Relevant bibliographies by topics / Uncertain power flow analysis

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

Academic literature on the topic 'Uncertain power flow analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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Journal articles on the topic "Uncertain power flow analysis"

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Laib, Khaled, Anton Korniienko, Florent Morel, and Gérard Scorletti. "LMI based approach for power flow analysis with uncertain power injection." IFAC-PapersOnLine 51, no. 25 (2018): 310–15. http://dx.doi.org/10.1016/j.ifacol.2018.11.125.

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Coletta, Guido, Alfredo Vaccaro, and Domenico Villacci. "Fast and reliable uncertain power flow analysis by affine arithmetic." Electric Power Systems Research 175 (October 2019): 105860. http://dx.doi.org/10.1016/j.epsr.2019.04.038.

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Luo, Jinqing, Libao Shi, and Yixin Ni. "Uncertain Power Flow Analysis Based on Evidence Theory and Affine Arithmetic." IEEE Transactions on Power Systems 33, no. 1 (January 2018): 1113–15. http://dx.doi.org/10.1109/tpwrs.2017.2691539.

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Lerche, I., and F. Rocha-Legoretta. "Risking Basin Analysis Results." Energy Exploration & Exploitation 21, no. 2 (April 2003): 81–164. http://dx.doi.org/10.1260/014459803322362459.

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The work presented here uses a basin analysis code, developed for Excel, to handle burial history, fluid flow, fracturing, overpressure development with time, erosion events, kerogen breakdown to oil and gas, hydrocarbon volumetrics for both oil and gas including source retention, migration loss, and area changes with time of source rocks for each formation. The code is remarkably fast, requiring about 0.2 seconds on a laptop to perform all the above calculations for ten formations as well as producing pictorial representations of all variables with space and time. The code seamlessly interfaces with the Monte Carlo risking program Crystal Ball so that a total uncertainty analysis can be done with as many uncertain inputs as required and as many outputs of interest as needed without increasing the computer time needed. A thousand Crystal Ball runs take only about 200 seconds, allowing one to investigate many possible scenarios extremely quickly. We show here with four basic examples how one goes about identifying which parameters in the input (ranging from uncertain data, uncertain thermal history, uncertain permeability, uncertain fracture coefficients for rocks, uncertain geochemistry kinetics, uncertain kerogen amounts and types per formation, through to uncertain volumetric factors) are causing the greatest contributions to uncertainty in any and all outputs. The relative importance, relative contributions and relative sensitivity are examined to show when it is necessary to know more about the underlying distributions of uncertain parameters, when it is necessary to know more about the dynamic range of a parameter to narrow its contribution to the total uncertainty, and which parameters are necessary to first focus on to narrow their uncertainty in order to improve the dynamical, thermal or hydrocarbon outputs. An interface of such a coupled pair of very fast Excel codes with an Excel economics package can also now easily be undertaken so that one ties scientific uncertainty and economic uncertainty together for hydrocarbon exploration and identifies the global parameters dominantly influencing the combined economic/basin analysis system.
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Ray, Shashwati, and Shimpy Ralhan. "Reliable power flow and short circuit analysis of systems with uncertain data." International Journal of Reliability and Safety 12, no. 1/2 (2018): 166. http://dx.doi.org/10.1504/ijrs.2018.092519.

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Ray, Shashwati, and Shimpy Ralhan. "Reliable power flow and short circuit analysis of systems with uncertain data." International Journal of Reliability and Safety 12, no. 1/2 (2018): 166. http://dx.doi.org/10.1504/ijrs.2018.10013806.

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Liao, Xiaobing, Kaipei Liu, Yachao Zhang, Kun Wang, and Liang Qin. "Interval method for uncertain power flow analysis based on Taylor inclusion function." IET Generation, Transmission & Distribution 11, no. 5 (March 30, 2017): 1270–78. http://dx.doi.org/10.1049/iet-gtd.2016.1344.

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Ouyang, Bin, Lu Qu, Qiyang Liu, Baoye Tian, Zhichang Yuan, Peiqian Guo, Hongyi Dai, and Weikun He. "Calculation and Analysis of the Interval Power Flow for Distributed Energy System Based on Affine Algorithm." Energies 14, no. 3 (January 25, 2021): 600. http://dx.doi.org/10.3390/en14030600.

