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Journal articles on the topic 'Power-flow solution'

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Author: Grafiati

Published: 14 March 2023

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1

Shi, Libao, Chen Wang, Liangzhong Yao, Yixin Ni, and Masoud Bazargan. "Optimal Power Flow Solution Incorporating Wind Power." IEEE Systems Journal 6, no. 2 (June 2012): 233–41. http://dx.doi.org/10.1109/jsyst.2011.2162896.

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2

Oh, HyungSeon. "Distributed optimal power flow." PLOS ONE 16, no. 6 (June 18, 2021): e0251948. http://dx.doi.org/10.1371/journal.pone.0251948.

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Objective The objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior solution can be found, and 3) develop a scalable algorithm that guarantees the convergence to a local minimum. Existing challenges Due to the nonconvexity of the problem, the search for a solution to OPF problems is not scalable, which makes the OPF highly limited for the system operation of large-scale real-world power grids—“the curse of dimensionality”. The recent attempts at distributed computation aim for a scalable and efficient algorithm by reducing the computational cost per iteration in exchange of increased communication costs. Motivation A new network model allows for efficient computation without increasing communication costs. With the network model, recent advancements in distributed computation make it possible to develop an efficient and scalable algorithm suitable for large-scale OPF optimizations. Methods We propose a new network model in which all nodes are directly connected to the center node to keep the communication costs manageable. Based on the network model, we suggest a nodal distributed algorithm and direct communication to all nodes through the center node. We demonstrate that the suggested algorithm converges to a local minimum rather than a point, satisfying the first optimality condition. Results The proposed algorithm identifies solutions to OPF problems in various IEEE model systems. The solutions are identical to those using a centrally optimized and heuristic approach. The computation time at each node does not depend on the system size, and Niter does not increase significantly with the system size. Conclusion Our proposed network model is a star network for maintaining the shortest node-to-node distances to allow a linear information exchange. The proposed algorithm guarantees the convergence to a local minimum rather than a maximum or a saddle point, and it maintains computational efficiency for a large-scale OPF, scalable algorithm.

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3

Pires, Robson, G. Chagas, and Lamine Mili. "Enhanced power flow solution in complex plane." International Journal of Electrical Power & Energy Systems 135 (February 2022): 107501. http://dx.doi.org/10.1016/j.ijepes.2021.107501.

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4

Hiskens, I. A., and R. J. Davy. "Exploring the Power Flow Solution Space Boundary." IEEE Power Engineering Review 21, no. 8 (August 2001): 57. http://dx.doi.org/10.1109/mper.2001.4311544.

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5

Rehman, Bilawal, and Chongru Liu. "AC/DC multi-infeed power flow solution." IET Generation, Transmission & Distribution 13, no. 10 (May 21, 2019): 1838–44. http://dx.doi.org/10.1049/iet-gtd.2018.6781.

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6

Wang, Lu, Niande Xiang, Shiying Wang, and Mei Huang. "Parallel reduced gradient optimal power flow solution." Electric Power Systems Research 17, no. 3 (November 1989): 229–37. http://dx.doi.org/10.1016/0378-7796(89)90025-4.

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7

Hiskens, I. A., and R. J. Davy. "Exploring the power flow solution space boundary." IEEE Transactions on Power Systems 16, no. 3 (2001): 389–95. http://dx.doi.org/10.1109/59.932273.

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8

Jovanović, S. M., and B. S. Babić. "Decoupled and decomposed power flow solution method." International Journal of Electrical Power & Energy Systems 9, no. 2 (April 1987): 117–21. http://dx.doi.org/10.1016/0142-0615(87)90033-0.

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9

Kulworawanichpong, Thanatchai. "Simplified Newton–Raphson power-flow solution method." International Journal of Electrical Power & Energy Systems 32, no. 6 (July 2010): 551–58. http://dx.doi.org/10.1016/j.ijepes.2009.11.011.

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10

Weng, Zhenxing, Libao Shi, Zheng Xu, Qiang Lu, Liangzhong Yao, and Yixin Ni. "Fuzzy power flow solution considering wind power variability and uncertainty." International Transactions on Electrical Energy Systems 25, no. 3 (January 14, 2014): 547–72. http://dx.doi.org/10.1002/etep.1871.

