Fayyadh Dzakwan, . (2026) OPTIMALISASI MAXIMUM POWER POINT TRACKING DENGAN ALGORITMA HIBRIDA DAN KONTROL ADAPTIF UNTUK MENURUNKAN RIPPLE DAYA PADA PANEL SURYA. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
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Abstract
Solar panel utilization requires a Maximum Power Point Tracking (MPPT) system capable of maintaining photovoltaic operation near the Maximum Power Point. Perturb and Observe (P&O) and Incremental Conductance (INC) are widely used due to their simplicity and effectiveness; however they still produce steady state power ripple and suboptimal transient response. This study designs a hybrid MPPT algorithm with adaptive control to reduce power ripple in a photovoltaic system using a boost converter. The proposed algorithm combines the P&O correction direction, an INC based MPP proximity indicator, adaptive step, hysteresis, dwell time, and holding strategy. Simulations were conducted under irradiance levels of 1000 W/m² and 750 W/m², using P&O and INC as baselines. The hybrid algorithm maintained steady-state average output power of 2.558 kW against 2.563 kW and 1.931 kW against 1.940 kW. The hybrid power ripple decreased to 9 × 10⁻⁹ kW and 5 × 10⁻⁹ kW in range used. It also achieved the fastest settling time of 0.032 s and 0.036 s. Although its average power in T1 was slightly lower, the difference was small and remained close to the theoretical value. Therefore, the hybrid algorithm reduces ripple, accelerates tracking toward the MPP, and improves power stability.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2210314076] [Pembimbing 1 : Ferdyanto] [Pembimbing 2 : Luh Krisnawati] [Penguji 1: Achmad Zuchriadi P.] [Penguji 2: Nur Fauziyah} |
| Uncontrolled Keywords: | Hybrid Algorithm, Maximum Power Point Tracking (MPPT), Ripple power, Settling time. |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Teknik > Program Studi Teknik Elektro (S1) |
| Depositing User: | FAYYADH DZAKWAN |
| Date Deposited: | 28 Aug 2026 03:12 |
| Last Modified: | 28 Aug 2026 03:12 |
| URI: | http://repository.upnvj.ac.id/id/eprint/52932 |
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