| Autor: |
Muhammad Nizar Habibi, Diah Septi Yanaratri, Ade Pradana Firmanza, Novie Ayub Windarko |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 10th Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS). |
| DOI: |
10.1109/eeccis49483.2020.9263430 |
| Popis: |
The performance of the photovoltaic system heavily depends on solar irradiance and temperature conditions. A condition where photovoltaic received non-uniform solar irradiance is called partial shading condition. Partial shading can affect the power-voltage characteristics of the photovoltaic system resulting in more than one maximum power points. This reason can be one of the leading causes of some energy losses for many photovoltaic systems. In order to overcome the mentioned problem, this paper proposes a differential evolution (DE) based MPPT algorithm with dual mutation factors to track the global maximum power point of photovoltaic systems under partial shading. The mutation step is modified by using two mutation factors to enlarge the search space and optimize the convergence speed in the tracking process. The photovoltaic system in this paper uses two 100 Wp photovoltaic modules configured in series and a DC-DC boost converter. The performance of the proposed algorithm is validated in PSIM simulation and compared to the PSO algorithm. The proposed MPPT is tested with a rapid change of solar irradiation on both two modules. The result shows that the MPPT is able to track the GMPP under fluctuating partial shading conditions fast, with no oscillation and accurate. The average tracking speed of the proposed algorithm is 0.309 s, and the MPPT accuracy is 99.9%. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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