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11

Van Dai, Le, Ngo Minh Khoa, and Le Cao Quyen. "An Innovatory Method Based on Continuation Power Flow to Analyze Power System Voltage Stability with Distributed Generation Penetration." Complexity 2020 (September 7, 2020): 1–15. http://dx.doi.org/10.1155/2020/8037837.

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With the penetration of distributed generation (DG) units, the power systems will face insecurity problems and voltage stability issues. This paper proposes an innovatory method by modifying the conventional continuation power flow (CCPF) method. The proposed method is realized on two prediction and correction steps to find successive load flow solutions according to a specific load scenario. Firstly, the tangent predictor is proposed to estimate the next predicted solution from two previous corrected solutions. And then, the corrector step is proposed to determine the next corrected solution on the exact solution. This corrected solution is constrained to lie in the hyperplane running through the predicted solution orthogonal to the line from the two previous corrected solutions. Besides, once the convergence criterion is reached, the procedure for cutting the step length control down to a smaller one is proposed to be implemented. The effectiveness of the proposed method is verified via numerical simulations on three standard test systems, namely, IEEE 14-bus, 57-bus, and 118-bus, and compared to the CCPF method.

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12

Liu-Lin, Yang, Hang Nai-Shan, and Liu Bai-Jiang. "A Modular Approach to Power Flow Regulation Solution." Open Electrical & Electronic Engineering Journal 9, no. 1 (March 18, 2015): 91–98. http://dx.doi.org/10.2174/1874129001509010091.

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The operating modes of generations and the voltage states of power system must be solved when calculating and analyzing the power flow problem with operation demands. The generation variable differential were derived as well as the complete principle of variable differential analysis was formed, based on the model of expanded power flow with constraints, by using the implicit function differential method, the linear composing relation between the voltage variable differential and the expanded correction equations which included the equations of PQV node and branch power, solutions were also proposed. This new solving method is not featured in minimum variables however it is featured as a one-time simultaneous solution. Through the IEEE 5 bus system, the analyzing cases of total differential sensitivity and operation under conditions of constant line power and constant node voltage were carried out, these cases described the fact that the mixed variable solving method of power flow regulation has a simple form, small calculation volume and efficiency.

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13

Terasawa, Yoshinori, and Shinichi Iwamoto. "Optimal power flow solution using fuzzy mathematical programming." IEEJ Transactions on Power and Energy 108, no. 5 (1988): 197–204. http://dx.doi.org/10.1541/ieejpes1972.108.197.

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14

Ahmed Nasser B. Alsammak, Dr. "Optimal Power Flow Solution with Maximum Voltage Stability." AL-Rafdain Engineering Journal (AREJ) 19, no. 6 (December 28, 2011): 40–53. http://dx.doi.org/10.33899/rengj.2011.26606.

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15

Ji, Zhen Yi, Wen Yuan Wu, Yi Li, and Yong Feng. "Computing the Singular Solution of Power Flow System." Applied Mechanics and Materials 392 (September 2013): 660–64. http://dx.doi.org/10.4028/www.scientific.net/amm.392.660.

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The purpose of this paper is to compute the singular solution of the nonlinear equations arising in power flow system. Based on the approximate null space of the Jacobian matrix, more equations are introduced to the origin system. Meanwhile, the Jacobian matrix of augmented equations at initial value is full rank, then the algorithm recovers quadratic convergence of Newtons iteration. The algorithm in this paper leads to higher accuracy of the singular solution and less iteration steps. In addition, two power flow systems are studied in this paper and the results show this new method has high accuracy and efficiency compared with traditional Newton iteration

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16

Alves, D. A., and G. R. M. da Costa. "An analytical solution to the optimal power flow." IEEE Power Engineering Review 22, no. 3 (March 2002): 49–51. http://dx.doi.org/10.1109/mper.2002.989195.

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17

Idema, Reijer, Georgios Papaefthymiou, Domenico Lahaye, Cornelis Vuik, and Lou van der Sluis. "Towards Faster Solution of Large Power Flow Problems." IEEE Transactions on Power Systems 28, no. 4 (November 2013): 4918–25. http://dx.doi.org/10.1109/tpwrs.2013.2252631.

