ICTACT Journal on Soft Computing

Chia Seet Chin ¹, Bih Lii Chua ¹, Pei Yi Lim ¹, Hui Hwang Goh ¹, Kenneth Tze Kin Teo ¹

Affiliations
1 Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, MY

Abstract

The photovoltaic (PV) array controlled by Maximum Power Point Tracking (MPPT) method for optimum PV power generation, particularly when the PV array is under partially shaded condition is presented in this paper. The system modelling is carried out in MATLAB-SIMULINK where the PV array is formed by five series connected identical PV modules. Under uniform solar irradiance conditions, the PV module and the PV array present nonlinear P-V characteristic but the maximum power point (MPP) can be easily identified. However, when the PV array is under shaded conditions, the P-V characteristic becomes more complex with the present of multiple MPP. While the PV array operated at local MPP, the generated power is limited. Thus, the investigation on MPPT approach is carried out to maximize the PV generated power even when the PV array is under partially shaded conditions (PSC). Fuzzy logic is adopted into the conventional MPPT to form fuzzy logic based MPPT (FMPPT) for better performance. The developed MPPT and FMPPT are compared, particularly the performances on the transient response and the steady state response when the array is under various shaded conditions. FMPPT shows better performance where the simulation results demonstrate FMPPT is able to facilitate the PV array to reach the MPP faster while it helps the PV array to produce a more stable output power.

Keywords

Photovoltaic, Partially Shaded Conditions, MPPT, Fuzzy Logic, Perturb and Observe.

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Nurul Izyan Kamaruddina ¹, Ahmad Razani Haron ¹, Bih Lii Chua ¹, Min Keng Tan ¹, Kit Guan Lim ¹, Kenneth Tze Kin Teo ¹

Affiliations
1 Modelling, Simulation and Computing Laboratory, Artificial Intelligence Research Unit, Faculty of Engineering, Universiti Malaysia Sabah, MY

Abstract

Photovoltaic system (PV) is an important technological asset for renewable energy production. It works by converting solar cell energy from the sun into electrical direct current. In reality, the photovoltaic module usually receives non-uniform solar irradiance at different light intensity due to non-atmospheric hindrance. Under such conditions, the PV system exhibits multiple peaks on the energy characteristic curve, generally known as the partial shading condition (PSC). Therefore, in order to maximize the energy harvested by the photovoltaic system (PV), maximum power point tracking (MPPT) method is suggested to extract all possible maxima that have been produced by the PV system under various circumstances through the non-uniform irradiance of the sunlight. Based on previous researches, it is found that conventional method such as perturb and observed (P&O) method failed to track the maximum power and was trapped at the local maximum power (LMPP). This paper focuses on exploring a metaheuristic method which is the differential evolution (DE) algorithm in optimizing the energy harvested by the PV system. The platform chosen for modelling in this paper is a 3 × 3 PV array. The PV array is tested with different conditions of partial shading where random irradiance values are set. Comparing the performance of PV between P&O and DE based MPPT controller, the DE based MPPT controller is inferred to have a higher success rate to escape from being trapped in LMPP and thus produce more total energy.

Keywords

Photovoltaic system, Maximum Power Point Tracking, Partial Shading Condition, Perturb and Observed, Differential Evolution.

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