Hybrid Optimization for Economic Load Dispatch in Microgrids Using Chaotic Maps and WOA

Problem Definition

The economic load dispatch (ELD) problem in power generating systems has been a major concern for researchers due to its non-linear nature and the incorporation of renewable energy sources (RES) to reduce environmental pollution. Traditional calculation-based solutions have struggled to handle the complexities of the ELD problem, leading to the exploration of stochastic-based optimization methods. However, the plethora of optimization techniques available makes it challenging to select the best algorithm, and the slow convergence rate of most algorithms hinders system accuracy. Additionally, the increased processing and computational time of traditional ELD models further impacts performance. To address these limitations, an improved ELD model is necessary to reduce fuel costs, harmful emissions, and enhance power system efficiency.

Objective

The objective of this research is to develop an innovative approach for multi-objective economic emission dispatch in microgrids by integrating renewable energy sources and utilizing the Chaotic Map and Whale Optimization Algorithm (WOA). This hybrid approach aims to optimize system performance by reducing fuel costs and emissions while meeting the overall demand for power. Additionally, the research extends to target Economic Dispatch (ED) and Combined Economic Emission Dispatch (CEED) in microgrids to enhance system efficiency and contribute to environmental sustainability. The utilization of WOA with chaotic maps is intended to improve convergence rate, stability, and initial population outcomes for optimizing power systems. Through the assessment of the proposed ELD model's performance in isolated microgrids, the research aims to provide a comprehensive solution for economic load management in power systems and establish a more efficient and sustainable energy system.

Proposed Work

In response to the identified gap in the literature regarding the Economic Load Dispatch (ELD) problem in power systems, the proposed work aims to address the challenge by integrating renewable energy sources (RES) to reduce harmful emissions and enhance system efficiency. By combining the Chaotic Map and Whale Optimization Algorithm (WOA), the objective is to develop an innovative approach for multi-objective economic emission dispatch in microgrids. The use of WOA along with chaotic maps is justified by their complementary characteristics, such as fast convergence rate and stable exploration and exploitation, which are essential for resolving the non-linear nature of the ELD problem. Through this hybrid approach, the proposed model seeks to optimize the system performance by reducing fuel costs and emissions while meeting the overall demand for power. Moreover, the proposed work extends beyond just addressing the ELD problem by also targeting Economic Dispatch (ED) and Combined Economic Emission Dispatch (CEED) issues in microgrids.

By incorporating the renewable energy systems like wind and solar, the aim is to enhance the overall system efficiency and contribute to environmental sustainability. The utilization of WOA with chaotic maps not only helps in improving the convergence rate and stability but also aids in achieving better initial population outcomes for optimizing the power system. Through the assessment of the proposed ELD model's performance in isolated microgrids with conventional generators and renewable energy systems, the research will contribute towards developing a comprehensive solution for economic load management in power systems. Ultimately, the proposed work seeks to establish a more efficient and sustainable energy system by utilizing nature-inspired optimization techniques and innovative approaches to tackle the complex challenges associated with ELD in power generation.

Application Area for Industry

This project can be used in various industrial sectors that heavily rely on power generating systems, such as the energy sector, manufacturing sector, and transportation sector. The proposed solutions in this project can be applied within different industrial domains to address specific challenges faced by industries. For example, the integration of renewable energy sources (RES) in power systems can help reduce the environmental pollution caused by conventional power generation methods, benefiting industries by lowering harmful emissions and overall costs. The use of stochastic-based optimization methods, such as the Whale Optimization Algorithm (WOA) combined with chaotic maps, can improve the efficiency of power systems in industries by addressing the Economic Load Dispatch (ELD) problem, reducing fuel costs, and enhancing system performance. By implementing these solutions, industries can achieve better operational efficiency, reduce their environmental impact, and meet their energy demands more effectively.

Application Area for Academics

The proposed project focusing on resolving Economic Load Dispatch (ELD) issues in power generating systems has significant potential to enrich academic research, education, and training in the field of renewable energy systems and optimization techniques. By incorporating the Whale Optimization Algorithm (WOA) along with chaotic maps, this research offers a novel approach to addressing the challenges associated with ELD, Economic Dispatch (ED), and Combined Economic Emission Dispatch (CEED) problems in microgrids. This project can serve as a valuable resource for researchers, MTech students, and PhD scholars working in the field of energy systems and optimization. The code and literature generated from this project can be used to explore innovative research methods, simulations, and data analysis techniques within educational settings. By utilizing stochastic-based optimization methods and nature-inspired algorithms, such as WOA and chaotic maps, researchers can enhance the efficiency of power systems while reducing costs and harmful emissions.

Moreover, the application of renewable energy sources, such as wind and solar energy, in the proposed ELD model demonstrates the relevance and potential impact of this research in promoting sustainable energy practices. Researchers in the specific domain of renewable energy systems can leverage the insights and methodologies proposed in this project to advance their own studies and contribute to the development of cleaner and more efficient energy systems. In conclusion, the proposed project not only addresses the critical issue of ELD in power systems but also opens up opportunities for further research and application of advanced optimization techniques in the field of renewable energy. The integration of WOA and chaotic maps offers a promising approach to improving system performance and sustainability, making this project a valuable asset for academic research, education, and training in the area of energy systems optimization. Future Scope: The future scope of this project includes expanding the application of WOA and chaotic maps to other optimization problems in renewable energy systems, as well as incorporating additional renewable energy sources for more comprehensive analysis.

Further research could explore the integration of machine learning algorithms for enhanced optimization and decision-making in microgrid systems. Additionally, collaborating with industry partners to implement and validate the proposed ELD model in real-world microgrid scenarios would be a key step towards practical applications of this research.

Algorithms Used

In this research project, an improved and hybrid approach is proposed for resolving Economic Load Dispatch (ELD), Economic Dispatch (ED), and Combined Economic Emission Dispatch (CEED) problems in microgrids. The Whale Optimization Algorithm (WOA) is used along with a chaotic map to optimize the system. The WOA addresses slow convergence rate issues, while the chaotic map provides better initial population outcomes. By combining these approaches, the system efficiency is improved, costs are reduced, and overall demand is met. The ELD model's performance is assessed for isolated microgrids with conventional generators, wind energy systems, and solar energy systems to reduce fuel costs and harmful emissions.

Keywords

SEO-optimized keywords: Economic Load Dispatch, ELD, Renewable Energy Sources, RES, Environmental Pollution, Stochastic Optimization, Optimization Techniques, Convergence Rate, Computational Time, Efficiency Enhancement, Hybrid Approach, Economic Dispatch, Economic Emission Dispatch, Microgrids, Harmful Emissions, Fossil Fuels, Whale Optimization Algorithm, WOA, Chaotic Map, Renewable Energy System, Energy Management, Power Generation, Energy Efficiency, Power Electronics, Emission Reduction, Sustainable Energy, Hybrid Algorithms, Energy Costs, Energy Emission Balance.

SEO Tags

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