首页|New Computational Intelligence Study Findings Have Been Published by Researchers at Aligarh Muslim University (Review of Computational Intelligence Approaches f or Microgrid Energy Management)
New Computational Intelligence Study Findings Have Been Published by Researchers at Aligarh Muslim University (Review of Computational Intelligence Approaches f or Microgrid Energy Management)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on computational int elligence are discussed in a new report. According to news reporting out of Alig arh, India, by NewsRx editors, research stated, “This research investigates impl ementing and optimizing microgrid energy management systems (EMS) utilizing arti ficial intelligence (AI). Inspired by the need for efficient resource utilizatio n and the limitations of traditional control methods, it addresses essential asp ects of microgrid design, such as cost-effectiveness, system capacity, power gen eration mix, and customer satisfaction.” Funders for this research include Taif University, Taif, Saudi Arabia. The news reporters obtained a quote from the research from Aligarh Muslim Univer sity: “The primary goals are to optimize energy management, control techniques, and AI applications in microgrids. The study critically examines the classificat ion of energy management systems, various EMS applications, and their associated challenges. Additionally, it discusses different optimization techniques releva nt to EMS, highlighting their applications, benefits, and challenges. The resear ch emphasizes the importance of hybrid systems, demand-side management, and ener gy storage in addressing the intermittency of renewable energy sources. AI techn iques, such as unsupervised learning (USL), supervised learning (SL), and semi-s upervised learning (SSL), are extensively analyzed in relation to their specific applications. The study explores AI-based hierarchical controls at primary, sec ondary, and tertiary levels. Furthermore, AI methods like deep learning for load forecasting and reinforcement learning for optimal control are emphasized for t heir substantial contributions to enhancing microgrid reliability and efficiency .”
Aligarh Muslim UniversityAligarhIndi aAsiaComputational IntelligenceEmerging TechnologiesMachine LearningSu pervised Learning
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