting en stelsel impedansie word verkry. Die vermoë van die kragstelsel stabiliseerder en beheerde serie kapasitor om stabiliteits-ondersteuning te verskaf, word vergelyk. Hierdie vergelyking is gebasseer op (a) die vermoë om meer dempingswrinkrag te voorsien wanneer benodig, en (b) die hoeveelheid dempingswrinkrag deur die stabiliseerder bygedra.
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Mudau, Dovhani Selby. "Comparison of three power system software packages for small-signal stability analysis." Master's thesis, University of Cape Town, 2009. http://hdl.handle.net/11427/8935.

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Includes bibliographical references (leaves 131-133).
Many power system simulation tools exist for small-signal stability analysis. This is due to the rapid development of computer systems, higher industrial growth and the need for reliable power system simulation tools for efficient planning and control of electric power systems. Three power system small-signal stability simulation tools have been selected for comparison and these are: PSAT 2.1.2, MatNetEig and PacDyn 8.1.1. These combine both open and closed source code industrial-grade power system analysis tools. The objective of this thesis is to compare three simulation tools on power system small-signal stability analysis. Input formats, data output flexibility, dynamic components and synchronous machine saturation modelling in all three simulation tools were amongst other features investigated for comparative studies.
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Kshatriya, Niraj. "Power System Controller Design by Optimal Eigenstructure Assignment." IEEE Transactions on Power System, 2010. http://hdl.handle.net/1993/4838.

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In this thesis the eigenstructure (eigenvalues and eigenvectors) assignment technique based algorithm has been developed for the design of controllers for power system applications. The application of the algorithm is demonstrated by designing power system stabilizers (PSSs) that are extensively used to address the small-signal rotor angle stability problems in power systems. In the eigenstructure assignment technique, the critical eigenvalues can be relocated as well as their associated eigenvectors can be modified. This method is superior and yield better dynamical performance compared to the widely used frequency domain design method, in which only the critical eigenvalues are relocated and no attempt is made to modify the eigenvectors. The reviewed published research has demonstrated successful application of the eigenstructure assignment technique in the design of controllers for small control systems. However, the application of this technique in the design of controllers for power systems has not been investigated rigorously. In contrast to a small system, a power system has a very large number state variables compared to the combined number of system inputs and outputs. Therefore, the eigenstructure assignment technique that has been successfully applied in the design of controllers for small systems could not be applied as is in the design of power system controllers. This thesis proposes a novel approach to the application of the eigenstructure assignment technique in the design of power system controllers. In this new approach, a multi-objective nonlinear optimization problem (MONLOP) is formulated by quantifying different design objectives as a function of free parametric vectors. Then the MONLOP is solved for the free parametric vectors using a nonlinear optimization technique. Finally, the solution of the controller parameters is obtained using the solved free parametric vectors. The superiority of the proposed method over the conventional frequency domain method is demonstrated by designing controllers for three different systems and validating the controllers through nonlinear transient simulations. One of the cases includes design of a PSS for the Manitoba Hydro system having about 29,000 states variables, which demonstrates the applicability of the proposed algorithm for a practical real-world system.
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Restrepo, Jaime Quintero. "A real-time wide-area control for mitigating small-signal instability in large electric power systems." Online access for everyone, 2005. http://www.dissertations.wsu.edu/Dissertations/Spring2005/j%5Fquintero%5F011905.pdf.

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Zhang, Pei. "Co-ordination and control of power system damping controllers to enhance small signal stability." Thesis, Imperial College London, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321949.

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Vance, Katelynn Atkins. "Evaluation of Stability Boundaries in Power Systems." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78322.

