Limits control and energy saturation management for DC bus regulation in photovoltaic systems with battery storage

Assem, H.; Bouchafaa, Farid; Arab, A. Hadj; Laarouci, Cherif

doi:10.1016/j.solener.2020.10.061

Cited by 9 publications

(2 citation statements)

References 34 publications

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“…A DS1104 DSpace board is used to real-time test the proposed control and power management system developed and implemented in Matlab/Simulink. Additional system specifcations of the relevant experimental parameters are given in Table 2 [48].…”

Section: Experimental Setup Descriptionmentioning

confidence: 99%

Adaptive Fuzzy Logic-Based Control and Management of Photovoltaic Systems with Battery Storage

Assem

Azib

Bouchafaa

et al. 2023

International Transactions on Electrical Energy Systems

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Renewable energy sources (RESs) such as solar photovoltaic (PV) systems are increasingly used as distributed generation for replacing the conventional energy. At the same time, energy storage systems like battery (BAT) must be applied for maintaining the balance between fluctuating energy production and load consumption. BAT’s state of charge (SOC) should be maintained within their design limits unaffected by RES intermittency and/or load power variations. This necessitates advanced power control and management methodologies for overcoming challenging conditions. This paper discusses and evaluates an optimal DC bus voltage regulation approach: an intelligent controller using an adaptive fuzzy logic controller (FLC) and a novel supervisory power management strategy for PV systems with BAT. The objectives are to keep a stable power flow in the system and guarantee the continuity of service by ensuring that the system components do not exceed their limits. In this manner, the DC bus voltage regulation of the PV/BAT system can be improved in comparison with conventional regulation. Therefore, the most important contributions of this work are as follows. (1) Development of comprehensive and modular novel energy management system (EMS): its originality is related to the inclusion of the control system limits with faster SOC balancing and smaller DC bus voltage fluctuation. (2) Providing a simple power flow management implementation that considers the optimal energy flow between PV system, BAT system, and load: a balance between minimal energy flow in the connecting line and the least requirements of BAT capacity is kept, reducing component constraints with a very straightforward structure. (3) Furthermore, FLC offers high robustness and smooth performances. FLC is added to the control strategy design requirements to reduce DC bus voltage deviation. (4) Real-time simulation/experimentation-based complete cases utilizing Matlab/Simulink and DSpace are illustrated to testify the effectiveness of the proposed FLC and EMS.

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Section: Experimental Setup Descriptionmentioning

confidence: 99%

Adaptive Fuzzy Logic-Based Control and Management of Photovoltaic Systems with Battery Storage

Assem

Azib

Bouchafaa

et al. 2023

International Transactions on Electrical Energy Systems

Self Cite

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“…This approach seeks and tracks the maximum power point (MPP) under a different set of dynamic solar irradiances. Additionally, it will precisely adjust the duty ratio cycle of a DC-DC converter to speed up the tracking process of MPP [36]. Simulation analyzes are performed to test the tracking accuracy and overall performance of the suggested approach in this research study.…”

Section: Introductionmentioning

confidence: 99%

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

M. Elzein,

Kurdi,

Harrye

2024

IJCDS

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In a photovoltaic system the challenge is to contentiously searching for the maximum power point to generate the maximum power (Pmax) within the system. In this study a hybrid maximum power point tracking module (MPPT) consisting of a well-known incremental conductance algorithm (INC) is being adapted to operate along with fuzzy logic controller (FLC). The new design focused on applying variable voltage step size estimations based on analyzing the degree of incremental and decremental of power to voltage relation. To achieve this, five effective regions were introduced around the maximum PV power point and FLC controlled the tunning and accurate adjustments of the duty ratio cycle step size by relying on the inputs of fuzzy logic controller to reach a zero oscillation around the MPP point. To adjust the duty cycle step size, fuzzy logic is established based on the position of the fuzzy input points which are derived from the current and voltage proportions and their derivatives, whereas the membership functions and rules are shaped. Matlab simulations were used under different irradiance levels to test the efficiency of tracking the maximum power. Based on the simulated results, the integration of fuzzy logic controller with incremental conductance algorithm provided enhanced performance in tracking the Pmax, and notable fast convergence time and provided the least oscillation around the maximum power point and thus maintained the overall tracking accuracy, and applying the proper step size to drive the operating point at the P-V curve in reaching Pmax under the effects of various environmental dynamic changes in temperature and irradiance.

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Comparative study of maximum power point tracking control for PV arrays system integration process

Meng,

Guo,

Yue

et al. 2024

Control Engineering Practice

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Limits control and energy saturation management for DC bus regulation in photovoltaic systems with battery storage

Cited by 9 publications

References 34 publications

Adaptive Fuzzy Logic-Based Control and Management of Photovoltaic Systems with Battery Storage

Adaptive Fuzzy Logic-Based Control and Management of Photovoltaic Systems with Battery Storage

Optimizing The Maximum Power of Photovoltaic System Using Modified Incremental Conductance Algorithm Operating Under Varying Dynamic Climatic Conditions

Comparative study of maximum power point tracking control for PV arrays system integration process

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