Reliability Improvement and Power Loss Reduction in Distribution System (Case Study: Hormat Substation II)
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Abstract
The distribution system connects high-voltage transmission networks with end users. Most of the
time, power plants are situated distant from the consumer's location. This results a large loss of
power in both distribution and transmission systems. However, distribution system losses are
typically greater than transmission line side losses. The main objective of this study is to reduce
power losses and improve system reliability using Distributed Generation (DG) in the case of
Hormat Substation II. Hormat distribution substation II has three feeder lines that provide energy
for different customers. From these feeders, the Ambo town feeder has been chosen since it is
frequently interrupted. The chosen feeder has been modeled in ETAP software, and simulation
results have been done with both ETAP, and MATLAB software, and the results show that the
feeder has a power loss of 759.7 KW and 403.5 kVar active and reactive respectively.
Additionally, the study has been able to investigate the existing reliability indices of SAIFI, SAIDI,
and EENS which has values of 355.0820 f/cust.yr, 335.9636 hr/cust.yr, and 2851.479 MWhr/yr
respectively. Multi-Objective Particle Swarm Optimization algorithm have been suggested to
decide the best size and position of DG. After renewable distributed Generation penetrated to the
network, the real and reactive power loss reduced from 759.7 KW and 403.5 kVar to 412.9 Kw,
and 203.12 KVar respectively. Additionally, the SAIFI, SAIDI, and EENS system reliability
indices were improved from 355.0820 f/cust.yr, 335.9636 hr/cust.yr, and 2851.479 MWhr/yr to
44.053 f/cust.yr, 55.648 hr/cust.yr, and 460.955MWh/yr respectively. At the end, reliability
indices, and line losses before, and after Distributed Generations penetrated to the network have
been compared. In general, the simulation results indicate that the suggested method is efficient
to maintain system reliability and minimize power losses.