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Due to the coupling of different energy systems, optimization of different energy complementarities, and the realization of the highest overall energy utilization rate and environmental friendliness of the energy system, distributed energy system has become an important way to build a clean and low-carbon energy system. However, the complex topological structure of the system and too many coupling devices bring more uncertain factors to the system which the calculation of the interval power flow of distributed energy system becomes the key problem to be solved urgently. Affine power flow calculation is considered as an important solution to solve uncertain steady power flow problems. In this paper, the distributed energy system coupled with cold, heat, and electricity is taken as the research object, the influence of different uncertain factors such as photovoltaic and wind power output is comprehensively considered, and affine algorithm is adopted to calculate the system power flow of the distributed energy system under high and low load conditions. The results show that the system has larger operating space, more stable bus voltage and more flexible pipeline flow under low load condition than under high load condition. The calculation results of the interval power flow of distributed energy systems can provide theoretical basis and data support for the stability analysis and optimal operation of distributed energy systems.
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Kinias, Ioannis, Ioannis Tsakalos, and Nikolaos Konstantopoulos. "Investment evaluation in renewable projects under uncertainty, using real options analysis: the case of wind power industry." Investment Management and Financial Innovations 14, no. 1 (March 31, 2017): 96–103. http://dx.doi.org/10.21511/imfi.14(1).2017.10.

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Investment analysis is a crucial process for any investment’s success. This process can be supported by both the discounted cash flow analysis and the real options analysis. Many researchers have point out restrictions for the first one, in cases of uncertainty in the entrepreneurial environment. The main types of uncertainty, concerning the wind energy sector, include uncertainties related to the price of electriticity by RES, the public policy regulatory policies, the demand, the initial capital costs, the technological progress, the weather conditions, the political and economical situations and generally the RES market structure. In this paper, we try to find the optimal investment strategy in a liberalized global electricity market, where the price of electricity is uncertain while the other parameters are configured separately in each country. The authors consider about the factors of the time for investment and the electricity’s price level, in wind energy by using the real options theory. The authors select a variety of data for the wind energy industry from different countries in several continents, and also create a model for the investment analysis in this entrepreneurial sector.
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Chen, Yue, Zhizhong Guo, Hongbo Li, Yi Yang, Abebe Tilahun Tadie, Guizhong Wang, and Yingwei Hou. "Probabilistic Optimal Power Flow for Day-Ahead Dispatching of Power Systems with High-Proportion Renewable Power Sources." Sustainability 12, no. 2 (January 9, 2020): 518. http://dx.doi.org/10.3390/su12020518.

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With the increasing proportion of uncertain power sources in the power grid; such as wind and solar power sources; the probabilistic optimal power flow (POPF) is more suitable for the steady state analysis (SSA) of power systems with high proportions of renewable power sources (PSHPRPSs). Moreover; PSHPRPSs have large uncertain power generation prediction error in day-ahead dispatching; which is accommodated by real-time dispatching and automatic generation control (AGC). In summary; this paper proposes a once-iterative probabilistic optimal power flow (OIPOPF) method for the SSA of day-ahead dispatching in PSHPRPSs. To verify the feasibility of the OIPOPF model and its solution algorithm; the OIPOPF was applied to a modified Institute of Electrical and Electronic Engineers (IEEE) 39-bus test system and modified IEEE 300-bus test system. Based on a comparison between the simulation results of the OIPOPF and AC power flow models; the OIPOPF model was found to ensure the accuracy of the power flow results and simplify the power flow model. The OIPOPF was solved using the point estimate method based on Gram–Charlier expansion; and the numerical characteristics of the line power were obtained. Compared with the simulation results of the Monte Carlo method; the point estimation method based on Gram–Charlier expansion can accurately solve the proposed OIPOPF model
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Dissertations / Theses on the topic "Uncertain power flow analysis"

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Marin, Manuel. "GPU-enhanced power flow analysis." Thesis, Perpignan, 2015. http://www.theses.fr/2015PERP0041.

