Technical Webinars: Electrical & Electronic Engineering - Data Centric Evolving Power Grid (repeat)

The privatized renewables-driven distributed grid is moving away from a utility-centric architecture and towards an end user-centric architecture. This shift is not going to be limited to any single segment or sub-sector. It is going to be much broader and even potentially total, simultaneously affecting several seemingly disparate segments. The future power grid is going to be “multilateral.” The delivery in and out of the grid is going to get more complicated: utilities and developers needed to place solar or wind onto the most appropriate nodes, industrial customers need to understand which of their sites are most suitable for renewables and, more and more individuals will be placing solar panels on their rooftops and parking an EV in their garages. All these different actors would need to communicate with each other, trade with each other. and ultimately, balance each other so that the grid would be able to continue to function reliably. The coal- and gas-fired generation will be replaced by renewables and the core issue with renewables, is intermittency; the sun doesn’t always shine and the wind doesn’t always blow. All of a sudden, the power sector would need to become a lot better at the weather forecasting business. This requires highly sophisticated – not generic – AI and machine learning software. Likewise, on the demand side, the coming wave of EVs – even if, realistically, it might need to wait until sufficient charging infrastructure is built – is introducing an entirely new and volatile source of demand. As sources of both supply and demand increasingly fragment, participants need to look outside of their own organizations to collate and make sense of these new data streams in real-time. No one player holds all the cards anymore: that’s the nature of the multilateral grid. This is thus heavily reliant on first generating the most comprehensive data and analytics possible. Key takeaways: - Customer and data-centric design - Energy Transition - Data analytics, probabilistic modeling, and real-time risk-limiting control Presenter: Professor Akhtar Kalam, EIT Academic Board Deputy Chair BSc, BScEng, MS, PhD, FIET, CEng, FAIE, FIEAust, CPEng, NER, APEC Engineer, IntPE(Aus), PEV, MCIGRE, Life Senior Member of IEEE. __ The Engineering Institute of Technology (EIT) is one of the only institutes in the world specializing in Engineering. We deliver industry-focused professional certificates, diplomas, advanced diplomas, undergraduate and graduate certificates, bachelor’s and master’s degrees, and a Doctor of Engineering to students from over 140 countries. -- FOLLOW US! Website: www.eit.edu.au Instagram: www.instagram.com/eit_engineering_training Facebook: www.facebook.com/EngineeringInstituteofTechnology LinkedIn: www.linkedin.com/school/engineering-institute-of-technology Twitter: https://twitter.com/enginstoftech -- All content in this video is current as of the date of upload. -- EIT CRICOS Provider Number: 03567C | EIT Institute of Higher Education: PRV14008 | EIT RTO Provider Number: 51971 -- #eit #engineeringinstituteoftechnology #engineering #engineeringstudent #studyengineering #renewableenergy #distributedsystems #powersector #energymanagement