Analisis Maximum Power Point Tracking Fuzzy Logic Boost Converter untuk Sistem Pengisian Daya pada Pembangkit Listrik Tenaga Surya terhadap Cuaca Kota Surabaya

Pembangkit Listrik Tenaga Surya (PLTS) menghadapi tantangan mendasar karena daya keluaran panel surya bersifat non-linear dan dipengaruhi oleh perubahan iradiasi matahari serta temperatur, sehingga Titik Daya Maksimum (Maximum Power Point) senantiasa bergeser dan berisiko menyebabkan energi hilang. Metode Maximum Power Point Tracking (MPPT) konvensional seperti Perturb & Observe (P&O) memiliki keterbatasan osilasi di sekitar MPP dan risiko mistracking saat iradiasi berubah mendadak. Penelitian ini bertujuan menganalisis pengaruh iradiasi dan temperatur Kota Surabaya terhadap performa PLTS, mengevaluasi kinerja MPPT berbasis Fuzzy Logic Controller (FLC), serta membandingkannya dengan MPPT P&O. Penelitian dilakukan melalui simulasi MATLAB/Simulink R2021a menggunakan data iradiasi dan temperatur Kota Surabaya tahun 2025. Model sistem meliputi panel surya, Boost Converter, baterai LiFePO4, dan Bidirectional DC-DC Converter (BDC) pada arsitektur Common DC Bus. Hasil simulasi menunjukkan variasi iradiasi dan temperatur berpengaruh signifikan terhadap performa PLTS, dengan daya puncak musim kemarau lebih dari dua kali lipat dibanding musim hujan (1.082,7 W berbanding 472,9 W). MPPT FLC menyesuaikan duty cycle adaptif dengan efisiensi tracking 76,24-78,53% dan ripple tegangan rendah (0,69-1,14%). Dibandingkan MPPT P&O, FLC menghasilkan ripple tegangan lima kali lebih kecil (0,93% berbanding 4,82%) dengan efisiensi energi tahunan sebanding (90,39% berbanding 93,05%), mengonfirmasi efektivitas FLC MPPT menjaga kestabilan pelacakan pada cuaca yang bervariasi.

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Photovoltaic (PV) systems face a fundamental challenge because the output power of photovoltaic panels is nonlinear and influenced by variations in solar irradiance and temperature. As a result, the Maximum Power Point (MPP) continuously shifts, increasing the risk of energy loss. Conventional Maximum Power Point Tracking (MPPT) methods, such as Perturb and Observe (P&O), have limitations due to oscillations around the MPP and the risk of mistracking during sudden changes in irradiance. This study aimed to analyze the effects of solar irradiance and temperature in Surabaya on the performance of a photovoltaic (PV) system, evaluate the performance of a Fuzzy Logic Controller (FLC)-based MPPT, and compare it with the conventional P&O MPPT method. The study was conducted through simulations using MATLAB/Simulink R2021a with solar irradiance and temperature data from Surabaya for the year 2025. The system model consisted of a photovoltaic panel, a boost converter, a LiFePO₄ battery, and a bidirectional DC–DC converter (BDC) configured in a common DC bus architecture. The simulation results demonstrated that variations in solar irradiance and temperature significantly affected the performance of the PV system, with the peak power during the dry season being more than twice that during the rainy season (1,082.7 W versus 472.9 W). The FLC-based MPPT adaptively adjusted the duty cycle, achieving a tracking efficiency ranging from 76.24% to 78.53% with low voltage ripple (0.69–1.14%). Compared with the P&O MPPT method, the FLC-based MPPT produced voltage ripple approximately five times lower (0.93% versus 4.82%) while maintaining comparable annual energy efficiency (90.39% versus 93.05%), confirming its effectiveness in maintaining stable tracking performance under varying weather conditions.