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Cette thèse propose un large éventail d'approches afin d'améliorer différents aspects de l'analyse des flux de puissance avec comme fils conducteur l'utilisation du processeurs graphiques (GPU). Si les GPU ont rapidement prouvés leurs efficacités sur des applications régulières pour lesquelles le parallélisme de données était facilement exploitable, il en est tout autrement pour les applications dites irrégulières. Ceci est précisément le cas de la plupart des algorithmes d'analyse de flux de puissance. Pour ce travail, nous nous inscrivons dans cette problématique d'optimisation de l'analyse de flux de puissance à l'aide de coprocesseur de type GPU. L'intérêt est double. Il étend le domaine d'application des GPU à une nouvelle classe de problème et/ou d'algorithme en proposant des solutions originales. Il permet aussi à l'analyse des flux de puissance de rester pertinent dans un contexte de changements continus dans les systèmes énergétiques, et ainsi d'en faciliter leur évolution. Nos principales contributions liées à la programmation sur GPU sont: (i) l'analyse des différentes méthodes de parcours d'arbre pour apporter une réponse au problème de la régularité par rapport à l'équilibrage de charge ; (ii) l'analyse de l'impact du format de représentation sur la performance des implémentations d'arithmétique floue. Nos contributions à l'analyse des flux de puissance sont les suivantes: (ii) une nouvelle méthode pour l'évaluation de l'incertitude dans l'analyse des flux de puissance ; (ii) une nouvelle méthode de point fixe pour l'analyse des flux de puissance, problème que l'on qualifie d'intrinsèquement parallèle
This thesis addresses the utilization of Graphics Processing Units (GPUs) for improving the Power Flow (PF) analysis of modern power systems. Currently, GPUs are challenged by applications exhibiting an irregular computational pattern, as is the case of most known methods for PF analysis. At the same time, the PF analysis needs to be improved in order to cope with new requirements of efficiency and accuracy coming from the Smart Grid concept. The relevance of GPU-enhanced PF analysis is twofold. On one hand, it expands the application domain of GPU to a new class of problems. On the other hand, it consistently increases the computational capacity available for power system operation and design. The present work attempts to achieve that in two complementary ways: (i) by developing novel GPU programming strategies for available PF algorithms, and (ii) by proposing novel PF analysis methods that can exploit the numerous features present in GPU architectures. Specific contributions on GPU computing include: (i) a comparison of two programming paradigms, namely regularity and load-balancing, for implementing the so-called treefix operations; (ii) a study of the impact of the representation format over performance and accuracy, for fuzzy interval algebraic operations; and (iii) the utilization of architecture-specific design, as a novel strategy to improve performance scalability of applications. Contributions on PF analysis include: (i) the design and evaluation of a novel method for the uncertainty assessment, based on the fuzzy interval approach; and (ii) the development of an intrinsically parallel method for PF analysis, which is not affected by the Amdahl's law
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Nasri, Amin. "On the Dynamics and Statics of Power System Operation : Optimal Utilization of FACTS Devicesand Management of Wind Power Uncertainty." Doctoral thesis, KTH, Elektriska energisystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-154576.

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Nowadays, power systems are dealing with some new challenges raisedby the major changes that have been taken place since 80’s, e.g., deregu-lation in electricity markets, significant increase of electricity demands andmore recently large-scale integration of renewable energy resources such aswind power. Therefore, system operators must make some adjustments toaccommodate these changes into the future of power systems.One of the main challenges is maintaining the system stability since theextra stress caused by the above changes reduces the stability margin, andmay lead to rise of many undesirable phenomena. The other important chal-lenge is to cope with uncertainty and variability of renewable energy sourceswhich make power systems to become more stochastic in nature, and lesscontrollable.Flexible AC Transmission Systems (FACTS) have emerged as a solutionto help power systems with these new challenges. This thesis aims to ap-propriately utilize such devices in order to increase the transmission capacityand flexibility, improve the dynamic behavior of power systems and integratemore renewable energy into the system. To this end, the most appropriatelocations and settings of these controllable devices need to be determined.This thesis mainly looks at (i) rotor angle stability, i.e., small signal andtransient stability (ii) system operation under wind uncertainty. In the firstpart of this thesis, trajectory sensitivity analysis is used to determine themost suitable placement of FACTS devices for improving rotor angle sta-bility, while in the second part, optimal settings of such devices are foundto maximize the level of wind power integration. As a general conclusion,it was demonstrated that FACTS devices, installed in proper locations andtuned appropriately, are effective means to enhance the system stability andto handle wind uncertainty.The last objective of this thesis work is to propose an efficient solutionapproach based on Benders’ decomposition to solve a network-constrained acunit commitment problem in a wind-integrated power system. The numericalresults show validity, accuracy and efficiency of the proposed approach.

