OPTIMASI MAXIMUM POWER POINT TRACKING DENGAN ALGORITMA INCREMENTAL CONDUCTANCE PADA SOLAR TRACKING MODUL SURYA BERBASIS SENSOR LDR

Manik, Risky Alberto (2026) OPTIMASI MAXIMUM POWER POINT TRACKING DENGAN ALGORITMA INCREMENTAL CONDUCTANCE PADA SOLAR TRACKING MODUL SURYA BERBASIS SENSOR LDR. S1 thesis, Universitas Kristen Indonesia.

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Abstract

Ketergantungan pada energi fosil memicu krisis sumber daya dan emisi gas rumah kaca, sehingga pemanfaatan energi terbarukan seperti sistem Photovoltaic (PV) menjadi krusial. Namun, efisiensi konversi energi PV masih rendah akibat faktor lingkungan seperti fluktuasi iradiasi matahari dan temperatur. Meskipun metode elektris melalui Maximum Power Point Tracking (MPPT) dan metode mekanis dengan Solar Tracking terbukti mampu meningkatkan performa, penelitian yang mengintegrasikan keduanya secara simultan masih sangat terbatas. Penelitian ini bertujuan untuk merancang sistem PV skala kecil yang optimal dengan mengintegrasikan algoritma MPPT Incremental Conductance (IC) dan sistem Solar Tracking single-axis berbasis sensor Light Dependent Resistor (LDR). Metodologi penelitian mencakup perancangan perangkat keras menggunakan panel 50 Wp Monocrystalline, Arduino Uno R3, baterai VRLA 12V 20Ah, sensor INA219, serta linear actuator. Pengujian dilakukan secara real-time dan simulasi berbasis Proteus. Hasil penelitian menunjukkan bahwa sistem kendali berbasis LDR mampu menggerakkan panel secara dinamis mengikuti lintasan matahari dari sudut {45}^\circ hingga {120}^\circ. Secara elektris, algoritma MPPT IC berhasil melacak dan mempertahankan operasi panel pada titik daya maksimum (MPP) meskipun terjadi fluktuasi cuaca. Integrasi kedua sistem ini terbukti sangat efektif meningkatkan performa dengan menghasilkan rata-rata daya sebesar 1,67 W dan total energi 13,9 Wh, yang merepresentasikan peningkatan performa energi rata-rata sebesar 76,45% dibandingkan dengan panel surya statis konvensional (daya rata-rata 1,02 W dan energi harian 8,47 Wh). Kebaruan sistem terintegrasi ini memberikan kontribusi signifikan bagi peningkatan performa pembangkit listrik tenaga surya masa depan. / Overdependence on fossil fuels triggers a resource crisis and greenhouse gas emissions, making the utilization of renewable energy, such as Photovoltaic (PV) systems, crucial. However, the energy conversion efficiency of PV remains low due to environmental factors like fluctuations in solar irradiation and temperature. Although electrical methods through Maximum Power Point Tracking (MPPT) and mechanical approaches using Solar Tracking have proven effective in enhancing performance, research integrating both simultaneously remains highly limited. This study aims to design an optimized small-scale PV system by integrating the Incremental Conductance (IC) MPPT algorithm with a single-axis Solar Tracking system based on Light Dependent Resistor (LDR) sensors. The research methodology encompasses hardware design using a 50 Wp Monocrystalline panel, Arduino Uno R3, 12V 20Ah VRLA battery, INA219 sensor, and a linear actuator. Tests were conducted in real-time and through Proteus-based simulations. The results indicate that the LDR-based control system successfully adjusted the panel dynamically following the sun's trajectory from an angle of 45∘ to 120∘ . Electrically, the IC MPPT algorithm effectively tracked and maintained the panel's operation at the Maximum Power Point (MPP) despite weather fluctuations. The integration of both systems proved highly effective in boosting performance, yielding an average power of 1.67 W and a total energy of 13.9 Wh. This represents an average energy performance improvement of 76.45% compared to a conventional static solar panel (average power of 1.02 W and daily energy of 8.47 Wh). The novelty of this integrated system provides a significant contribution to the performance enhancement of future solar power plants. Keywords : Incremental Conductance, LDR Sensor, Performance Enhancement, Photovoltaic, Solar Tracking.

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