Artificial Intelligent Intervention to Urban Building Renewable Energy Modeling for Robust Energy Flexible Communities
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This research coveys a comparative analysis between Urban Building energy model (UBEM) generated by scholar, researchers, and professional in academia and industry while highlighting the reliable main components to manifest a successful and reliable UBEM technologies. Nevertheless, it consolidates distributed generation on building blocks rather than a whole district relying on renewable energy sources. It guides engineers through energy system model simulation on Openmodelica platform to feed green sustained communities. Moreover, energy use-pattern is mapped and analyzed by internet of things (IOT) technologies to fine-tune energy uses and refine use-pattern. Demonstrating artificial Intelligence (AI) algorithmto predict energy consumption can reflect on the amount of energy required for storage to cover energy needs. AI shapes a robust positive energy district (PED) through storinggenerated renewable solar or bio-energy to cover predicted energy use-pattern.Distributed -power-plant stations capacity to cover clusters using AI in predicting energy consumption consolidates on-site energy generation recommended by multiple International rating systems. AI-based Energy management plan guide engineers and planners to design distributed-power-plants of energy generation capacity lies between the actual energy need and a predicted scenario.
[Sammar Z. Allam (2021); Artificial Intelligent Intervention to Urban Building Renewable Energy Modeling for Robust Energy Flexible Communities Int. J. of Adv. Res. 9 (Mar). 314-321] (ISSN 2320-5407). www.journalijar.com
October University for Modern Sciences and Arts - SHM Studio 16 (Green Scope)
Egypt