The Doctoral Degrees issued upon completion of the programme are issued by Comillas Pontifical University, Delft University of Technology and KTH Royal Institute of Technology. The invested degrees are official in Spain, the Netherlands and Sweden, respectively.QC 20141028

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Laib, Khaled. "Analyse hiérarchisée de la robustesse des systèmes incertains de grande dimension." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEC027/document.

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Ces travaux de thèse concernent l'analyse de la robustesse (stabilité et performance) de systèmes linéaires incertains de grande dimension avec une structure hiérarchique. Ces systèmes sont obtenus en interconnectant plusieurs sous-systèmes incertains à travers une topologie hiérarchique. L'analyse de la robustesse de ces systèmes est un problème à deux aspects : la robustesse et la grande dimension. La résolution efficace de ce problème en utilisant les approches usuelles est difficile, voire impossible, à cause de la complexité et de la grande taille du problème d'optimisation associé. La conséquence de cette complexité est une augmentation importante du temps de calcul nécessaire pour résoudre ce problème d'optimisation. Afin de réduire ce temps de calcul, les travaux existants ne considèrent que des classes particulières de systèmes linéaires incertains de grande dimension. De plus, la structure hiérarchique de ces systèmes n'est pas prise en compte, ce qui montre, de notre point de vue, les limitations de ces résultats. Notre objectif est d'exploiter la structure hiérarchique de ces systèmes afin de ramener la résolution du problème d'analyse de grande taille à la résolution d'un ensemble de problèmes d'analyse de faible taille, ce qui aura comme conséquence une diminution du temps de calcul. De plus, un autre avantage de cette approche est la possibilité de résoudre ces problèmes en même temps en utilisant le calcul parallèle. Afin de prendre en compte la structure hiérarchique du système incertain de grande dimension, nous modélisons ce dernier comme l'interconnexion de plusieurs sous-systèmes incertains qui sont eux-mêmes l'interconnexion d'autres sous-systèmes incertains, etc.. Cette technique récursive de modélisation est faite sur plusieurs niveaux hiérarchiques. Afin de réduire la complexité de la représentation des systèmes incertains, nous construisons une base de propriétés de dissipativité pour chaque sous-système incertain de chaque niveau hiérarchique. Cette base contient plusieurs éléments qui caractérisent des informations utiles sur le comportement de systèmes incertains. Des exemples de telles caractérisations sont : la caractérisation de la phase incertaine, la caractérisation du gain incertain, etc.. L'obtention de chaque élément est relaxée comme un problème d'optimisation convexe ou quasi-convexe sous contraintes LMI. L'analyse de la robustesse de systèmes incertains de grande dimension est ensuite faite de façon hiérarchique en propageant ces bases de propriétés de dissipativité d'un niveau hiérarchique à un autre. Nous proposons deux algorithmes d'analyse hiérarchique qui permettent de réduire le temps de calcul nécessaire pour analyser la robustesse de ces systèmes. Un avantage important de notre approche est la possibilité d'exécuter des parties de ces algorithmes de façon parallèle à chaque niveau hiérarchique ce qui diminuera de façon importante ce temps de calcul. Pour finir et dans le même contexte de système de grande dimension, nous nous intéressons à l'analyse de la performance dans les réseaux électriques et plus particulièrement «l'analyse du flux de puissances incertaines dans les réseaux électriques de distribution». Les sources d'énergies renouvelables comme les éoliennes et les panneaux solaires sont influencées par plusieurs facteurs : le vent, l'ensoleillement, etc.. Les puissances générées par ces sources sont alors intermittentes, variables et difficiles à prévoir. L'intégration de telles sources de puissance dans les réseaux électriques influencera les performances en introduisant des incertitudes sur les différentes tensions du réseau. L'analyse de l'impact des incertitudes de puissances sur les tensions est appelée «analyse du flux de puissances incertaines». La détermination de bornes sur les modules des différentes tensions est formulée comme un problème d'optimisation convexe sous contraintes LMI
This PhD thesis concerns robustness analysis (stability and performance) of uncertain large scale systems with hierarchical structure. These systems are obtained by interconnecting several uncertain sub-systems through a hierarchical topology. Robustness analysis of these systems is a two aspect problem: robustness and large scale. The efficient resolution of this problem using usual approaches is difficult, even impossible, due to the high complexity and the large size of the associated optimization problem. The consequence of this complexity is an important increase of the computation time required to solve this optimization problem. In order to reduce this computation time, the existing results in the literature focus on particular classes of uncertain linear large scale systems. Furthermore, the hierarchical structure of the large scale system is not taken into account, which means, from our point of view, that these results have several limitations on different levels. Our objective is to exploit the hierarchical structure to obtain a set of small scale size optimization problems instead of one large scale optimization problem which will result in an important decrease in the computation time. Furthermore, another advantage of this approach is the possibility of solving these small scale optimization problems in the same time using parallel computing. In order to take into account the hierarchical structure, we model the uncertain large scale system as the interconnection of uncertain sub-systems which themselves are the interconnection of other uncertain sub-systems, etc.. This recursive modelling is performed at several hierarchical levels. In order to reduce the representation complexity of uncertain systems, we construct a basis of dissipativity properties for each uncertain sub-system at each hierarchical level. This basis contains several elements which characterize different useful information about uncertain system behaviour. Examples of such characterizations are: uncertain phase characterization, uncertain gain characterization, etc.. Obtaining each of these elements is relaxed as convex or quasi-convex optimization problem under LMI constraints. Robustness analysis of uncertain large scale systems is then performed in a hierarchical way by propagating these dissipativity property bases from one hierarchical level to another. We propose two hierarchical analysis algorithms which allow to reduce the computation time required to perform the robustness analysis of the large scale systems. Another key point of these algorithms is the possibility to be performed in parallel at each hierarchical level. The advantage of performing robustness analysis in parallel is an important decrease of the required computation time. Finally and within the same context of robustness analysis of uncertain large scale systems, we are interested in robustness analysis of power networks and more precisely in "the uncertain power flow analysis in distribution networks". The renewable energy resources such as solar panels and wind turbines are influenced by many factors: wind, solar irradiance, etc.. Therefore, the power generated by these resources is intermittent, variable and difficult to predict. The integration of such resources in power networks will influence the network performances by introducing uncertainties on the different network voltages. The analysis of the impact of power uncertainties on the voltages is called "uncertain power flow analysis". Obtaining the boundaries for the different modulus of these voltages is formulated as a convex optimization problem under LMI constraints
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MacMartin, Douglas G. "An H [infinity] power flow approach to control of uncertain structures." Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/42189.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1990.
On t.p. "[infinity]" is the symbol.
Includes bibliographical references (leaves 92-95).
by Douglas G. MacMartin.
M.S.
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Glockner, Gregory D. "Dynamic network flow with uncertain arc capacities." Diss., Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/30734.

