Renewable energy forecasting is a crucial aspect of optimizing the integration of sustainable energy sources into the power grid. It involves predicting the output of renewable resources like solar and wind, enabling efficient grid management. Advanced meteorological models and data analytics are employed to anticipate fluctuations in energy production, aiding in grid stability. Accurate forecasting enhances the reliability of renewable energy sources, allowing utilities to balance supply and demand effectively. It enables better integration of renewable energy into the grid, reducing the reliance on traditional fossil fuel-based power plants and lowering carbon emissions. Real-time monitoring and forecasting technologies help energy operators anticipate variations in wind speed, solar irradiance, and other factors affecting renewable generation. This information allows for proactive grid adjustments and ensures a steady and reliable energy supply. Renewable energy forecasting supports energy market participants in making informed decisions, optimizing energy trading, and managing energy storage systems. It also facilitates the planning of maintenance activities for renewable infrastructure, ensuring optimal performance. As the world transitions to cleaner energy sources, accurate forecasting becomes increasingly vital for creating resilient and sustainable energy systems. It contributes to the overall stability of the power grid and accelerates the global shift towards a greener and more sustainable energy future.
Title : Local actions, global impact: Community-centered approaches to green chemistry and renewable energy for sustainability
Helena Belchior Rocha, ISCTE-Institituto Universitario de Lisboa, Portugal
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Title : Quinazolines: Green synthesis, characterization and biological activities
Jenifer Robinson, Indian School Alwadi AL Kabir, Oman
Title : Green synthesis and application of a bio emulsion liquid membrane (bio elm) for wastewater pollutant extraction
Manisha Wakle, Ahmedabad University, India
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Tshifhiwa Masikhwa, Necsa – South African Nuclear Energy Corporation, South Africa
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Supriya Santosh Patil, MES Abasaheb Garware College, India
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Asmaa S Morshedy, Egyptian Petroleum Research Institute, Egypt
Title : Chemistry control of peach fruit moth and agriculture high-quality development
Zhongsheng Guo, Northwest A&F University, China
Title : An explainable multi-agent AI framework for sustainable autonomous mobility and electric grid integration
Abhinav Tiwari, York University, United States