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18

Pablo Oñate, Y., Juan M. Ramirez, and Carlos A. Coello Coello. "An optimal power flow plus transmission costs solution." Electric Power Systems Research 79, no. 8 (August 2009): 1240–46. http://dx.doi.org/10.1016/j.epsr.2009.03.005.

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19

Terasawa, Yoshinori, and Shinichi Iwamoto. "Optimal power flow solution using fuzzy mathematical programming." Electrical Engineering in Japan 108, no. 3 (1988): 46–54. http://dx.doi.org/10.1002/eej.4391080306.

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20

Guo, Xiaoxuan, Haibo Bao, Jing Xiao, and Shaonan Chen. "A Solution of Interval Power Flow Considering Correlation of Wind Power." IEEE Access 9 (2021): 78915–24. http://dx.doi.org/10.1109/access.2021.3051745.

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21

Li, Zelan, Yijia Cao, Le Van Dai, Xiaoliang Yang, and Thang Trung Nguyen. "Optimal Power Flow for Transmission Power Networks Using a Novel Metaheuristic Algorithm." Energies 12, no. 22 (November 12, 2019): 4310. http://dx.doi.org/10.3390/en12224310.

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In the paper, a modified coyote optimization algorithm (MCOA) is proposed for finding highly effective solutions for the optimal power flow (OPF) problem. In the OPF problem, total active power losses in all transmission lines and total electric generation cost of all available thermal units are considered to be reduced as much as possible meanwhile all constraints of transmission power systems such as generation and voltage limits of generators, generation limits of capacitors, secondary voltage limits of transformers, and limit of transmission lines are required to be exactly satisfied. MCOA is an improved version of the original coyote optimization algorithm (OCOA) with two modifications in two new solution generation techniques and one modification in the solution exchange technique. As compared to OCOA, the proposed MCOA has high contributions as follows: (i) finding more promising optimal solutions with a faster manner, (ii) shortening computation steps, and (iii) reaching higher success rate. Three IEEE transmission power networks are used for comparing MCOA with OCOA and other existing conventional methods, improved versions of these conventional methods, and hybrid methods. About the constraint handling ability, the success rate of MCOA is, respectively, 100%, 96%, and 52% meanwhile those of OCOA is, respectively, 88%, 74%, and 16%. About the obtained solutions, the improvement level of MCOA over OCOA can be up to 30.21% whereas the improvement level over other existing methods is up to 43.88%. Furthermore, these two methods are also executed for determining the best location of a photovoltaic system (PVS) with rated power of 2.0 MW in an IEEE 30-bus system. As a result, MCOA can reduce fuel cost and power loss by 0.5% and 24.36%. Therefore, MCOA can be recommended to be a powerful method for optimal power flow study on transmission power networks with considering the presence of renewable energies.

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22

Warid, Warid. "A Novel Chaotic Rao-2 Algorithm for Optimal Power Flow Solution." Journal of Electrical and Computer Engineering 2022 (November 4, 2022): 1–19. http://dx.doi.org/10.1155/2022/7694026.

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This article suggests a novel chaotic Rao-2 algorithm to solve various optimal power flow (OPF) problems. The basic Rao-2 solver is a newly developed metaphor-less optimization tool. The novel optimization course of the basic Rao-2 algorithm relies on the finest and inferior solutions within the population and the indiscriminate interrelations among the nominee individuals. This tactic allows superior directions to scrutinize the exploration space. In this work, a novel chaotic Rao-2 algorithm-inspired scheme for handling the OPF problem is offered. In the offered solver, a chaotic tactic is amalgamated into the movement formula of the basic Rao-2 algorithm to enhance the variety of solutions and enhance both its global and local search capabilities. This novel scheme, which incorporates the features of the basic Rao-2 algorithm and chaotic dynamics, is then utilized to solve various OPF problems. For the OPF solution, five situations are investigated. The offered solver is examined on two standard IEEE test grids and the emulation outcomes are evaluated with the outcomes offered in the other publications and deemed competitive in terms of the features of the solution. The offered chaotic Rao-2 algorithm outperforms the basic Rao-2 algorithm regarding convergence velocity and solution competence. Furthermore, a test is performed to validate the statistical worth of the offered chaotic Rao-2-inspired solver. The offered chaotic Rao-2 algorithm presents a vigorous and simple solution for the OPF framework under various objectives.