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Athari, Mir Hadi. "Modeling Cascading Failures in Power Systems in the Presence of Uncertain Wind Generation." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5936.

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One of the biggest threats to the power systems as critical infrastructures is large-scale blackouts resulting from cascading failures (CF) in the grid. The ongoing shift in energy portfolio due to ever-increasing penetration of renewable energy sources (RES) may drive the electric grid closer to its operational limits and introduce a large amount of uncertainty coming from their stochastic nature. One worrisome change is the increase in CFs. The CF simulation models in the literature do not allow consideration of RES penetration in studying the grid vulnerability. In this dissertation, we have developed tools and models to evaluate the impact of RE penetration on grid vulnerability to CF. We modeled uncertainty injected from different sources by analyzing actual high-resolution data from North American utilities. Next, we proposed two CF simulation models based on simplified DC power flow and full AC power flow to investigate system behavior under different operating conditions. Simulations show a dramatic improvement in the line flow uncertainty estimation based on the proposed model compared to the simplified DC OPF model. Furthermore, realistic assumptions on the integration of RE resources have been made to enhance our simulation technique. The proposed model is benchmarked against the historical blackout data and widely used models in the literature showing similar statistical patterns of blackout size.
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Bayan, Nima. "Harmonic flow analysis in power distribution networks." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0011/MQ52509.pdf.

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Dandachi, Najib H. "Network flow method for power system analysis." Thesis, Imperial College London, 1989. http://hdl.handle.net/10044/1/47398.

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Yang, J. "Power flow analysis of nonlinear dynamical systems." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/355696/.

