Готові списки джерел за темами / Power system dynamic

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Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Power system dynamic"

1

Madzharov, Nikolay D., Raycho T. Ilarionov, and Anton T. Tonchev. "System for Dynamic Inductive Power Transfer." Indian Journal of Applied Research 4, no. 7 (October 1, 2011): 173–76. http://dx.doi.org/10.15373/2249555x/july2014/52.

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2

KATAGIRI, Yukinori, Takuya YOSHIDA, and Tatsurou YASHIKI. "E208 AUTOMATIC CODE GENERATION SYSTEM FOR POWER PLANT DYNAMIC SIMULATORS(Power System-2)." Proceedings of the International Conference on Power Engineering (ICOPE) 2009.2 (2009): _2–401_—_2–406_. http://dx.doi.org/10.1299/jsmeicope.2009.2._2-401_.

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3

C, Shilaja. "Identifying and Detecting Dynamic Island in DG Connected Power System." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (July 25, 2020): 744–49. http://dx.doi.org/10.5373/jardcs/v12sp7/20202164.

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4

Neuman, P., K. Máslo, B. Šulc, and A. Jarolímek. "Power System and Power Plant Dynamic Simulation." IFAC Proceedings Volumes 32, no. 2 (July 1999): 7294–99. http://dx.doi.org/10.1016/s1474-6670(17)57244-4.

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5

Ponnala, Ravi. "Dynamic Power System Monitoring and Protection Using Phasor Measurements and Less Data Storage System." Journal of Advanced Research in Dynamical and Control Systems 12, SP8 (July 30, 2020): 625–36. http://dx.doi.org/10.5373/jardcs/v12sp8/20202564.

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6

Ma, Feng, and Vijay Vittal. "Right-Sized Power System Dynamic Equivalents for Power System Operation." IEEE Transactions on Power Systems 26, no. 4 (November 2011): 1998–2005. http://dx.doi.org/10.1109/tpwrs.2011.2138725.

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7

Gulati, Navneet, and Eric J. Barth. "Dynamic Modeling of a Monopropellant-Based Chemofluidic Actuation System." Journal of Dynamic Systems, Measurement, and Control 129, no. 4 (October 17, 2006): 435–45. http://dx.doi.org/10.1115/1.2718243.

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Анотація:
This paper presents a dynamic model of a monopropellant-based chemofluidic power supply and actuation system. The proposed power supply and actuation system, as presented in prior works, is motivated by the current lack of a viable system that can provide adequate energetic autonomy to human-scale power-comparable untethered robotic systems. As such, the dynamic modeling presented herein is from an energetic standpoint by considering the power and energy exchanged and stored in the basic constituents of the system. Two design configurations of the actuation system are presented and both are modeled. A first-principle based lumped-parameter model characterizing reaction dynamics, hydraulic flow dynamics, pneumatic flow dynamics, and compressible gas dynamics is developed for purposes of control design. Experimental results are presented that validate the model.
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8

Sun, Shu Xia, Xiang Jun Zhu, and Ming Ming Wang. "Power Turret the Dynamics Simulation Analysis of Power Turret." Applied Mechanics and Materials 198-199 (September 2012): 133–36. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.133.

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The dynamic performance of the CNC turret affect the cutting capability and cutting efficiency of the NC machine tool directly, embody the core level of the design and manufacture of the NC machine tool. However, the dynamic performance of the CNC turret mostly decided by the dynamic performance of the power transmission system of the power turret. This passage use Pro/E to set the accurate model of the gears and the CAD model of the gear transmission system and based on this to constitute the ADAMS model of virtual prototype. On the many-body contact dynamics theory basis, dynamic describes the process of the mesh of the gears, work out the dynamic meshing force under the given input rotating speed and loading, and the vibration response of the gear system. The simulation result disclosure the meshing shock excitation and periodical fluctuation phenomena arose by stiffness excitation of the gear transmission. Analyses and pick-up the radial vibration response of the output gear of the gear transmission system as the feasibility analysis data.
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Zhang, Qiang, Bao Li, Quan Yuan, Mingfu Lu, and Xinlei Huang. "Database dynamic update management system for power system." Journal of Physics: Conference Series 1550 (May 2020): 052001. http://dx.doi.org/10.1088/1742-6596/1550/5/052001.