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23

Singh, Pradeep, and Rajive Tiwari. "Amalgam Power Flow Controller: A Novel Flexible, Reliable, and Cost-Effective Solution to Control Power Flow." IEEE Transactions on Power Systems 33, no. 3 (May 2018): 2842–53. http://dx.doi.org/10.1109/tpwrs.2017.2764954.

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24

Et. al., Ranjani Senthilkumara,. "Solution for Optimal Power Flow Problem Using WDO Algorithm." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 889–95. http://dx.doi.org/10.17762/turcomat.v12i2.1097.

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Wind driven optimization (WDO) algorithm is a best optimization method based on atmospherically motion, global optimization nature inspired method. The method is based on population iterative analytical global optimization for multifaceted and multi prototype in the search domain for constraints to implement. In this paper, WDO algorithm is accustomed to find optimal power flow solution. To find the efficacy of the technique, it is applied to IEEE 30 bus systems to find fuel cost for generation of power as a main objective. Obtained results were compared with other techniques shows the better solution for optimal power flow problem.

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25

Ge, Ting You, and Yang Jiang. "Analysis on Control Solution of Interline Power Flow Controller." Materials Science Forum 861 (July 2016): 299–301. http://dx.doi.org/10.4028/www.scientific.net/msf.861.299.

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Interline power flow controller is the control device of FACTS (Flexible AC Transmission Systems) which can adjust trend, enhance stability, improve power grid transmission, etc. Through the analysis of the structure of IPFC, this paper demonstrates that fuzzy control method is an advanced and reasonable control method, which can be independently control bus voltage and the active and reactive power current on a line in the power system.

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26

Ren, Ping, and Nan Li. "Optimal Power Flow Solution Using the Harmony Search Algorithm." Applied Mechanics and Materials 599-601 (August 2014): 1938–41. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1938.

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Inthis paper, the nonlinear optimal control problem is formulated as amulti-objective mathematical optimization problem. Harmony search (HS)algorithm is one of the new heuristic algorithms. The harmony search(HS) optimization algorithm is introduced forthe first time in solving the optimal power flow(OPF) solution. A case onoptimal power flow problem in the IEEE 30 bus system is presented to show themethodology’s feasibility and efficiency, compared with the existing optimalpower flow problem in power system methods, the search time of the HSoptimization algorithm is shorter and the result is close to the idealsolution, simultaneously.

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27

Home-Ortiz, Juan M., Wmerson Claro De Oliveira, and Jose Roberto Sanches Mantovani. "Optimal Power Flow Problem Solution Through a Matheuristic Approach." IEEE Access 9 (2021): 84576–87. http://dx.doi.org/10.1109/access.2021.3087626.

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28

Khamees, Amr K., Ahmed El-Rafei, N. M. Badra, and Almoataz Y. Abdelaziz. "Solution of optimal power flow using evolutionary-based algorithms." International Journal of Engineering, Science and Technology 9, no. 1 (April 10, 2017): 55. http://dx.doi.org/10.4314/ijest.v9i1.5.

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29

Afsari, M., S. P. Singh, G. S. Raju, and G. K. Rao. "A Fast Power Flow Solution of Radial Distribution Networks." Electric Power Components and Systems 30, no. 10 (October 2002): 1065–74. http://dx.doi.org/10.1080/15325000290085361.

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30

Kaur, Mandeep, and Nitin Narang. "An integrated optimization technique for optimal power flow solution." Soft Computing 24, no. 14 (December 11, 2019): 10865–82. http://dx.doi.org/10.1007/s00500-019-04590-3.

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31

Sinsuphan, Nampetch, Uthen Leeton, and Thanatchai Kulworawanichpong. "Optimal power flow solution using improved harmony search method." Applied Soft Computing 13, no. 5 (May 2013): 2364–74. http://dx.doi.org/10.1016/j.asoc.2013.01.024.

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32

Sadasivam, G., and M. Abdullah Khan. "A fast method for optimal reactive power flow solution." International Journal of Electrical Power & Energy Systems 12, no. 1 (January 1990): 65–68. http://dx.doi.org/10.1016/0142-0615(90)90023-5.