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The power ow analysis approach, which arose from high frequency vibration problems, has been developed into a powerful technique to characterise the dynamic behaviour of complex structures and coupled systems. It has been extensively used to study various linear systems. However, because of the complexity in modelling and simulation, the power ow behaviour of nonlinear dynamical systems remains largely unexplored. This thesis aims to develop power ow analysis approaches for nonlinear dynamical systems, to investigate the effects of damping and/or stiffness nonlinearities on their power ow behaviour, and to apply the findings to enhance the performance of energy harvesting devices as well as vibration control systems. Power ow characteristics of the Du�ng and the Van der Pol (VDP) oscillators are investigated to address the distinct power input and dissipation behaviour due to stiffness and damping nonlinearities, respectively. It is shown that in a nonlinear velocity response with multiple frequency signatures, only the in-phase component of the same frequency as the harmonic excitation contributes to the time-averaged input power. It is demonstrated that bifurcations can cause significant jumps of time-averaged power ows, whereas the associated time-averaged input power of a chaotic response is insensitive to the initial conditions but tends to an asymptotic value as the averaging time increases. It is also found that the time averaged input power of the unforced VDP oscillator can become negative in some ranges of excitation frequencies. Power ow behaviour of two degrees-of-freedom systems with nonlinear stiffness/- damping is also studied using the developed methods to enhance vibration isolation/absorption performance. It is demonstrated that the stiffness and damping nonlinearities in the system affects time-averaged power ows mainly in a narrow frequency range around resonance frequencies. The work described in this thesis provides new insights into power ow generation, transmission and dissipation mechanisms in nonlinear dynamical systems and facilitates more reliable and effective designs with improved dynamic performance. The ability of the VDP oscillator to extract external energy sheds light on energy harvesting using ow-induced vibrations of a nonlinear apping foil system. A nonlinear isolator with a negative sti�ness mechanism is proposed providing less input power in an enlarged frequency range. These studies thus yield an improved understanding of power ow behaviour in nonlinear dynamical systems.
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Lande, Rolf Helge. "The development of power absorbing matrices for the vibration analysis of complex uncertain structures." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614269.

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Books on the topic "Uncertain power flow analysis"

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Power system analysis: Short-circuit load flow and harmonics. 2nd ed. Boca Raton: CRC Press, 2012.

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Power system analysis: Short-circuit load flow and harmonics. New York: Marcel Dekker, 2002.

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G, Wilson David, and SpringerLink (Online service), eds. Nonlinear Power Flow Control Design: Utilizing Exergy, Entropy, Static and Dynamic Stability, and Lyapunov Analysis. London: Springer-Verlag London Limited, 2011.

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Heitz, L. F. Prediction of flow duration curves for use in hydropower analysis at ungaged sites in Pohnpei, FSM. Mangilao, Guam]: Water and Environmental Research Institute of the Western Pacific, University of Guam, 2010.

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Borkowski, Dariusz. Matrix converter as power flow controller in transmission line--operation analysis in frequency domain: Przekształtnik macierzowy jako kontroler przepływu mocy w linii elektroenergetycznej--analiza pracy układu w dziedzinie częstotliwości = [Matrichnyĭ preobrazovatelʹ kak reguli︠a︡tor peretoka moshchnosti v linii ėlektroperedachi--analiz po operat︠s︡iĭ v oblasti chastot]. Kraków: Politechnika Krakowska im. Tadeusza Kościuszki, 2013.

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Power System Load Flow Analysis (Professional Engineering). McGraw-Hill Professional, 2004.

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Powell, Lynn. Power System Load Flow Analysis (Professional Engineering). McGraw-Hill Professional, 2004.

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1952-, Bernhard Robert, and United States. National Aeronautics and Space Administration., eds. Vibrational power flow analysis of rods and beams. [West Lafayette, Ind: Purdue University, 1988.

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Morin, Philip S. G. Power flow and fault analysis by computer methods. Bradford, 1985.

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Das, J. C. Power System Analysis: Short-Circuit Load Flow and Harmonics (Power Engineering). CRC, 2002.

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Book chapters on the topic "Uncertain power flow analysis"

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Abebe, Yoseph Mekonnen, Mallikarjuna Rao Pasumarthi, and Gopichand Naik Mudavath. "Load Flow Analysis of Uncertain Power System Through Affine Arithmetic." In Lecture Notes in Electrical Engineering, 217–31. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2728-1_20.

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Milano, Federico. "Power Flow Analysis." In Power System Modelling and Scripting, 61–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13669-6_4.

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Tuinema, Bart W., José L. Rueda Torres, Alexandru I. Stefanov, Francisco M. Gonzalez-Longatt, and Mart A. M. M. van der Meijden. "Probabilistic Power Flow Analysis." In Probabilistic Reliability Analysis of Power Systems, 179–208. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43498-4_6.

