Song Zhang, Ph.D., SMIEEE

Song Zhang (IEEE S'13 M'14 SM'20) is from Chengdu, China. He received his Ph.D. degree from Arizona State University in 2014. Song is now a Senior Solution Architect and Grid Solution Leader at Amazon Web Services, the Energy and Utilities Industry Business Unit (IBU). Before joining AWS, Song was an R&D lead analyst and a Cloud CoE Lead at ISO New England, where he led multiple cloud adoption projects and took charge of cloud application and infrastructure design of current cloud product for planning studies. Song had also worked with Alstom Grid (now GE Grid Solutions) from 2014 to 2017. Song's primary research interests include power system optimal control, power system operations, power system stability and dynamics. He is a domain expert in cloud solution architecting, cloud center of excellence and power utility customer insights.

In addition to traditional power system topics, Song also has interest in applying emerging technologies such as Cloud Computing, Big Data, Machine Learning and Internet of Things (IoT) to resolve new challenges in smart grid. He led a project at the ISONE which built a hadoop-based scalable big data analytics platform to process massive volume of historical data, including PMU data, SCADA data, market data and weather data. The cloud computing platform Song is currently managing at the ISO allows engineers to access unlimited computing resources on the cloud to meet the ever-growing demand of computational-intensive power system simulations. For example, transmission planning and resource adequacy analysis require a large number of PSS/E simulations. Tie Benefits and Installed Capacity Requirement (ICR) are determined through sequential Monte Carlo simulations which are very time-consuming. With this cloud platform, these compute-intensive simulation jobs can be completed in a reasonable amount of time, usually a couple of hours, at a cost-effective way (several dollars per hour), compared to hundreds of hours on a PC or tens of hours on a on-premises cluster with long queuing time.

Dr. Song Zhang has been specialized in power system engineering research and development for over 10 years. He has rich experience in modeling, simulation, analysis of large power system networks, optimal control design for nonlinear systems, cloud computing, big data analytics, data-driven approaches, and development of large scale commercial software packages. Up to now, Dr. Zhang has published 30+ papers with more than 700 total citations. He had won the "Best Paper Award" in IEEE PES General Meeting for three times, one of which was rated as the "highly-cited paper" by Web Of Science. Besides, Dr. Zhang has been the recipient of ISO New England's top award "CEO Innovation Award" in 2019 and 2020.

As a pioneering cloud user in power engineering area, Song is an AWS Certified Solution Architect (Associate). He founded IEEE PES Task Force "Cloud Computing for Power Grid Operation, Planning, Monitoring and Control" and is currently chairing it. He also serves as the chair of IEEE Region 1 PES Springfield Chapter. He is an editor of IEEE Transactions on Smart Grid and CSEE Journal of Power and Energy Systems (an IEEE and CSEE co-sponsored journal). In the meanwhile, he serves as a reviewer of multiple prestigious journals and conferences in power system and control area, including IEEE Transactions on Power Systems, IEEE Transactions on Power Delivery, IEEE Transactions on Smart Grid, IET Generation, Transmission & Distribution, IET Control Theory & Applications, Electric Power System Research, Electric Power Components & Systems, IEEE PES General Meeting, IEEE T&D Exposition Conference, and etc. In March 2015, he was awarded by IEEE PES with the honor of "outstanding reviewer" for his extraordinary reviewing service. 

Song has one granted patent since 2010. As the co-inventor of the patent "Ultra-fast HVDC Line Protection using Transient Signals" (CN101777759B), he led a team in Xuji Electric Group (a SGCC company) and successfully developed the prototype of transient-based boundary protection. This groundbreaking work was later submitted to IEEE Transactions on Power Delivery and soon accumulated a lot of followers. The novel protection developed by him has saved the utilities up to 1.5 million dollars annually on HVDC projects owing to the decrease of power outage duration.

If you're interested in any project Song is working on or just want to be connected with him, please feel free to join his network on LinkedIn