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Gharban, C. K., and B. J. Cory. "Nonlinear Dynamic Power System State Estimation." IEEE Power Engineering Review PER-6, no. 8 (August 1986): 54–55. http://dx.doi.org/10.1109/mper.1986.5527808.

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Дисертації з теми "Power system dynamic"

1

Hockenberry, James Richard. "Power system dynamic load modeling." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/42594.

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Demiray, Turhan Hilmi. "Simulation of power system dynamics using dynamic phasor models /." Zürich : ETH, 2008. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=17607.

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3

Bousnane, Kafiha. "Real-time power system dynamic simulation." Thesis, Durham University, 1990. http://etheses.dur.ac.uk/6623/.

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Анотація:
The present day digital computing resources are overburdened by the amount of calculation necessary for power system dynamic simulation. Although the hardware has improved significantly, the expansion of the interconnected systems, and the requirement for more detailed models with frequent solutions have increased the need for simulating these systems in real time. To achieve this, more effort has been devoted to developing and improving the application of numerical methods and computational techniques such as sparsity-directed approaches and network decomposition to power system dynamic studies. This project is a modest contribution towards solving this problem. It consists of applying a very efficient sparsity technique to the power system dynamic simulator under a wide range of events. The method used was first developed by Zollenkopf (^117) Following the structure of the linear equations related to power system dynamic simulator models, the original algorithm which was conceived for scalar calculation has been modified to use sets of 2 * 2 sub-matrices for both the dynamic and algebraic equations. The realisation of real-time simulators also requires the simplification of the power system models and the adoption of a few assumptions such as neglecting short time constants. Most of the network components are simulated. The generating units include synchronous generators and their local controllers, and the simulated network is composed of transmission lines and transformers with tap-changing and phase-shifting, non-linear static loads, shunt compensators and simplified protection. The simulator is capable of handling some of the severe events which occur in power systems such as islanding, island re-synchronisation and generator start-up and shut-down. To avoid the stiffness problem and ensure the numerical stability of the system at long time steps at a reasonable accuracy, the implicit trapezoidal rule is used for discretising the dynamic equations. The algebraisation of differential equations requires an iterative process. Also the non-linear network models are generally better solved by the Newton-Raphson iterative method which has an efficient quadratic rate of convergence. This has favoured the adoption of the simultaneous technique over the classical partitioned method. In this case the algebraised differential equations and the non-linear static equations are solved as one set of algebraic equations. Another way of speeding-up centralised simulators is the adoption of distributed techniques. In this case the simulated networks are subdivided into areas which are computed by a multi-task machine (Perkin Elmer PE3230). A coordinating subprogram is necessary to synchronise and control the computation of the different areas, and perform the overall solution of the system. In addition to this decomposed algorithm the developed technique is also implemented in the parallel simulator running on the Array Processor FPS 5205 attached to a Perkin Elmer PE 3230 minicomputer, and a centralised version run on the host computer. Testing these simulators on three networks under a range of events would allow for the assessment of the algorithm and the selection of the best candidate hardware structure to be used as a dedicated machine to support the dynamic simulator. The results obtained from this dynamic simulator are very impressive. Great speed-up is realised, stable solutions under very severe events are obtained showing the robustness of the system, and accurate long-term results are obtained. Therefore, the present simulator provides a realistic test bed to the Energy Management System. It can also be used for other purposes such as operator training.
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4

Zhong, Zhian. "Power Systems Frequency Dynamic Monitoring System Design and Applications." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28707.

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Анотація:
Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet. The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation.
Ph. D.
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5

Song, Xuefeng. "Dynamic modeling issues for power system applications." Texas A&M University, 2003. http://hdl.handle.net/1969.1/1591.

