Integrated PV-Farm and Micro Hydro as Distributed Generation in The Distribution Network

https://doi.org/10.22146/juliet.v6i1.104834

Muhaimin Muchti Prabowo(1), Pandhu Ardi Prasetyo(2), Lesnanto Multa Putranto(3*), Sarjiya Sarjiya(4), Jaya Kurniawan(5)

(1) Department of Electrical and Information Engineering, Universitas Gadjah Mada
(2) Department of Electrical and Information Engineering, Universitas Gadjah Mada
(3) Department of Electrical and Information Engineering, Universitas Gadjah Mada
(4) Department of Electrical and Information Engineering, Universitas Gadjah Mada
(5) PT PLN (Persero)
(*) Corresponding Author

Abstract


Renewable energy should be implemented in a compact size appropriate for a distributed generation (DG) system in order to maximize its maximum potential. For the distribution system utility, integrating a lot of DGs may cause some problems like voltage regulation and line loading violation. The condition might be worse if the DG is not owned by the distribution system since there are not so many control options. For that purpose, the optimization method for determining the location and size of DG is proposed based on the power system losses minimization. The optimization model is developed using a genetic algorithm technique. The real case 20 kV Godean Distribution System feeder number 4, having a peak load of 5.11 MW, is used for the test case with the integration options of solar and hydropower. The power system model is built using DIgSILENT PowerFactory, while the optimization model is built under the Python environment. Three scenarios, namely solar only, hydro only, and solar-hydro optimized, are developed to show the proposed method's effectiveness. From the simulation result, it shows that installing DGs in some buses and different resources may increase the penetration levels, which are 3.14, 2.24, and 3.78 MW, simultaneously for the solar-only, hydro-only, and solar-hydro-optimized scenarios. Furthermore, the solar-hydro-optimized scenario also results in higher loss reduction (7.27%) compared to 6.85% (solar only) and 6.56% (hydro only).




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DOI: https://doi.org/10.22146/juliet.v6i1.104834

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