Hybrid Optimization of FOPID Controller with WOA-ALO Algorithm for Enhanced Control in Solar PV Systems

Problem Definition

The solar photovoltaic (PV) systems are critical components of renewable energy infrastructure, offering a sustainable and environmentally friendly solution for power generation. Within this domain, the optimization of power output and efficiency remains a key challenge. The Perturb and Observe (P&O) Method for Maximum Power Point Tracking (MPPT) has been a widely studied approach, with researchers like Ebrahim, Mohamed et al. (2019) implementing a Proportional-Integral-Derivative (PID) controller to improve system performance. While this method has shown promise, there are significant limitations and areas for improvement that need to be addressed.

The existing approach may not fully exploit the potential of maximizing power output and efficiency, leading to suboptimal performance and energy wastage. Therefore, there is a pressing need for further research and optimization to enhance the effectiveness of MPPT algorithms in solar PV systems. By addressing these limitations and problems, the overall efficiency and performance of solar PV systems can be significantly improved, contributing to a more sustainable energy future.

Objective

The objective of this study is to improve the effectiveness of Maximum Power Point Tracking (MPPT) algorithms in solar photovoltaic (PV) systems by addressing the limitations of the existing Perturb and Observe (P&O) method with a PID controller. The proposed work involves integrating the Whale Optimization Algorithm (WOA) and Ant Lion Optimization Algorithm (ALO) to fine-tune a Fractional Order Proportional-Integral-Derivative (FO-PID) controller, aiming to enhance power output and efficiency. By utilizing a hybrid optimization technique, the study seeks to overcome the drawbacks of individual algorithms, reduce model complexity, and achieve better performance in solar PV systems.

Proposed Work

In the realm of solar photovoltaic (PV) systems, the Perturb and Observe (P&O) method with a PID controller has been utilized for MPPT, as demonstrated in a previous study by Ebrahim, Mohamed et al. (2019). While effective, there is room for improvement in maximizing power output and efficiency. The proposed project aims to enhance this method by incorporating a hybrid approach that combines the Whale Optimization Algorithm (WOA) and Ant Lion Optimization Algorithm (ALO) for tuning the FO-PID controller. By leveraging the strengths of these two optimization algorithms, the performance of the system can be further optimized.

To achieve this objective, the WOA algorithm is utilized to determine the gain parameters of the system to enhance its performance. However, the WOA algorithm alone has limitations such as poor exploration of the search space, high overshoot, and settling time. These drawbacks are addressed by replacing the PID controller with a Fractional Order Proportional-Integral-Derivative (FO-PID) controller and by incorporating a hybrid of WOA and ALO algorithms. By applying this hybrid optimization technique, the complexity of the model is reduced, and the system's performance is enhanced by fine-tuning the FO-PID controller. This approach is expected to overcome the limitations of the individual optimization algorithms and achieve better results in maximizing power output and efficiency in solar PV systems.

Application Area for Industry

This project can be effectively utilized in the renewable energy sector, specifically in the solar photovoltaic (PV) industry. By implementing the proposed solutions such as the Fractional Order Proportional-Integral-Derivative (FO-PID) controller and the hybrid of Whale Optimization Algorithm (WOA) and Ant Lion Optimization (ALO) Algorithms, industries can address the challenge of maximizing power output and enhancing efficiency in solar PV systems. The optimization of gain parameters using the FO-PID controller and the hybrid algorithm approach allows for improved system performance, reduced complexity, and faster response times. These solutions help overcome the limitations of traditional methods like the Perturb and Observe (P&O) Method and standard PID controllers, leading to more reliable and cost-effective solar energy generation. Furthermore, this project's proposed solutions can also benefit other industrial sectors that rely on optimization techniques for system control and performance enhancement.

Industries such as manufacturing, automotive, and aerospace can leverage the FO-PID controller and the hybrid algorithm approach to fine-tune their processes, reduce inefficiencies, and improve overall output quality. By adopting these advanced control strategies, businesses can achieve higher levels of productivity, operational efficiency, and cost savings, making the project's solutions versatile and beneficial across various domains.

Application Area for Academics

The proposed project can enrich academic research, education, and training in the field of solar photovoltaic (PV) systems by offering a novel approach to maximize power output and enhance efficiency. By incorporating the Fractional Order Proportional-Integral-Derivative controller (FO-PID) and a hybrid of Whale Optimization Algorithm (WOA) and Ant Lion Optimization Algorithm (ALO), researchers, MTech students, and PhD scholars can explore innovative methods for Maximum Power Point Tracking (MPPT) in solar PV systems. The utilization of FO-PID and the hybrid optimization algorithm not only enhances the system's performance but also addresses the limitations of previous methods, such as high overshoot and settling time. This project offers a comprehensive framework for optimizing solar PV systems, thereby contributing to the advancement of research in renewable energy technologies. The proposed work opens up opportunities for researchers to delve into the intersection of control theory, optimization algorithms, and solar energy systems.

By providing the code and literature on FO-PID and WOA-ALO hybrid optimization, this project equips academia with valuable resources for conducting cutting-edge research, developing simulation models, and analyzing data within educational settings. Future applications of this project could extend to various research domains, including renewable energy systems, control engineering, and optimization techniques. By leveraging the advancements in FO-PID and hybrid optimization algorithms, researchers can explore new avenues for improving the performance of solar PV systems and advancing the field of sustainable energy technologies. The potential scope for future research could involve further optimization of the hybrid algorithm, integration with other control strategies, and validation through experimental studies. This project sets the stage for ongoing research endeavors in enhancing the efficiency and reliability of solar PV systems, thereby contributing to the broader academic discourse on renewable energy solutions.

Algorithms Used

The project utilized a hybrid approach of the Whale Optimization Algorithm (WOA) and Ant Lion Optimization (ALO) Algorithms to enhance the optimization method. The Whale Optimization Algorithm was initially used to determine the gain parameters, but it had drawbacks such as limited exploration of the search space, high overshoot, and settling time. To address these issues, the Fractional Order Proportional-Integral-Derivative controller (FO-PID) was implemented instead of the PID controller. Additionally, the hybrid approach of WOA and ALO Algorithms was applied to overcome the drawbacks of WOA and streamline the model complexity by tuning the FOPID. This combination of algorithms played a crucial role in improving accuracy, efficiency, and overall performance in achieving the project's objectives.

Keywords

MPPT, solar PV, FO-PID controller, hybrid optimization algorithms, maximum power point tracking, solar energy, photovoltaic systems, renewable energy, energy efficiency, power optimization, control systems, fractional calculus, optimization techniques, intelligent algorithms, renewable energy integration, Perturb and Observe method, Proportional-Integral-Derivative controller, whale optimization algorithm, Fractional Order Proportional-Integral-Derivative controller, Ant Lion Optimization algorithm, PID controller tuning, power output enhancement, system efficiency, performance optimization, search space exploration, overshoot reduction, settling time improvement, model complexity reduction.

SEO Tags

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