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Milano, Federico. "Continuation Power Flow Analysis." In Power System Modelling and Scripting, 103–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13669-6_5.

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Milano, Federico. "Optimal Power Flow Analysis." In Power System Modelling and Scripting, 131–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13669-6_6.

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Arrillaga, J., and C. P. Arnold. "Load Flow." In Computer Analysis of Power Systems, 7–41. West Sussex, England: John Wiley & Sons, Ltd., 2013. http://dx.doi.org/10.1002/9781118878309.ch2.

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Debs, Atif S. "Load Flow Analysis." In Modern Power Systems Control and Operation, 19–86. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1073-0_3.

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Salam, Md Abdus. "Load Flow Analysis." In Fundamentals of Electrical Power Systems Analysis, 317–77. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3212-2_7.

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Soman, S. A., S. A. Khaparde, and Shubha Pandit. "Optimal Power Flow." In Computational Methods for Large Sparse Power Systems Analysis, 257–92. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0823-6_11.

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Soman, S. A., S. A. Khaparde, and Shubha Pandit. "Load Flow Analysis." In Computational Methods for Large Sparse Power Systems Analysis, 147–78. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0823-6_8.

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Conference papers on the topic "Uncertain power flow analysis"

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Zhang, Cong, Haoyong Chen, Ke Shi, Zipeng Liang, and Dong Hua. "Range Analysis of Power Flow in Electric Power Systems Incorporating Uncertain Wind Power Generation." In 2018 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia). IEEE, 2018. http://dx.doi.org/10.1109/isgt-asia.2018.8467798.

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Keyser, David R. "Accuracy Analysis of Code-Test Flow Measurements." In ASME 2006 Power Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/power2006-88179.

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Analysis and estimation of uncertainty is presented for several typical Code-test situations for PTC-approved, differential pressure, flow-measurement systems. These analyses trace the calibration pedigree from the fundamental standards at NIST to the implementation of the instrumentation at the test site.
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Marin, Manuel, David Defour, and Federico Milano. "Power flow analysis under uncertainty using symmetric fuzzy arithmetic." In 2014 IEEE Power & Energy Society General Meeting. IEEE, 2014. http://dx.doi.org/10.1109/pesgm.2014.6939274.

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Hering, Michael S., and David R. Mesnard. "Understanding Measurement Uncertainty in DP Flow Devices." In ASME 2014 Power Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/power2014-32205.

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This paper examines the concepts and methods involved in the uncertainty analysis of a differential pressure flow measurement, including which variables have the greatest influence on the uncertainty, and how to effectively manage the influence of error sources on the measurement. An uncertainty analysis will provide the user with a good measure of actual and/or potential system performance and can be instrumental in identifying potential areas of improvement in system performance. The wide availability of instruments of all types and levels of performance presents a difficult decision to those who are responsible for project success and budgets. Optimizing the investment in instrumentation is possible when the required performance is known based an appropriate uncertainty analysis.
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Nystrom, James B., and Philip S. Stacy. "Calibration Uncertainty of PTC-6 Flow Sections." In ASME 2006 Power Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/power2006-88058.

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PTC 6-2004 Performance Test Code on Steam Turbines [1] delineates fabrication and calibration requirements for throat tap flow nozzles with the purpose of obtaining the best feasible accuracy of flow measurement, a primary measurement to determine turbine performance. The Code requires nozzle discharge coefficient calibration results meet tight specifications for average value and rate of change with throat Reynolds number. Performance specifications were developed from large historical, empirical bases and an extensive theoretical analysis. Calibration uncertainty for PTC-6 Flow Meters using gravimetric flow measurement method in accordance with ASME/ANSI MFC 9M Measurement of Liquid Flow in Closed Conduits by Weighing Method [2] using a 100,000 lb capacity weigh tank is estimated. Calibration results are compared to Code requirements for about 330 meters with 1320 individual tap sets.
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Arrigo, Adriano, Christos Ordoudis, Jalal Kazempour, Zacharie de Greve, Jean-Francois Toubeau, and Francois Vallee. "Optimal Power Flow Under Uncertainty: An Extensive Out-of-Sample Analysis." In 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe). IEEE, 2019. http://dx.doi.org/10.1109/isgteurope.2019.8905752.

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Cloud, David, and Ethan Stearns. "Probabilistic Analysis of a Turbofan Secondary Flow System." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53197.

