Optimal Location of Small Hydro Power Plants (SHPPS) at Distribution System by Using Voltage Sensitivity Index
International Journal of Energy and Power Engineering
Volume 5, Issue 2-1, March 2016, Pages: 13-17
Received: Sep. 18, 2015; Accepted: Sep. 21, 2015; Published: Oct. 12, 2015
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Authors
Alaa Abdulwahhab Azeez Baker, Department of Electrical Power and Machines Engineering, Engineering College, Mosul, Iraq
Maamon Phadhil Yasen Al-Kababji, Department of Electrical Power and Machines Engineering, Engineering College, Mosul, Iraq
Sameer Saadoon Al-Juboori, Department of Electronics & Control Engineering, Kirkuk Technical College, Kirkuk, Iraq
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Abstract
This work presents a method to enhance the distribution network for both test and real systems by adding small hydro power plants (SHPPS). The voltage sensitivity index (VSI) was used to find the optimal locations to add small hydro power plants (SHPPS). The study has been applied to the system at unity and 0.9 lagging power factor. The test system is a standard IEEE 33-nodes radial distribution network. Maltab program was used to simulate the systems. The simulation results when connecting the (SHPPS) to the test system showed the improvement in voltage profile of the test system nodes in addition to power losses reduction. The reductions of the real and reactive power losses percentage reached (36%) and (14%) at unity power factor respectively, while at (0.9) lagging power factor, the reduction of the real and reactive power losses percentage were found (53%) and (56%) respectively.
Keywords
Distribution System, Loss Minimization, Voltage Profile, IEEE Bus System, Renewable Energy Sources (RESs), Small Hydropower Plant (SHP)
To cite this article
Alaa Abdulwahhab Azeez Baker, Maamon Phadhil Yasen Al-Kababji, Sameer Saadoon Al-Juboori, Optimal Location of Small Hydro Power Plants (SHPPS) at Distribution System by Using Voltage Sensitivity Index, International Journal of Energy and Power Engineering. Special Issue: Modeling and Simulation of Electric Power Systems and Smart Grids. Vol. 5, No. 2-1, 2016, pp. 13-17. doi: 10.11648/j.ijepe.s.2016050201.13
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