A new method based on chaotic neural networks for the optimal allocation of reactive power sources

2006 ◽  
Author(s):  
Xiaolei Du ◽  
Tiecheng Lu
Keyword(s):  
Neural Networks ◽  
Optimal Allocation ◽  
Reactive Power ◽  
New Method ◽  
Power Sources ◽  
Chaotic Neural Networks

Implementation of Population Algorithms to Minimize Power Losses and Cable Cross-Section in Power Supply System

2016 ◽  
Vol 6 (6) ◽  
pp. 2955 ◽  
Author(s):  
V. Z. Manusov ◽  
P. V. Matrenin ◽  
E. S. Tretiakova
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
Capital Investment ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Active Power ◽  
Power Losses ◽  
Power Sources ◽  
First Case ◽  
Active Power Losses

<p><span lang="EN-US">The article dues to the arrangement of the reactive power sources in the power grid to reduce the active power losses in transmission lines and minimize cable cross-sections of the lines. The optimal arrangement is considered from two points of view. In the first case, it is possible to minimize the active power losses only. In the second case, it is possible to change the cross-sections of the supply lines to minimize both the active power losses and the volume of the cable lines. The sum of the financial cost of the active power losses, the capital investment to install the deep reactive power compensation, and cost of the cable volume is introduced as the single optimization criterion. To reduce the losses, the deep compensation of reactive power sources in nodes of the grid are proposed. This optimization problem was solved by the Genetic algorithm and the Particle Swarm optimization algorithm. It was found out that the deep compensation allows minimizing active power losses the cable cross-section. The cost-effectiveness of the suggested method is shown. It was found out that optimal allocation of the reactive power sources allows increasing from 9% to 20% the financial expenses for the enterprise considered.</span></p>

scholarly journals Implementation of Population Algorithms to Minimize Power Losses and Cable Cross-Section in Power Supply System

2016 ◽  
Vol 6 (6) ◽  
pp. 2955
Author(s):  
V. Z. Manusov ◽  
P. V. Matrenin ◽  
E. S. Tretiakova
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
Capital Investment ◽  
Optimal Allocation ◽  
Reactive Power ◽  
Active Power ◽  
Power Losses ◽  
Power Sources ◽  
First Case ◽  
Active Power Losses

<p><span lang="EN-US">The article dues to the arrangement of the reactive power sources in the power grid to reduce the active power losses in transmission lines and minimize cable cross-sections of the lines. The optimal arrangement is considered from two points of view. In the first case, it is possible to minimize the active power losses only. In the second case, it is possible to change the cross-sections of the supply lines to minimize both the active power losses and the volume of the cable lines. The sum of the financial cost of the active power losses, the capital investment to install the deep reactive power compensation, and cost of the cable volume is introduced as the single optimization criterion. To reduce the losses, the deep compensation of reactive power sources in nodes of the grid are proposed. This optimization problem was solved by the Genetic algorithm and the Particle Swarm optimization algorithm. It was found out that the deep compensation allows minimizing active power losses the cable cross-section. The cost-effectiveness of the suggested method is shown. It was found out that optimal allocation of the reactive power sources allows increasing from 9% to 20% the financial expenses for the enterprise considered.</span></p>

scholarly journals Inequalities and pth moment exponential stability of impulsive delayed Hopfield neural networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yutian Zhang ◽  
Guici Chen ◽  
Qi Luo
Keyword(s):  
Neural Networks ◽  
Lyapunov Function ◽  
Exponential Stability ◽  
Hopfield Neural Networks ◽  
New Method ◽  
Integral Inequalities ◽  
Delay Function ◽  
Pth Moment Exponential Stability ◽  
Moment Exponential Stability

AbstractIn this paper, the pth moment exponential stability for a class of impulsive delayed Hopfield neural networks is investigated. Some concise algebraic criteria are provided by a new method concerned with impulsive integral inequalities. Our discussion neither requires a complicated Lyapunov function nor the differentiability of the delay function. In addition, we also summarize a new result on the exponential stability of a class of impulsive integral inequalities. Finally, one example is given to illustrate the effectiveness of the obtained results.

scholarly journals Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jinde Cao ◽  
Abdulaziz Alofi ◽  
Abdullah Al-Mazrooei ◽  
Ahmed Elaiw
Keyword(s):  
Neural Networks ◽  
Matrix Measure ◽  
Chaotic Neural Networks ◽  
Time Varying Delay ◽  
Synchronization Problem ◽  
Arbitrary Switching ◽  
Parameters Uncertainty ◽  
Inequality Technique ◽  
Error System ◽  
Switched Interval Networks

This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchronization criteria are derived for switched interval networks under the arbitrary switching rule, which are easy to verify in practice. Moreover, as an application, the proposed scheme is then applied to chaotic neural networks. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.

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