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This paper documents a probabilistic analysis of the secondary flow system in a modern commercial turbofan engine. The purpose of this analysis is to investigate the variability in the high and low rotor bearing loads and total secondary flow due to the inherent uncertainty in manufacturing processes and engine performance. In addition to quantifying the variability in bearing load and secondary flow, the sensitivity of the parameters to individual input variables is determined. The system was found to behave linearly, resulting in negligible mean shifts due to input variation. The importance of correlation among the performance parameters will be addressed, as well as the effects of different correlations. Methods used to reduce the time required for the analysis will also be discussed. This type of analysis has many applications in cost reduction, engine design, optimization, and root cause analysis that will be covered in this paper.
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Wakeland, Richard. "Long Radius Flow Nozzle Study." In ASME 2009 Power Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/power2009-81053.

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The objective of this study is to examine the American Society of Mechanical Engineers (ASME) Long Radius Flow Nozzle. This study was conducted with regard to published standards for design and installation, manufacturing, and the comparative analysis of laboratory flow calibrations to the theoretical predictions of the coefficient of discharge. Several sets of identically designed Long Radius Flow Nozzles were manufactured and laboratory flow calibrated. The results of the flow calibration data were used to evaluate the accuracy of the prediction equations for the Coefficient of Discharge and to determine the effects of materials and manufacturing processes such as post weld stress relieving. Preliminary results of continuing research indicate that the uncertainty of the coefficient of discharge may be 1% or less while the published uncertainty is 2%. These results indicate that well controlled design and manufacturing processes influence the flow nozzle performance. These results are based on flow calibration data from an independent laboratory. In conclusion, the long radius flow nozzle can be designed and manufactured so the uncertainty associated with the coefficient of discharge is less than published values. Further study is required of the published equations for predicting the coefficient of discharge.
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Dhabai, Poonam, and Neeraj Tiwari. "Analysis of Variation in Power Flows due to Uncertain Solar Farm Power Output and its Location in Network." In 2020 IEEE International Conference for Innovation in Technology (INOCON). IEEE, 2020. http://dx.doi.org/10.1109/inocon50539.2020.9298308.

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Henry, Ray E., Robert Jorgensen, and Philip M. Gerhart. "Uncertainty Analysis in Fan Testing." In ASME 2007 Power Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/power2007-22099.

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The ASME performance test codes require an uncertainty analysis as part of a code test, and some codes require both a pre-test and a post-test uncertainty analysis. ASME PTC-19.1, Test Uncertainty provides the basic approach to conducting an uncertainty analysis. The individual test codes, such as ASME PTC-11, Fans, provide specific guidance for uncertainty analysis of tests of particular equipment or processes. The following issues related to an uncertainty analysis for a PTC-11 fan test are discussed. • Evaluating uncertainties for traverse measurements — Fan testing requires one or more traverses to measure flow rate as well as various pressures, temperatures, and gas composition. Evaluating and propagating the uncertainty associated with traverse point measurements to obtain overall uncertainty is explained. • Evaluating uncertainties for non-traverse measurements — Fan testing also requires the measurement of power input, fan speed, and atmospheric temperature and pressure. Evaluating the uncertainties in these quantities is discussed. • Propagating uncertainties of the measurements into the final results — An analytical method is compared to “dithering” to obtain a sensitivity factor. • Using a pre-test uncertainty analysis to optimize the test design — Examples are provided on how a pre-test uncertainty analysis can be used to reduce the uncertainties of a fan test. The results include results of sample pre-test and post-test uncertainty analyses for fans.
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Reports on the topic "Uncertain power flow analysis"

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Sorooshian, Kianfar. Load flow and contingency analysis in power systems. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.3310.

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Cuschieri, J. M. Mobility Power Flow Analysis of a Thick Plate Structure. Fort Belvoir, VA: Defense Technical Information Center, January 1990. http://dx.doi.org/10.21236/ada279431.

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Broderick, Robert Joseph, Jimmy Edward Quiroz, Abraham Ellis, Matthew J. Reno, Jeff Smith, and Roger Dugan. Time series power flow analysis for distribution connected PV generation. Office of Scientific and Technical Information (OSTI), January 2013. http://dx.doi.org/10.2172/1088099.

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McCraney, Joshua. Analysis of Capillary Flow in Interior Corners : Perturbed Power Law Similarity Solutions. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2721.

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