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33

Taher, Mahrous A., Salah Kamel, Francisco Jurado, and Mohamed Ebeed. "Modified grasshopper optimization framework for optimal power flow solution." Electrical Engineering 101, no. 1 (March 20, 2019): 121–48. http://dx.doi.org/10.1007/s00202-019-00762-4.

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34

Benato, R., A. Paolucci, and R. Turri. "Power flow solution by a complex admittance matrix method." European Transactions on Electrical Power 11, no. 3 (May 2001): 181–88. http://dx.doi.org/10.1002/etep.4450110305.

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35

Jia, Jun, Xuan Li, and Ping Ping Han. "The Convergence Analysis of Parsing Algorithm in Power Flow." Advanced Materials Research 588-589 (November 2012): 547–51. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.547.

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Power flow solution is one of the most important means of power system stability analysis. While parsing algorithm is the basis of power flow analysis. The idea of iteration is frequently used in power flow solution because of the characteristics of power system itself. Textbooks, however, use the gradual iterative thought without rigorous demonstration of the conditions for convergence. From the point of view of mathematical analysis, the article not only gives a proper way to determine the convergence or divergence of the power flow but also provide the exact solution of a simple power flow with an example to demonstrate the validity of the algorithm.

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36

Ali, Mahmoud A., Salah Kamel, Mohamed H. Hassan, Emad M. Ahmed, and Mohana Alanazi. "Optimal Power Flow Solution of Power Systems with Renewable Energy Sources Using White Sharks Algorithm." Sustainability 14, no. 10 (May 16, 2022): 6049. http://dx.doi.org/10.3390/su14106049.

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Modern electrical power systems are becoming increasingly complex and are expanding at an accelerating pace. The power system’s transmission lines are under more strain than ever before. As a result, the power system is experiencing a wide range of issues, including rising power losses, voltage instability, line overloads, and so on. Losses can be minimized and the voltage profile can be improved when energy resources are installed on appropriate buses to optimize real and reactive power. This is especially true in densely congested networks. Optimal power flow (OPF) is a basic tool for the secure and economic operation of power systems. It is a mathematical tool used to find the instantaneous optimal operation of a power system under constraints meeting operation feasibility and security. In this study, a new application algorithm named white shark optimizer (WSO) is proposed to solve the optimal power flow (OPF) problems based on a single objective and considering the minimization of the generation cost. The WSO is used to find the optimal solution for an upgraded power system that includes both traditional thermal power units (TPG) and renewable energy units, including wind (WPG) and solar photovoltaic generators (SPG). Although renewable energy sources such as wind and solar energy represent environmentally friendly sources in line with the United Nations sustainable development goals (UN SDG), they appear as a major challenge for power flow systems due to the problems of discontinuous energy production. For overcoming this problem, probability density functions of Weibull and Lognormal (PDF) have been used to aid in forecasting uncertain output powers from WPG and SPG, respectively. Testing on modified IEEE-30 buses’ systems is used to evaluate the proposed method’s performance. The results of the suggested WSO algorithm are compared to the results of the Northern Goshawk Optimizer (NGO) and two other optimization methods to investigate its effectiveness. The simulation results reveal that WSO is more effective at finding the best solution to the OPF problem when considering total power cost minimization and solution convergence. Moreover, the results of the proposed technique are compared to the other existing method described in the literature, with the results indicating that the suggested method can find better optimal solutions, employ less generated solutions, and save computation time.

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37

Chen, Yi-Rui, Liang-Hsun Chen, Kuo-Lun Tung, Yu-Ling Li, Yu-Shao Chen, Che-Chia Hu, and Ching-Jung Chuang. "Semianalytical solution for power-law polymer solution flow in a converging annular spinneret." AIChE Journal 61, no. 10 (May 25, 2015): 3489–99. http://dx.doi.org/10.1002/aic.14875.

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38

Pareek, Parikshit, and Hung D. Nguyen. "State-Aware Stochastic Optimal Power Flow." Sustainability 13, no. 14 (July 7, 2021): 7577. http://dx.doi.org/10.3390/su13147577.