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Power system dynamics are commonly modeled by parameter dependent nonlinear differential-algebraic equations (DAE) x p y x f ) and 0 = p y x g ) . Due to (,, (,, the algebraic constraints, we cannot directly perform integration based on the DAE. Traditionally, we use implicit function theorem to solve for fast variables y to get a reduced model in terms of slow dynamics locally around x or we compute y numerically at each x . However, it is well known that solving nonlinear algebraic equations analytically is quite difficult and numerical solution methods also face many uncertainties since nonlinear algebraic equations may have many solutions, especially around bifurcation points. In this thesis, we apply the singular perturbation method to model power system dynamics in a singularly perturbed ODE (ordinary-differential equation) form, which makes it easier to observe time responses and trace bifurcations without reduction process. The requirements of introducing the fast dynamics are investigated and the complexities in the procedures are explored. Finally, we propose PTE (Perturb and Taylor’s expansion) technique to carry out our goal to convert a DAE to an explicit state space form of ODE. A simplified unreduced Jacobian matrix is also introduced. A dynamic voltage stability case shows that the proposed method works well without complicating the applications.
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6

Singhavilai, Thamvarit. "Identification of electric power system dynamic equivalent." Thesis, University of Strathclyde, 2011. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=15647.

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7

Geitner, Gert-Helge, and Guven Komurgoz. "Power Flow Modelling of Dynamic Systems." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-171305.

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Анотація:
As tools for dynamic system modelling both conventional methods such as transfer function or state space representation and modern power flow based methods are available. The latter methods do not depend on energy domain, are able to preserve physical system structures, visualize power conversion or coupling or split, identify power losses or storage, run on conventional software and emphasize the relevance of energy as basic principle of known physical domains. Nevertheless common control structures as well as analysis and design tools may still be applied. Furthermore the generalization of power flow methods as pseudo-power flow provides with a universal tool for any dynamic modelling. The phenomenon of power flow constitutes an up to date education methodology. Thus the paper summarizes fundamentals of selected power flow oriented modelling methods, presents a Bond Graph block library for teaching power oriented modelling as compact menu-driven freeware, introduces selected examples and discusses special features.
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8

Newham, Nikki. "Power System Investment Planning using Stochastic Dual Dynamic Programming." Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/1975.

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Анотація:
Generation and transmission investment planning in deregulated markets faces new challenges particularly as deregulation has introduced more uncertainty to the planning problem. Tradi- tional planning techniques and processes cannot be applied to the deregulated planning problem as generation investments are profit driven and competitive. Transmission investments must facilitate generation access rather than servicing generation choices. The new investment plan- ning environment requires the development of new planning techniques and processes that can remain flexible as uncertainty within the system is revealed. The optimisation technique of Stochastic Dual Dynamic Programming (SDDP) has been success- fully used to optimise continuous stochastic dynamic planning problems such as hydrothermal scheduling. SDDP is extended in this thesis to optimise the stochastic, dynamic, mixed integer power system investment planning problem. The extensions to SDDP allow for optimisation of large integer variables that represent generation and transmission investment options while still utilising the computational benefits of SDDP. The thesis also details the development of a math- ematical representation of a general power system investment planning problem and applies it to a case study involving investment in New Zealand’s HVDC link. The HVDC link optimisation problem is successfully solved using the extended SDDP algorithm and the output data of the optimisation can be used to better understand risk associated with capital investment in power systems. The extended SDDP algorithm offers a new planning and optimisation technique for deregulated power systems that provides a flexible optimal solution and informs the planner about investment risk associated with uncertainty in the power system.
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9

Wu, Qiang. "Tap changing dynamic modeling and its effects on power system voltage behavior." Thesis, The University of Sydney, 1998. https://hdl.handle.net/2123/27640.