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Power systems are extremely non-linear systems which require substantial modeling and control efforts to run continuously. The movement of the power system in parameter and state space is often not well understood, thus making it difficult or impossible to determine whether the system is nearing instability. This dissertation demonstrates several ways in which the power system stability boundary can be calculated. The power system movements evaluated here address the effects of inter-area oscillations on the system which occur in the seconds to minutes time period. The first uses gain scheduling techniques through creation of a set of linear parameter varying (LPV) systems for many operating points of the non-linear system. In the case presented, load and line reactance are used as parameters. The scheduling variables are the power flows in tie lines of the system due to the useful information they provide about the power system state in addition to being available for measurement. A linear controller is developed for the LPV model using H₂/H∞ with pole placement objectives. When the control is applied to the non-linear system, the proposed algorithm predicts the response of the non-linear system to the control by determining if the current system state is located within the domain of attraction of the equilibrium. If the stability domain contains a convex combination of the two points, the control will aid the system in moving towards the equilibrium. The second contribution of this thesis is through the development and implementation of a pseudo non-linear evaluation of a power system as it moves through state space. A system linearization occurs first to compute a multi-objective state space controller. For each contingency definition, many variations of the power system example are created and assigned to the particular contingency class. The powerflow variations and contingency controls are combined to run sets of time series analysis in which the Lyapunov function is tracked over three time steps. This data is utilized for a classification analysis which identifies and classifies the data by the contingency type. The goal is that whenever a new event occurs on the system, real time data can be fed into the trained tree to provide a control for application to increase system damping.
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Books on the topic "Power system small-signal stability"

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Kong, Kit N. A. The influence of load dynamics on power system small-signal stability. Manchester: UMIST, 1998.

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Du, Wenjuan, Haifeng Wang, and Siqi Bu. Small-Signal Stability Analysis of Power Systems Integrated with Variable Speed Wind Generators. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94168-4.

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Mondal, Debasish, Abhijit Chakrabarti, and Aparajita Sengupta. Power System Small Signal Stability Analysis and Control. Elsevier Science & Technology, 2020.

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Power System Small Signal Stability Analysis and Control. Elsevier Science & Technology Books, 2014.

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Power System Small Signal Stability Analysis and Control. Elsevier Science & Technology Books, 2020.

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Power System Small Signal Stability Analysis and Control. Elsevier, 2020. http://dx.doi.org/10.1016/c2018-0-02439-1.

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Power System Small Signal Stability Analysis and Control. Elsevier, 2014. http://dx.doi.org/10.1016/c2013-0-18470-x.

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Small signal stability, control and dynamic performance of power systems. Adelaide, Australia: University of Adelaide, 2015.

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Gibbard, M. J. Small-signal stability, control and dynamic performance of power systems. University of Adelaide Press, 2015.

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Wang, Haifeng, Wenjuan Du, and Siqi Bu. Small-Signal Stability Analysis of Power Systems Integrated with Variable Speed Wind Generators. Springer, 2019.

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Book chapters on the topic "Power system small-signal stability"

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Vittal, Vijay. "Small Signal Stability in Electric Power Systems." In Encyclopedia of Systems and Control, 1279–82. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5058-9_260.

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Vittal, Vijay. "Small Signal Stability in Electric Power Systems." In Encyclopedia of Systems and Control, 1–5. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5102-9_260-1.

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Vittal, Vijay. "Small Signal Stability in Electric Power Systems." In Encyclopedia of Systems and Control, 2086–90. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_260.

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Alizadeh Bidgoli, Mohsen, Davood Ganjali, Weijia Yang, and Saman Atrian. "Small Signal Stability Improvement of Pumped Storage Hydropower Using Wide Area Signal Considering Wind Farm." In Power Systems, 249–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54275-7_9.

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Nazari, Masoud Honarvar. "Small-Signal Stability Analysis of Electric Power Systems on the Azores Archipelago." In Power Electronics and Power Systems, 445–72. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-0-387-09736-7_17.

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Dey, Prasenjit, Anulekha Saha, Sourav Mitra, Bishwajit Dey, Aniruddha Bhattacharya, and Boonruang Marungsri. "Improvement of Small-Signal Stability with the Incorporation of FACTS and PSS." In Control Applications in Modern Power System, 335–44. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8815-0_28.