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The increase in distributed generation (DG) and variable load mandates system operators to perform decision-making considering uncertainties. This paper introduces a novel state-aware stochastic optimal power flow (SA-SOPF) problem formulation. The proposed SA-SOPF has objective to find a day-ahead base-solution that minimizes the generation cost and expectation of deviations in generation and node voltage set-points during real-time operation. We formulate SA-SOPF for a given affine policy and employ Gaussian process learning to obtain a distributionally robust (DR) affine policy for generation and voltage set-point change in real-time. In simulations, the GP-based affine policy has shown distributional robustness over three different uncertainty distributions for IEEE 14-bus system. The results also depict that the proposed SA-OPF formulation can reduce the expectation in voltage and generation deviation more than 60% in real-time operation with an additional day-ahead scheduling cost of 4.68% only for 14-bus system. For, in a 30-bus system, the reduction in generation and voltage deviation, the expectation is achieved to be greater than 90% for 1.195% extra generation cost. These results are strong indicators of possibility of achieving the day-ahead solution which lead to lower real-time deviation with minimal cost increase.

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39

Khamees, Amr Khaled, Almoataz Y. Abdelaziz, Makram R. Eskaros, Adel El-Shahat, and Mahmoud A. Attia. "Optimal Power Flow Solution of Wind-Integrated Power System Using Novel Metaheuristic Method." Energies 14, no. 19 (September 26, 2021): 6117. http://dx.doi.org/10.3390/en14196117.

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Wind energy is particularly significant in the power system today since it is a cheap and clean power source. The unpredictability of wind speed leads to uncertainty in devolved power which increases the difficulty in wind energy system operation. This paper presents a stochastic optimal power flow (SCOPF) for obtaining the best scheduled power from wind farms while lowering total operational costs. A novel metaheuristics method called Aquila Optimizer (AO) is used to address the SCOPF problem due to its highly nonconvex and nonlinear nature. Wind speed is represented by the Weibull probability distribution function (PDF), which is used to anticipate the cost of wind-generated power from a wind farm based on scheduled power. Weibull parameters that provide the best match to wind data are estimated using the AO approach. The suggested wind generation cost model includes the opportunity costs of wind power underestimation and overestimation. Three IEEE systems (30, 57, and 118) are utilized to solve optimal power flow (OPF) using the AO method to prove the accuracy of this method, and results are compared with other metaheuristic methods. With six scenarios for the penalty and reverse cost coefficients, SCOPF is applied to a modified IEEE-30 bus system with two wind farms to obtain the optimal scheduled power from the two wind farms which reduces total operation cost.

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40

El-Arini, M. M. M. "Decoupled power flow solution method for well-conditioned and ill-conditioned power systems." IEE Proceedings C Generation, Transmission and Distribution 140, no. 1 (1993): 7. http://dx.doi.org/10.1049/ip-c.1993.0002.

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41

Luo, Jinqing, Libao Shi, and Yixin Ni. "A Solution of Optimal Power Flow Incorporating Wind Generation and Power Grid Uncertainties." IEEE Access 6 (2018): 19681–90. http://dx.doi.org/10.1109/access.2018.2823982.

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42

Attia, Abdel-Fattah, Ragab A. El Sehiemy, and Hany M. Hasanien. "Optimal power flow solution in power systems using a novel Sine-Cosine algorithm." International Journal of Electrical Power & Energy Systems 99 (July 2018): 331–43. http://dx.doi.org/10.1016/j.ijepes.2018.01.024.

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43

Popovic, Dragan. "Initialization of steady-state security analyses of electric power interconnections." Facta universitatis - series: Electronics and Energetics 23, no. 1 (2010): 119–38. http://dx.doi.org/10.2298/fuee1001119p.

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The basic objective of this paper is to present the relevant methodological and practical aspects of two efficient procedures for initialization of steady-state security analyses of electric power interconnection. The first procedure gives the load flow solution for known initial generators scheduling and the second one gives the load-flow solution in conditions of bilateral or multilateral exchange programs realization. Those procedures are fully consistent with the specially developed procedure for steady-state security analysis, which is based on successive solutions of load-flow in characteristic post-dynamic quasi-stationary states, occurring after the considered disturbances. The efficiency of proposed procedures is demonstrated on the example of real electric power interconnection in the Balkan area. .

