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Elias K. Bawan
Jurusan Teknik Universitas Negeri Papua

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DAMPAK PEMASANGAN DISTRIBUTED GENERATION TERHADAP RUGI-RUGI DAYA Elias K. Bawan
Foristek Vol. 2 No. 2 (2012): Foristek
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The introduction of distributed generation (DG) onto distribution networks has a significant effect on power system. This effect cannot be characterized as detrimental or beneficial but is dependent on the allocation of DG on each distribution network section. Here the impact of DG on losses has been modeLED, facilitating a unique approach to the allocation of DG. This approach has been implemented and tested on sample sections of distribution network and results are presented showing the optimal allocation of DG which improves the efficiency of energy delivery on the distribution network. This paper aims to investigate the impact of distributed generation on distribution system losses. The main objective is to reduce the power losses based on location of DG and size of injection. Minimizing losses in the system is a delicate balance; one of the key areas is a balance between transmission losses andstorage losses. Distributed generation can save on transmission losses and must be carefully designed to ensure that storage and the losses associated are minimized. Distributed generation can be used in niche applications to assist distributed generation and help manage the variability of the transmission grid. Using application program ETAP 6.0 and the Manokwari electricity distribution system as case study, the results shows thatat certain location, the power injection of DG has decrease losses from 240,15 kW to 99,39 kW and more economic than without DG installation. The best location of interconnection is bus 77 from power grid and injection of 85% DG capacity.
ESTIMASI PEMBEBANAN TRANSFORMATOR GARDU INDUK 150 KV Elias K. Bawan
Foristek Vol. 3 No. 2 (2013): Foristek
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Development of an area, such as Yogyakarta is directly proportional to consumption of power in that area. Transformer of 150 KV Wirobrajan substation, 60 MVA, is one of main equipment in power system. Load forecasting on this research using daily average peak load data during five years that is since 2003 to 2008. Based on the analysis of the result of exponential model approach method, the equation Y = 5.29 e 0.04057X is obtained. By using this model, it is found that average load growth forecasting of the transformer during 2009 to 2025, is suitable to supply 50.89 MVA of load demand (85% of full load). Moreover,model Y = 20.18 + 0.44X1 + 0.07X2 is found using polynomial method. In 2025, the transformer, based on polynomial method,can deliver power 80.07 MVA (about 80.07% of full load). Finally, load current was 230.72 A, in 2025.