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Murugan, A., S. Jayaprakash, and R. Raghavan. "Contingency Analysis Reliability Evaluation of Small-Signal Stability Analysis." In Advances in Power Systems and Energy Management, 229–39. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4394-9_24.

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Zhang, Xiao-Ping, Christian Rehtanz, and Bikash Pal. "Modeling of Power Systems for Small Signal Stability Analysis with FACTS." In Flexible AC Transmission Systems: Modelling and Control, 371–400. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28241-6_13.

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Marconato, Roberto, and Alberto Berizzi. "Small-Disturbance Angle Stability and Electromechanical Oscillation Damping." In Handbook of Electrical Power System Dynamics, 477–569. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118516072.ch9.

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Du, Wenjuan, Haifeng Wang, and Siqi Bu. "Small-Signal Stability of a Power System Integrated with an MTDC Network for the Wind Power Transmission." In Small-Signal Stability Analysis of Power Systems Integrated with Variable Speed Wind Generators, 243–301. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94168-4_7.

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Conference papers on the topic "Power system small-signal stability"

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Singhvi, Vikas, and S. Mark Halpin. "Small Signal Stability of an Unregulated Power System." In 2007 Thirty-Ninth Southeastern Symposium on System Theory. IEEE, 2007. http://dx.doi.org/10.1109/ssst.2007.352312.

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Bokharaie, Vahid, Rifat Sipahi, and Federico Milano. "Small-signal stability analysis of delayed power system stabilizers." In 2014 Power Systems Computation Conference (PSCC). IEEE, 2014. http://dx.doi.org/10.1109/pscc.2014.7038316.

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Firdaus, Ayesha, and Anwaruddin Anwar. "Effect of exciter gain on small signal stability of power system." In 2014 6th IEEE Power India International Conference (PIICON). IEEE, 2014. http://dx.doi.org/10.1109/poweri.2014.7117656.

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Zhao Yang Dong. "Genetic algorithms in power system small signal stability analysis." In APSCOM-97. International Conference on Advances in Power System Control, Operation and Management. IEE, 1997. http://dx.doi.org/10.1049/cp:19971857.

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Hu, Tao, Fang Li, and Yangyu Hu. "Small signal stability assessment of extra-large power system." In 2010 International Conference on Power System Technology - (POWERCON 2010). IEEE, 2010. http://dx.doi.org/10.1109/powercon.2010.5666539.

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Ben Salah, Rim, Meriam Djebali, Omar Kahouli, Chokri Bouchoucha, and Hsan Hadj Abdallah. "Small signal stability of the Tunisian interconnected power system." In 2014 15th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA). IEEE, 2014. http://dx.doi.org/10.1109/sta.2014.7086801.

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Jia, H., W. Yinghui, and Y. Xiaodan. "Power system small signal stability region with time delay." In 7th IET International Conference on Advances in Power System Control, Operation and Management (APSCOM 2006). IEE, 2006. http://dx.doi.org/10.1049/cp:20062023.

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Gholami, Amin, and Xu Andy Sun. "A Fast Certificate for Power System Small-Signal Stability." In 2020 59th IEEE Conference on Decision and Control (CDC). IEEE, 2020. http://dx.doi.org/10.1109/cdc42340.2020.9304077.

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Jiaying Shi and Chen Shen. "Impact of DFIG wind power on power system small signal stability." In 2013 IEEE PES Innovative Smart Grid Technologies Conference (ISGT 2013). IEEE, 2013. http://dx.doi.org/10.1109/isgt.2013.6497851.

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Joseph, Thomas, Barjeev Tyagi, and Vishal Kumar. "Small signal stability analysis and optimal control of multi-area power system." In 2016 IEEE 7th Power India International Conference (PIICON). IEEE, 2016. http://dx.doi.org/10.1109/poweri.2016.8077316.

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