scholarly journals Perancangan maximum power point tracking dengan algoritma incremental conductance untuk PLTS 100 Wp

2021 ◽  
Vol 1 (1) ◽  
pp. 1-8
Author(s):  
Abdullah Assegaf ◽  
Dedi Aming ◽  
Febri Alvianto
Keyword(s):  
Duty Cycle ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Incremental Conductance ◽  
Power Point

Efisiensi konversi energi yang rendah menjadi masalah utama padaupembangkit listrikutenagausurya (PLTS). Makalah ini membahas tentang implementasi metode maximum power point tracking (MPPT) dengan algoritma incremental conductance (IC) pada sistem panel surya dengan kapasitas 100 Wattpeak (Wp) yang bertujuan untuk mendapatkan daya keluaran yang paling optimal dari panel surya. Sistem dibangun dengan menggunakan konverter DC/DC buck-boost dan mikrokontroler sebagai pengolah algoritma MPPT serta pusat kendali sistem. Mikrokontroler akan mengontrol duty cycle dari konverter buck-boost dan memastikan bahwa panel surya selalu beroperasi pada kondisi titik daya maksimum dengan menggunakan algoritma IC. Hasil pengujian menunjukkan bahwa penggunaan metode MPPT dengan algoritma IC pada sistem panel surya 100 Wp dapat memaksimalkan daya keluaran dari panel surya sebesar 56%-94% dibandingkan dengan penggunaan panel surya secara langsung tanpa menggunakan MPPT.

scholarly journals Perbaikan MPPT Incremental Conductance menggunakan ANN pada Berbayang Sebagian dengan Hubungan Paralel

2020 ◽  
Vol 8 (3) ◽  
pp. 546
Author(s):  
MUHAMMAD NIZAR HABIBI ◽  
DIMAS NUR PRAKOSO ◽  
NOVIE AYUB WINDARKO ◽  
ANANG TJAHJONO
Keyword(s):  
Neural Network ◽  
Duty Cycle ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Incremental Conductance ◽  
Power Point

ABSTRAKAlgoritma IncrementaL Conductance (IC) adalah algoritma yang bisa diimplementasikan pada sistem Maximum Power Point Tracking (MPPT) untuk mendapatkan daya maksimum dari panel surya. Akan tetapi algoritma MPPT IC tidak bisa bekerja dikondisi berbayang sebagian, karena menimbulkan daya maksimum lebih dari satu. Artificial Neural Network (ANN) bisa mengidentifikasi kurva karakteristik pada kondisi berbayang sebagian dan dapat mengetahui posisi daya maksimum yang sebenarnya. Masukan dari ANN merupakan nilai arus hubung singkat serta tegangan buka dari panel surya, dan keluaran dari ANN adalah nilai duty cycle yang digunakan sebagai posisi awal tracking dari MPPT IC. Data learning didapatkan dari perubahan nilai duty cycle secara manual pada sistem MPPT di berbagai kondisi radiasi. Hasil pengujian menunjukkan algoritma yang diajukan dapat menaikkan energi 5.79% - 13.32% dibandingkan dengan ANN-Perturb and Observe dan ANN-Incremental Resistance dengan durasi 0.6 detik.Kata kunci: MPPT, Incremental Conductance, Artficial Neural Network, Berbayang Sebagian, Hubungan Paralel ABSTRACTThe Incremental Conductance (IC) algorithm is an algorithm that can be implemented on Maximum Power Point Tracking (MPPT) systems to get maximum power from solar panels. However, the MPPT IC algorithm cannot work in partial shading conditions because it causes more than one maximum power. Artificial Neural Network (ANN) can identify characteristic curves under partial shading conditions and can know the actual maximum power position. The input from ANN is the short circuit current and the open voltage of the solar panel. The output of ANN is the duty cycle value that is used as the initial tracking position of the MPPT IC. Learning data is obtained from manually changing the duty cycle value in the MPPT system in various radiation conditions. The test results show the proposed algorithm can increase energy 5.79% - 13.32% when compared with ANN-Perturb and Observe and ANN-Incremental Resistance with a duration of 0.6 seconds.Keywords: Maximum Power Point Tracking, Incremental Conductance, Artficial Neural Network, Partial Shading, Parallel Connection

scholarly journals Implementation of Algorithm on MPPT

2021 ◽  
Vol 9 (VI) ◽  
pp. 5473-5478
Author(s):  
Bharat Khandelwal
Keyword(s):  
Tracking System ◽  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Maximum Efficiency ◽  
Maximum Power Point ◽  
Good Efficiency ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Incremental Conductance ◽  
Power Point

Solar energy is a potential energy source in India. A photovoltaic is a efficient way to cure the energy in a huge amount and keep to gather that kind of energy for future, and the PV must have good efficiency. The maximum power point tracking (MPPT) is a process that tracks one maximum power point from array input, in which the ratio varies between the voltage and current delivered to get the most power it can. Several algorithms have been developed for extracting maximum power. To increase its efficiency many MPPT techniques are used. Incremental conductance is one of the important techniques in this system and because of its higher steady-state accuracy and environmental adaptability it is a widely implemented tracked control strategy. This research was aimed to explore the performance of a maximum power point tracking system that implements the Incremental Conductance (IC) method. The IC algorithm was designed to control the duty cycle of the Buck-Boost converter and to ensure the MPPT work at its maximum efficiency. From the simulation, the IC method shows better performance and also has a lower oscillation.

scholarly journals A Maximum Power Point Tracking Method Based on a Modified Grasshopper Algorithm Combined with Incremental Conductance

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4329
Author(s):  
Bustani Hadi Wijaya ◽  
Ramadhani Kurniawan Subroto ◽  
Kuo Lung Lian ◽  
Nanang Hariyanto
Keyword(s):  
Maximum Power Point Tracking ◽  
Maximum Power ◽  
Global Maximum ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Incremental Conductance ◽  
Grasshopper Optimization Algorithm ◽  
Tracking Time ◽  
Power Point

The partial shading of photovoltaic (PV) modules due to clouds or blocking objects, such as buildings or tree leaves, is a common problem for photovoltaic systems. To address this, maximum power point tracking (MPPT) is implemented to find the global maximum power point (GMPP). In this paper, a new hybrid MPPT is proposed that combines a modified grasshopper optimization algorithm (GOA) with incremental conductance (IC). In the first stage, the proposed modified GOA is implemented to find a suitable tracking area where the GMPP is located. Then the system moves to the second stage by implementing IC to get the correct GMPP. IC is a fast-performing and reliable algorithm. By combining GOA and IC, the proposed method can find the GMPP accurately with a short tracking time. Various experimental results show that the proposed method yields the highest tracking efficiency and lowest tracking time compared to some of the state-of-the-art MPPT algorithms, such as particle swarm and modified firefly optimizations.

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