Unbalanced Radial Distribution Systems Voltage Stability Index Using Extreme Learning Machine

2016 ◽  
Vol 11 (4) ◽  
pp. 428
Author(s):  
Dimas Fajar Uman Putra ◽  
Ontoseno Penangsang ◽  
Adi Soeprijanto ◽  
Hajime Miyauchi
Keyword(s):  
Extreme Learning Machine ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Stability Index ◽  
Voltage Stability Index ◽  
Learning Machine

Voltage Stability Index of Radial Distribution Networks by Considering Distributed Generator for Different Types of Loads

2016 ◽  
Vol 5 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Tapan Kumar Chattopadhyay ◽  
Sumit Banerjee ◽  
Chandan Kumar Chanda
Keyword(s):  
Stability Analysis ◽  
Radial Distribution ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Stability Index ◽  
Distribution Networks ◽  
Voltage Collapse ◽  
Distributed Generator ◽  
Voltage Stability Index ◽  
Different Types

The paper presents an approach on voltage stability analysis of distribution networks for loads of different types. A voltage stability index is proposed for identifying the node, which is most sensitive to voltage collapse. It is shown that the node, at which the value of voltage stability index is maximum, is more sensitive to voltage collapse. For the purpose of voltage stability analysis, constant power, constant current, constant impedance and composite load modeling are considered. Distributed generation can be integrated into distribution systems to meet the increasing load demand. It is seen that with the insertion of distributed generator (DG), load capability limit of the feeder has increased for all types of loads. By using this voltage stability index, one can measure the level of voltage stability of radial distribution systems and thereby appropriate action may be taken if the index indicates a poor level of stability. The effectiveness of the proposed method is demonstrated through two examples.

Optimization of Real Power Loss and Voltage Stability Index for Distribution Systems with Distributed Generation

2017 ◽  
Vol 33 ◽  
pp. 100-114 ◽  
Author(s):  
Mostafa Elshahed ◽  
Mahmoud Dawod ◽  
Zeinab H. Osman
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Reactive Power ◽  
Optimization Problems ◽  
Stability Index ◽  
Mixed Integer ◽  
Voltage Profile ◽  
Voltage Stability Index

Integrating Distributed Generation (DG) units into distribution systems can have an impact on the voltage profile, power flow, power losses, and voltage stability. In this paper, a new methodology for DG location and sizing are developed to minimize system losses and maximize voltage stability index (VSI). A proper allocation of DG has to be determined using the fuzzy ranking method to verify best compromised solutions and achieve maximum benefits. Synchronous machines are utilized and its power factor is optimally determined via genetic optimization to inject reactive power to decrease system losses and improve voltage profile and VSI. The Augmented Lagrangian Genetic Algorithm with nonlinear mixed-integer variables and Non-dominated Sorting Genetic Algorithm have been implemented to solve both single/multi-objective function optimization problems. For proposed methodology effectiveness verification, it is tested on 33-bus and 69-bus radial distribution systems then compared with previous works.

scholarly journals Coyote multi-objective optimization algorithm for optimal location and sizing of renewable distributed generators

2021 ◽  
Vol 11 (2) ◽  
pp. 975
Author(s):  
E. M. Abdallah ◽  
M. I. El Sayed ◽  
M. M. Elgazzar ◽  
Amal A. Hassan
Keyword(s):  
Optimization Algorithm ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Reducing Power ◽  
Stability Index ◽  
Optimal Location ◽  
Voltage Profile ◽  
Power Losses ◽  
Voltage Stability Index ◽  
Distributed Generators

Research on the integration of renewable distributed generators (RDGs) in radial distribution systems (RDS) is increased to satisfy the growing load demand, reducing power losses, enhancing voltage profile, and voltage stability index (VSI) of distribution network. This paper presents the application of a new algorithm called ‘coyote optimization algorithm (COA)’ to obtain the optimal location and size of RDGs in RDS at different power factors. The objectives are minimization of power losses, enhancement of voltage stability index, and reduction total operation cost. A detailed performance analysis is implemented on IEEE 33 bus and IEEE 69 bus to demonstrate the effectiveness of the proposed algorithm. The results are found to be in a very good agreement.

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