Enhancing Renewable Energy System Performance through Hybridization and Advanced Control Techniques using AmpliPity Algorithm and Hybrid Optimization with YSGA and Bat Algorithms

Problem Definition

The research aims to address the pressing issue of performance optimization in renewable energy systems, particularly focusing on enhancing power stability in hybrid systems that leverage various renewable sources like wind, solar, and hydro. One of the key challenges faced in this domain is the need to maximize the performance of these systems by improving power output efficiency. This can be achieved through the implementation of advanced control algorithms that can optimize energy production and distribution. Despite the advancements in renewable energy technology, there are still limitations and constraints that hinder the full potential of these systems. By tackling these limitations and developing innovative solutions, the research endeavors to contribute towards enhancing energy sustainability and promoting the widespread adoption of renewable energy sources.

Objective

The objective of the research project is to enhance the performance optimization of hybrid renewable energy systems by implementing advanced control algorithms. This includes stabilizing and maximizing power generation from systems utilizing wind, solar, and hydro energy sources. The study aims to evaluate the effectiveness of different controller algorithms on solar and wind power systems through the application of innovative techniques like the AmpliPity controller and optimization using the Yellow Saddle Godfish and BAT algorithms. The goal is to improve the stability and efficiency of renewable energy systems in order to promote energy sustainability and widespread adoption of renewable sources.

Proposed Work

The research project aims to address the performance optimization of renewable energy systems, particularly focusing on the power stability of hybrid systems powered by various renewable sources. By combining wind, solar, and hydro energy sources, the goal is to enhance the power output and overall efficiency of renewable energy systems through the implementation of advanced control algorithms. The main objective of the study is to stabilize and maximize power generation from hybrid renewable energy systems by utilizing different advanced control techniques on solar and wind power systems, and evaluating their performance transitions. To achieve the project's goal, an innovative approach has been proposed involving the hybridization of multiple renewable energy sources and the application of an advanced controller algorithm known as AmpliPity. Four different types of controllers, including P&O method MPPT, PD method with MPPT, P&I method, and PID MPPT, were designed for the study.

The optimization of the controllers was carried out using a combination of the Yellow Saddle Godfish algorithm and BAT algorithm. The performance of the optimized controllers was then tested in three distinct hybrid systems: Wind-Hydro, Solar-Wind, and Solar-Hydro. Various performance parameters such as THD, integral time scale error, overshoot, settling time, and rise time were analyzed to assess the effectiveness of the controllers in improving the stability and output of renewable energy systems. The project was implemented using MATLAB software for simulation and analysis purposes.

Application Area for Industry

This project's proposed solutions can be applied in various industrial sectors such as renewable energy, power generation, and sustainable development. By optimizing the performance of hybrid renewable energy systems using advanced control algorithms, industries can enhance energy sustainability and improve power stability. The challenges faced by industries include maximizing power output from various renewable energy sources such as wind, solar, and hydro while maintaining a consistent energy supply. Implementing the innovative approach of hybridizing different energy sources and using optimized controller algorithms can help industries overcome these challenges and achieve higher efficiency in their energy systems. Benefits of implementing these solutions include increased energy sustainability, improved power stability, and reduced reliance on traditional fossil fuels, leading to a more environmentally friendly and cost-effective energy production process.

Application Area for Academics

This proposed project can significantly enrich academic research, education, and training in the field of renewable energy systems optimization. By focusing on improving the performance of hybrid systems powered by various renewable energy sources, such as wind, solar, and hydro, this research can contribute valuable insights into maximizing power stability and energy sustainability. The utilization of advanced control algorithms, such as the AmpliPity controller, in conjunction with the optimization techniques of YSGA and Bat algorithms, offers a novel approach to enhancing the power output of renewable energy systems. The development and analysis of different controller types (P&O method MPPT, PD method with MPPT, P&I method, and PID MPPT) in various hybrid systems (Wind-Hydro, Solar-Wind, and Solar-Hydro) provide a comprehensive understanding of how these systems can be optimized for improved performance. The use of MATLAB software and the integration of these advanced algorithms offer a platform for researchers, MTech students, and PhD scholars to explore innovative research methods, conduct simulations, and perform data analysis within educational settings.

The code and literature generated from this project can be utilized by field-specific researchers and students to further their own work in the domain of renewable energy systems optimization. The relevance of this research lies in its potential applications for real-world energy systems and the development of sustainable energy solutions. By investigating performance parameters such as THD, Integral time scale error, Integral time absolute error, Overshoot, Settling time, and Rise time for the optimized controllers, this project can provide valuable insights into improving the efficiency and stability of renewable energy systems. In terms of future scope, the project can be expanded to include more complex hybrid systems, incorporate additional control algorithms for comparison, and explore the integration of other renewable energy sources. This research has the potential to drive innovation in the field of renewable energy systems optimization and contribute to the development of more sustainable energy solutions for the future.

Algorithms Used

The main algorithms used in this project include the AmpliPity algorithm, Yellow Saddle Godfish Algorithm (YSGA), and Bat algorithm. AmpliPity algorithm was utilized to stabilize and maximize power output in the hybrid renewable energy systems. The YSGA and Bat algorithms were integrated to optimize the gains and performance of the four controllers designed in the study, namely P&O method MPPT, PD method with MPPT, P&I method, and PID MPPT. These algorithms were implemented using MATLAB software to enhance the accuracy and efficiency of the controllers in the hybrid systems. The proposed work focused on hybridizing different renewable energy sources and employing the innovative AmpliPity controller algorithm.

The optimization of the controllers was carried out using a hybrid of YSGA and BAT algorithms to improve their performance. The performance of the optimized controllers was evaluated in three hybrid systems: Wind-Hydro, Solar-Wind, and Solar-Hydro. Various performance parameters such as Total Harmonic Distortion (THD), Integral time scale error, Integral time absolute error, Overshoot, Settling time, and Rise time were analyzed to assess the effectiveness of the controllers in enhancing the overall system efficiency.

Keywords

SEO-optimized keywords: Renewable Energy, Hybrid Energy Systems, Power Stability, Wind Energy, Solar Energy, Hydro Energy, Controller Techniques, AmpliPity, MATLAB, Optimization Algorithm, YSGA, BAT Algorithm, PID Controller, MPPT, P&O method, PD method, P&I method, THD, Integral time scale error, Overshoot, Settling time, Rise time.

SEO Tags

Renewable Energy, Hybrid Energy Systems, Controller Techniques, YSGA, BAT Algorithm, AmpliPity, MATLAB, Power Stability, Wind Energy, Solar Energy, Hydro Energy, Optimization Algorithm, PID Controller, MPPT, PD Method, Performance Optimization, Renewable Energy Sources, Advanced Control Algorithms, Hybrid Systems, Renewable Energy Efficiency, Renewable Energy Sustainability, THD Analysis, Integral Time Scale Error, Overshoot Analysis, Settling Time Analysis, Rise Time Analysis, Hybrid Renewable Energy Systems.