Optimal Sizing and Sitting of Distributed Generation for Power Quality Improvement of Distribution Network

Abubakar Bawa, Muhammad Uthman, Farouq E. Shaibu and Koledowo Saliu Oyewale
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Abubakar Bawa: Transmission Company of Nigeria (TCN), ISO, Nigeria
Muhammad Uthman: Universtiy OF Abuja, Nigeria
Farouq E. Shaibu: Federal Radio Corporation of Nigeria (FRCN), Nigeria

European Journal of Engineering and Technology Research, 2019, vol. 4, issue 10, 18-23

Abstract: The Point of Common Coupling (PCC) where suppliers’ responsibility and customers demand meet is of great concern due to increase degree of voltage variation assessment; valuable indicator of system conditions (voltage profile). Unstable condition of the power system outside operational or statutory limit, an adverse effect of nonlinear loads usually generate harmonics as well as fundamental frequency voltage variations and increase rate of power losses. These loads need to be compensated for. The major concerns of utility operations is to mitigate adverse effect of this system conditions. This research work focuses on optimal siting and sizing of Distributed Generation (DG) in a 43 bus distribution system. Power losses coupled with voltage deviation, considering objective function that compute present percentage losses in 11kV Dikko feeder, Abuja Electricity Distribution Company (AEDC), Suleja Distribution Network, Nigeria. We identified buses with poor voltage profile without DG installation and determined optimal sizing and siting of DGs where losses can be mitigated and power quality improved. ETAP version 12.6 2014 was used for load flow analysis to establish a decisive based case. The total load of the system considered was (3490 + j2700) kVA. Active and Reactive power losses in the system before DG installation were 246.300 kW and 289.903 kVAR respectively. DGs installation in the case study, has a considerable effects on loss reduction in the network. It is observed that 8.10% and 7.20% active and reactive power loss reduction was achieved while bus voltage improved by 0.4%. Genetic Algorithm Optimization techniques programmed in MATLAB 2015 software was used for optimal placement and sizing of the DG in the system.

Keywords: Distributed Generation; Genetic Algorithm; Optimal Placement; Power Loss Reduction; Voltage Profile Improvement (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:4:y:2019:i:10:id:61555

DOI: 10.24018/ejeng.2019.4.10.1555

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