OPTIMAL ALLOCATION OF DG IN DISTRIBUTION SYSTEM WITH GENETIC ALGORITHM TECHNIQUE
ABSTRACT:: The interconnection of Dstributed Generation (DG) in a distribution network would change the radiality of the convention power flows in the system. Instead of helping to reduce the system losses, it also improves the quality of the overall system network. However, improper allocation and sizing of its interconnection to the system could oppositely change those advantages. The total system may experience higher losses and instability. In our project, a new technique to determine the optimal allocation of DG in distribution system by using Genetic Algorithm (GA) technique is proposed. The effectiveness of this technique over sensitivity factor approach is demonstrated using IEEE-11, 33 and 69 bus distribution test system and simulated in MATLAB.
Key words: Distribution system, embedded generation (EG), genetic algorithm (GA), optimal allocation.
11-BUS SYSTEM ::
•Fig. shows the 11-bus system with a total real and reactive power demand is 7.1558 p.u and 5.3555 p.u respectively.
•DG’s size is more accurate and efficient method of finding by Genetic algorithm(GA)
Technique.
•As the voltage profile and real power losses are inversely related, improvement in voltage is observed with DG.
33-BUS SYSTEM ::
•Fig. shows the 33-bus system with a total real and reactive power demand is 3,715 kW and 2,300 KVAR. respectively.
•As all buses are not rooted from bus-1 the entire system will effect with placing of DG.
•Simulation results bus-7 is the optimal location.
•Losses reduced more at the location of bus.
•Voltage profile is improved throughout the system.
•Based on the system losses and requirement it can be able to connect multiple DG’s.
•With and without DG effect is observed.
69-BUS SYSTEM ::
•Fig. shows the 69-bus system with a total real and reactive power demand is 3802.19 kW and 2694.6 KVAR respectively.
•Simulation results bus-61 is the optimal location.
•Losses are reduced more at the location of bus and Voltage profile is improved throughout the system.
•Based on the system losses and requirement it can be able to connect multiple DG’s.
With and without DG effect is observed.
Summary
• Without DG real power losses are maximum and voltage profile is poor.
• Requirement of DG is essential where the distributed network sustains loss.
• Introducing DG improves voltage profile and reduces losses.
• Improper allocation misleads to drastic profile of the system.
• GA technique solves the DG size problem optimistically.
• Once the DG power output exceeded the optimal value, power losses will tend to increase beyond the minimal value.
• Introducing of GA technique differentiates the improvement from analytical method in voltage profile and DG size.
• Conventional method is not a big hand with large system but GA can help for extension.
• GA gives best results than computational procedure.
My Role in the project
Under the esteemed guidance of Dr. V.S.Vakula, Associate Professor, Department of Electrical & Electronics Engineering, JNTUK, Vizianagaram we, a team of 5 members have done our project. Even though I involved in the whole project work, my key role was to do calculations and program solving for 11- bus and 33-bus system.
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