Urban/Community Hybrid Renewable Energy Solutions - Optimization Models and Data Analytics for Design, Configuration, and Operation

Explore optimization models and data analytics for designing, configuring, and operating hybrid renewable energy systems in urban and community settings through this 59-minute research seminar. Examine how hybridizing renewable energy sources like wind, solar, biomass, hydrogen, and geothermal can improve economy of scale and reliability by diversifying energy contributions. Learn about the challenges of renewable energy transition, including intermittency issues and cost efficiency concerns for smaller-scale installations. Discover how hybrid solutions become particularly viable in urban environments with stable grid backup and community-scale implementations that can incorporate larger energy storage systems. Analyze recent developments in optimization modeling for system design, configuration, sizing, scheduling, and control of integrated renewable energy systems that include backup solutions such as urban grids, energy storage technologies, and diesel or natural gas generators and boilers. Study various urban and community load types including power, heating, and cooling requirements. Gain insights into system design characteristics, optimization problem notation, and result analysis and interpretation for each case study presented. Understand how data analytics enhances the performance and efficiency of these complex hybrid renewable energy systems in real-world applications.