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This thesis presents research results on the effects of tap changing dynamic modeling on power system mid-to-long term voltage behavior. The modeling of tap changing dynamics in voltage stability studies is first addressed. The dynamic operation of an on-load-tap—changing transformer is represented by a highly nonlinear, discrete and time—delay embedded model, which is suitable to mid-to—long term voltage stability studies. Different discrete tap models and their continuous approximations with respect to time and tap position are introduced. The initial emphasis is on studying the influences of different discrete and continuous tap models on voltage stability properties. Combining the tap changer dynamics with the detailed load dynamics, the impacts of different tap models on system voltage behavior are illustrated via theoretical analysis and simulation. It is shown that different stability regions are associated with different continuous tap models and significantly influence the system/voltage behavior, especially under heavily loaded system conditions. The Lyapunov stability method is used to predict the stability region. Limit cycle phenomena are observed in systems with discrete tap models due to the inherent nonlinearities present in these models, the tap dynamics and its interaction with the load dynamics. Conditions for existence of limit cycles are derived via the describing function method. Cases when discrete tap models and their corresponding continuous approximations result in different and / or similar system behavior are also illustrated. Further, a detailed study is given on. the voltage oscillation phenomenon in power systems with on-load—tap—changers. Two kinds of oscillations are considered, namely the well-known voltage oscillations due to tap hunting and oscillations due to tap— load interactions. The focus is on the limit cycle caused by the tap-load interaction. The effects of tap deadband and other parameters such as tap delay time and load recovery time on the existence of system cyclic behavior are carefully investigated. It. is shown that whether or not the limit cycle can be avoided by adjusting the tap deadband depends mainly on the load characteristics. Trajectory sensitivity analysis offers useful information on the influence of parameters on system cyclic behavior. Next, consideration is given to the coordination of a tap changer, as a voltage control device, with other controls, such as a switching capacitor. Using the results of voltage stability analysis as a framework, a new approach for the coordination of dissimilar control actions is derived for arresting voltage collapse. The benefits of coordination of tap locking and capacitor switching are demonstrated foi two possible situations. Firstly, prior capacitor switching at some buses is shown to expand the stability regioh and provide sufficient time for successful tap locking. Secondly, locking taps at some buses can slow the system deterioration and provides time for capacitor switching. The results obtained not only highlight the importance of tap dynamics modeling in voltage behavior studies, but also give an insight into system voltage stability evaluatiofi and control involving on—load-tap—changer dynamics.
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10

Troullinos, George. "Estimating order reduction for dynamic systems with applications to power system equivalents." Diss., Georgia Institute of Technology, 1988. http://hdl.handle.net/1853/13449.

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Книги з теми "Power system dynamic"

1

M, Friefeld Jerry, and United States. National Aeronautics and Space Administration., eds. Solar dynamic power system definition study: Final report. Canoga Park, Calif: Rocketdyne Division, Rockwell International Corporation, 1988.

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2

IEEE Power System Engineering Committee., ed. Eigenanalysis and frequency domain methods for system dynamic performance. New York, NY, USA (345 E. 47th St., New York 10017-2394): Institute of Electrical and Electronics Engineers, 1989.

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3

Perez-Davis, Marla E. Sensible heat receiver for solar dynamic space power system. [Washington, DC]: National Aeronautics and Space Administration, 1991.

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4

Center, Lewis Research. Solar dynamic power system development for Space Station Freedom. Cleveland, Ohio: Lewis Research Center, 1993.

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5

United States. National Aeronautics and Space Administration., ed. Solar simulator for solar dynamic space power system testing. [Washington, DC]: National Aeronautics and Space Administration, 1993.

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6

Lewis Research Center. Solar Dynamic Power System Branch. and United States. National Aeronautics and Space Administration. Scientific and Technical Information Program., eds. Solar dynamic power system development for Space Station Freedom. [Washington, D.C.]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1993.

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7

Bai, Shushan. Dynamic analysis and control system design of automatic transmissions. Warrendale, Pennsylvania, USA: SAE International, 2013.

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8

T, Farmer J., and Langley Research Center, eds. System impacts of solar dynamic and growth power systems on space station. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1986.

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9

United States. National Aeronautics and Space Administration., ed. Small stirling dynamic isotope power system for multihundred-watt robotic missions. [Washington, DC]: National Aeronautics and Space Administration, 1991.

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10

Power reading: A dynamic system for mastering all your business reading. Englewood Cliffs, N.J: Prentice Hall, 1993.

