Simultaneous placement of distributed generation and capacitors in distribution networks considering voltage stability index

Author(s):  
Sayyid Mohssen Sajjadi ◽  
Mahmoud-Reza Haghifam ◽  
Javad Salehi
Author(s):  
Mostafa Elshahed ◽  
Mahmoud Dawod ◽  
Zeinab H. Osman

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.


Author(s):  
Mahesh Kumar ◽  
Perumal Nallagownden ◽  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Luqman Hakim Rahman

In the distribution system, distributed generation (DG) are getting more important because of the electricity demands, fossil fuel depletion and environment concerns. The placement and sizing of DGs have greatly impact on the voltage stability and losses in the distribution network. In this chapter, a particle swarm optimization (PSO) algorithm has been proposed for optimal placement and sizing of DG to improve voltage stability index in the radial distribution system. The two i.e. active power and combination of active and reactive power types of DGs are proposed to realize the effect of DG integration. A specific analysis has been applied on IEEE 33 bus system radial distribution networks using MATLAB 2015a software.


Author(s):  
Tapan Kumar Chattopadhyay ◽  
Sumit Banerjee ◽  
Chandan Kumar Chanda

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.


2018 ◽  
Vol 7 (3) ◽  
pp. 442-449
Author(s):  
Mohd Nurulhady Morshidi ◽  
Ismail Musirin ◽  
Siti Rafidah Abdul Rahim ◽  
Mohd Rafi Adzman ◽  
Mohamad Hatta Hussain

This paper presents Whale Optimization Algorithm (WOA) Based Technique for Distributed Generation Installation in Transmission System. In this study, WOA optimization engine is developed for the installation of Distributed Generation (DG). Prior to the optimization process, a pre-developed voltage stability index termed Fast Voltage Stability Index (FVSI) was used as an indicator to identify the location for the DG to be installed in the system. Meanwhile, for sizing the DG WOA is employed to identify the optimal sizing. By installing DG in the transmission system, voltage stability and voltage profile can be improved, while power losses can be minimized. The proposed algorithm was tested on 30-bus radial distribution network. Results obtained from the EP were compared with firefly algorithm (FA); indicating better results. This highlights the strength of WOA over FA in terms of minimizing total losses.


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