SELECTION BASED NETWORK RECONFIGURATION IN DISTRIBUTION SYSTEMS
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DESIGN DETAILS
This design is based on the implementation of an algorithm which predicts optimum reconfiguration plan for power distribution system with DG and Capacitor. Since network reconfiguration is a multi-objective and multi constrained problem, genetic algorithm is used for optimization. Forward backward load flow method with time varying load condition and different load conditions are considered for performance evaluations. The objective function of the genetic algorithm incorporates all the objectives and constraints required for the reconfiguration plan. The algorithm developed predicts the switching pattern for reconfiguration which gives minimum loss and minimum voltage deviation. The design tested in IEEE 33 and 69 Bus System using Matlab 2020a version to verify the performance by applying 12 cases as below.
1. Base case
2. Only Reconfiguration
3. Only DG Allocation
4. Only Capacitor Allocation
5. DG allocation after Reconfiguration
6. Reconfiguration after DG Allocation
7. Capacitor allocation after Reconfiguration
8. Reconfiguration after Capacitor Allocation
9. Simultaneous Capacitor and DG Allocation
10. Simultaneous Reconfiguration and DG Allocation
11. Simultaneous Reconfiguration and Capacitor Allocation
12. Simultaneous Reconfiguration, DG and Capacitor Allocation
REFERENCES
Reference Paper-1: Genetic Algorithm based Network Reconfiguration in Distribution Systems with Multiple DGs for Time Varying Loads
Author’s Name: Chidanandappa. R, Dr.T.Ananthapadmanabha and , Ranjith. H.C
Source: Elsevier
Year:2015
Reference Paper-2: Optimal reconfiguration and capacitor placement for power loss reduction of a distribution system using improved binary particle swarm optimization.
Author’s Name: Mostafa Sedighizadeh. Marzieh Dakhem. Mohammad Sarvi and Hadi Hosseini Kordkheili
Source: Int J Energy Environ Eng
Year:2014
Reference Paper-3: Reconfiguration and optimal capacitor placement for losses reduction
Author’s Name: Diana P. Montoya and Juan M. Ramirez
Source: IEEE
Year:2012
DOWNLOAD the Matlab(P-code) encrypted code from the below URL,
https://drive.google.com/file/d/17pXqCdWopiQAZnhAJTLw3mLFff_Y-IDF/view?usp=sharing
SIMULATION VIDEO DEMO
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