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Частини книг з теми "Power system dynamic"

1

Annakkage, Udaya D. "Dynamic System Equivalents." In Transient Analysis of Power Systems, 581–600. Chichester, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118694190.oth2.

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2

Gaglioti, Enrico, and Adriano Iaria. "Power System Dynamic Phenomena." In Monitoring, Control and Protection of Interconnected Power Systems, 35–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-53848-3_3.

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3

Čepin, Marko. "Dynamic Programming." In Assessment of Power System Reliability, 253–55. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-688-7_17.

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4

JU, Ping. "Stochastic Dynamic Simulation of Power System." In Power Systems, 41–72. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1816-0_3.

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JU, Ping. "Stochastic Dynamic Oscillation of Power System." In Power Systems, 91–143. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1816-0_5.

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JU, Ping. "Stochastic Dynamic Security of Power System." In Power Systems, 145–94. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1816-0_6.

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Khaitan, Siddhartha Kumar, and James D. McCalley. "Dynamic Load Balancing and Scheduling for Parallel Power System Dynamic Contingency Analysis." In Power Systems, 189–209. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32683-7_6.

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Khaitan, Siddhartha Kumar, and James D. McCalley. "High Performance Computing for Power System Dynamic Simulation." In Power Systems, 43–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32683-7_2.

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Micheli, Giovanni, Luca Benini, and Alessandro Bogliolo. "Dynamic Power Management of Electronic Systems." In System-Level Synthesis, 263–92. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4698-2_8.

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Soroudi, Alireza. "Dynamic Economic Dispatch." In Power System Optimization Modeling in GAMS, 95–118. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62350-4_4.

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Тези доповідей конференцій з теми "Power system dynamic"

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Benini, L., A. Bogliolo, and G. De Micheli. "System-level dynamic power management." In Proceedings IEEE Alessandro Volta Memorial Workshop on Low-Power Design. IEEE, 1999. http://dx.doi.org/10.1109/lpd.1999.750384.

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2

Arora, Ritika, and Surender Dahiya. "Dynamic stability enhancement of power system using PSO optimized fuzzy power system stabilizer." In 2014 6th IEEE Power India International Conference (PIICON). IEEE, 2014. http://dx.doi.org/10.1109/poweri.2014.7117618.

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3

Otting, William D., Maribeth E. Hunt, Thomas L. Ashe, Mohamed S. El-Genk, and Mark D. Hoover. "Dynamic Isotope Power System, Integrated System Test." In SPACE NUCLEAR POWER AND PROPULSION: Eleventh Symposium. AIP, 1994. http://dx.doi.org/10.1063/1.2950204.

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Apostoaia, Constantin M., and Mihai Cernat. "A Dynamic Inductive Power Transfer System." In 2019 8th International Conference on Renewable Energy Research and Applications (ICRERA). IEEE, 2019. http://dx.doi.org/10.1109/icrera47325.2019.8997072.

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Ruhle, Olaf, and Florin Balasin. "Simulations of Power System dynamic phenomena." In 2009 IEEE Bucharest PowerTech (POWERTECH). IEEE, 2009. http://dx.doi.org/10.1109/ptc.2009.5282074.

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Rahman, Md Ashfaqur, and Ganesh Kumar Venayagamoorthy. "Power system distributed dynamic state prediction." In 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2016. http://dx.doi.org/10.1109/ssci.2016.7849847.

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Thabet, A., M. Boutayeb, G. Didier, S. Chniba, and M. N. Abdelkrim. "Fault diagnosis for dynamic power system." In 2011 8th International Multi-Conference on Systems, Signals and Devices (SSD 2011). IEEE, 2011. http://dx.doi.org/10.1109/ssd.2011.5767361.

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Fani, Bahador, Mehdi Mahdavian, Saeed Farazpey, Mohammadreza Janghorbani, and Manijeh Azadeh. "Improving dynamic stability of power system using derivative power system stabilizer." In 2016 13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). IEEE, 2016. http://dx.doi.org/10.1109/ecticon.2016.7560904.

