Optimizing Solar Panel Output With An AI-Driven Approach In Grid Staion Design

Objectives

Aims and Objectives 1) To monitor and analyze the power system accurately. 2) To Analyze the Load flow analysis, short circuit analysis, Transient analysis, and Arc flash analysis. 3) To determine grounding design of grid. 4) To expand the substations in future demand. 5) To overcome the under voltage problem. 6) To integrate renewable energy sources, such as solar panels, into the grid station's infrastructure. 7) An important objective is to apply economic merit order principles to optimize energy costs and maximize economic benefits.

Socio-Economic Benefit

Socio-Economic Benefits: Increased Energy Efficiency: By optimizing solar panel output, the project ensures more efficient use of renewable energy, reducing dependency on fossil fuels and lowering greenhouse gas emissions. Cost Savings: Improved efficiency and load flow management lead to reduced operational costs and lower electricity prices for consumers. Enhanced Grid Stability: The load flow analysis of the 132kV Musazai Grid Station helps in identifying and mitigating potential issues, ensuring a stable and reliable power supply. Job Creation: The implementation and maintenance of advanced AI-driven systems and solar technologies create new job opportunities in the tech and renewable energy sectors. Environmental Sustainability: By maximizing the use of solar energy, the project supports sustainable development goals, contributing to a cleaner and healthier environment. Economic Growth: Reduced energy costs and improved grid reliability attract businesses and industries, fostering economic growth in the region. Energy Security: Diversifying the energy mix with optimized solar power enhances energy security and resilience against supply disruptions. Technological Advancement: The project promotes the adoption of cutting-edge AI and renewable energy technologies, positioning the region as a leader in innovative energy solutions.

Methodologies

Data Collection From PESCO ETAP Modeling Single Line Diagram Formation Load Flow Analysis Arc Flash Analysis Relay Coordination Grounding Of the Grid Station Solar injection Grid formation MATLAB Code For Future Prediction of Irridiance Using AI tools

Outcome

Project Outcomes: The project significantly improved solar panel efficiency through AI-driven optimization, leading to lower operational costs and consumer savings. Enhanced grid stability was achieved via comprehensive load flow analysis, ensuring reliable power supply. Environmental benefits included reduced greenhouse gas emissions and decreased reliance on fossil fuels. The project stimulated economic growth by creating jobs and attracting businesses due to stable, cost-effective power. Technological advancements were made in AI and machine learning for energy optimization. Energy security was bolstered with a diversified and resilient energy mix. The project provided a scalable, replicable model for other regions, engaged stakeholders through detailed reporting and training, and established a continuous improvement system for long-term sustainability.

Project Team Members

PROJECT GALLERY

Optimizing Solar Panel Output With An AI-Driven Approach In Grid Staion Design

27 May, 2024 11:45 pm