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44

Kerswell, R. R., and A. M. Soward. "Upper bounds for turbulent Couette flow incorporating the poloidal power constraint." Journal of Fluid Mechanics 328 (December 10, 1996): 161–76. http://dx.doi.org/10.1017/s0022112096008683.

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The upper bound on momentum transport in the turbulent regime of plane Couette flow is considered. Busse (1970) obtained a bound from a variational formulation based on total energy conservation and the mean momentum equation. Two-dimensional asymptotic solutions of the resulting Euler-Lagrange equations for the system were obtained in the large-Reynolds-number limit. Here we make a toroidal poloidal decomposition of the flow and impose an additional power integral constraint, which cannot be satisfied by two-dimensional flows. Nevertheless, we show that the additional constraint can be met by only small modifications to Busse's solution, which leaves his momentum transport bound unaltered at lowest order. On the one hand, the result suggests that the addition of further integral constraints will not significantly improve bound estimates. On the other, our optimal solution, which possesses a weak spanwise roll in the outermost of Busse's nested boundary layers, appears to explain the three-dimensional structures observed in experiments. Only in the outermost boundary layer and in the main stream is the solution three-dimensional. Motion in the thinner layers remains two-dimensional characterized by streamwise rolls.

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45

Genesi, Camillo, and Mario Montagna. "Adjusted reactive solutions for multiple power flow computations." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 33, no. 1/2 (December 20, 2013): 581–93. http://dx.doi.org/10.1108/compel-03-2013-0093.

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Purpose – The purpose of this work is that of showing some efficient techniques to perform PV-PQ node type switching in multiple power flow computations. Design/methodology/approach – Reactive generation limits of generation buses must be taken into account to obtain realistic power flow solutions. This may result computationally demanding when many power flow computations are required as in contingency screening or Monte Carlo simulations. In the present paper, the implementation of efficient PV-PQ node type switching is examined with particular emphasis on the efficiency of computation. Some different methods are proposed and compared on the basis of computation speed and accuracy. Findings – Tests show the efficiency of the proposed methods with reference to actual networks with up to 800 buses. Originality/value – The classical method of (partial) re-factorisation is not very efficient when many power flow solutions are to be evaluated. In the present work, a different approach is proposed; it is based on grounding each PV node by a fictitious short-circuit branch which is removed when the node type is changed to PQ. This operation is carried out by compensation of the solution and combined with the modifications required for contingency simulation.

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Bogobowicz, A., L. Rothenburg, and M. B. Dusseault. "Solutions for Non-Newtonian Flow Into Elliptical Openings." Journal of Applied Mechanics 58, no. 3 (September 1, 1991): 820–24. http://dx.doi.org/10.1115/1.2897268.

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A semi-analytical solution for plane velocity fields describing steady-state incompressible flow of nonlinearly viscous fluid into an elliptical opening is presented. The flow is driven by hydrostatic pressure applied at infinity. The solution is obtained by minimizing the rate of energy dissipation on a sufficiently flexible incompressible velocity field in elliptical coordinates. The medium is described by a power creep law and solutions are obtained for a range of exponents and ellipse eccentricites. The obtained solutions compare favorably with results of finite element analysis.

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ALLAOUA, B., and A. LAOUFI. "Optimal Power Flow Solution Using Ant Manners for Electrical Network." Advances in Electrical and Computer Engineering 9, no. 1 (2009): 34–40. http://dx.doi.org/10.4316/aece.2009.01006.

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Messaoudi, Abdelmoumene, and Mohamed Belkacemi. "Optimal Power Flow Solution using Efficient Sine Cosine Optimization Algorithm." International Journal of Intelligent Systems and Applications 12, no. 2 (April 8, 2020): 34–43. http://dx.doi.org/10.5815/ijisa.2020.02.04.

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KumarEaswaramoorthy, Nanda, and R. Dhanasekaran. "Solution of Optimal Power Flow Problem Incorporating Various FACTS Devices." International Journal of Computer Applications 55, no. 4 (October 20, 2012): 38–44. http://dx.doi.org/10.5120/8746-2633.

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Ranjan, R., B. Venkatesh, A. Chaturvedi, and D. Das. "Power Flow Solution of Three-Phase Unbalanced Radial Distribution Network." Electric Power Components and Systems 32, no. 4 (April 2004): 1. http://dx.doi.org/10.1080/759369252.

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