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9

Rosenberg, R. C., and T. Zhou. "Power-Based Simplification of Dynamic System Models." In ASME 1988 Design Technology Conferences. American Society of Mechanical Engineers, 1988. http://dx.doi.org/10.1115/detc1988-0062.

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Abstract Simplification of system models is done in a variety of ways. A new approach based on measures of power interaction within a system graph model is presented in this paper. The method can detect the existence and location of weak coupling in both linear and nonlinear systems. Weak coupling may be exploited by partitioning the system into subsystems or by eliminating unimportant effects. Both types of simplification typically lead to reduced computational loads and greater model insight.
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10

Jinquan Zhao, Lijie Ju, Weihua Luo, and Jun Zhao. "Reactive power optimization considering dynamic reactive power reserves." In 2014 International Conference on Power System Technology (POWERCON). IEEE, 2014. http://dx.doi.org/10.1109/powercon.2014.6993530.

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Звіти організацій з теми "Power system dynamic"

1

Johnson, G., W. Determan, and W. Otting. NASA low power DIPS [Dynamic Isotope Power System] conceptual design requirements document. Office of Scientific and Technical Information (OSTI), January 1990. http://dx.doi.org/10.2172/721000.

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2

Dagle, J. E., D. W. Winiarski, and M. K. Donnelly. End-use load control for power system dynamic stability enhancement. Office of Scientific and Technical Information (OSTI), February 1997. http://dx.doi.org/10.2172/484515.

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3

Kueck, John D., D. Tom Rizy, Fangxing Li, Yan Xu, Huijuan Li, Sarina Adhikari, and Philip Irminger. Local Dynamic Reactive Power for Correction of System Voltage Problems. Office of Scientific and Technical Information (OSTI), December 2008. http://dx.doi.org/10.2172/945348.

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4

Wichner, R. P., A. D. Solomon, J. B. Drake, and P. T. Williams. Thermal analysis of heat storage canisters for a solar dynamic, space power system. Office of Scientific and Technical Information (OSTI), April 1988. http://dx.doi.org/10.2172/7050127.

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5

Muelaner, Jody Emlyn. Electric Road Systems for Dynamic Charging. SAE International, March 2022. http://dx.doi.org/10.4271/epr2022007.

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Electric road systems (ERS) enable dynamic charging—the most energy efficient and economical way to decarbonize road vehicles. ERS draw electrical power directly from the grid and enable vehicles with small batteries to operate without the need to stop for charging. The three main technologies (i.e., overhead catenary lines, road-bound conductive tracks, and inductive wireless systems in the road surface) are all technically proven; however, no highway system has been commercialized. Electric Road Systems for Dynamic Charging discusses the technical and economic advantages of dynamic charging and questions the current investment in battery-powered and hydrogen-fueled vehicles.
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6

Flueck, Alex. High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report. Office of Scientific and Technical Information (OSTI), July 2017. http://dx.doi.org/10.2172/1369569.

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7

Hauer, John F. Initial Results in the Use of Prony Methods to Determine the Damping and Modal Composition of Power System Dynamic Response Signals. Office of Scientific and Technical Information (OSTI), October 1988. http://dx.doi.org/10.2172/6174430.

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8

Schock, Alfred. Structural, Thermal, and Safety Analysis of Isotope Heat Source and Integrated Heat Exchangers for 6-kWe Dynamic Isotope Power System (DIPS). Office of Scientific and Technical Information (OSTI), January 1989. http://dx.doi.org/10.2172/1033408.

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9

Schock, Alfred. Design of Isotope Heat Source for Automatic Modular Dispersal During Reentry, and Its Integration with Heat Exchangers of 6-kWe Dynamic Isotope Power System. Office of Scientific and Technical Information (OSTI), January 1989. http://dx.doi.org/10.2172/1033407.

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10

Swaminathan, Vishnu, Krishnendu Chakrabarty, and S. S. Iyengar. Dynamic I/O Power Management for Hard Real-Time Systems. Fort Belvoir, VA: Defense Technical Information Center, January 2005. http://dx.doi.org/10.21236/ada440182.

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