Abstract
Electric power is the main energy source for a modern society. Good management of electric power cycle is essential for a sustainable society. The electric power cycle is composed of Generation, Transmission, Distribution, and Consumption. Smart Grid (SG) is a system that integrated traditional grids with Information and Communication Technology (ICT). In addition, SG has the ability to integrate electrical power supply from both to main power substation and Distributed Generation (DG), which compensates for the power demand during peak times. However, SG still has a similar problem to the original grid in terms of active power loss, from electric current injecting through the transmission line. This paper solves the active power loss problem by feeder routing using the Adjusting Dijkstra's Cost Method, follow by deciding the allocation position and sizing of DG by the use of Evolutionary Computing, namely Harmony Search (HS), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO). The experiments evaluate the performance of the algorithm using power flow analysis, Backward / Forward Sweep Method, on the IEEE 33 bus system. From the experimental results, PSO provides the best performance. The overall active power loss in the cases of 3 DGs was reduced from 202.67 to 52.29 kW, representing a reduction of 74.20%.
Highlights
A smart electricity system, such as a Smart Grid (SG) system, is required in order to efficiently serve higher power demand
SG has the ability to integrate electrical power supply from both to main power substation and Distributed Generation (DG), which compensates for the power demand during peak times
The experimentation was reconfigured as feeder topology to improve performance
Summary
A smart electricity system, such as a Smart Grid (SG) system, is required in order to efficiently serve higher power demand. The SG distribution has more advanced information, it still suffers from the same problem as the traditional grid, namely active power loss, that affects the electrical power transfer directly. Optimization (PSO) was used to determine the allocation and sizing of the DG to reduce the active power loss. In the experiments with the IEEE 33 bus system, the results reduced active power loss by determining the allocation and sizing of the DG appropriately (Guerriche and Boktir, 2015). In order to minimize active power loss, this paper selects the IEEE 33 bus system and processes with feeder routing. After defined the routing path, the DG allocation and sizing was used to compare the techniques of HS, ABC, and PSO.
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