A recent Ph.D. graduate from the Georgia Tech School of Electrical and Computer Engineering (ECE), Zhang worked in the Advanced Computational Electricity Systems (ACES) Lab, which is led by ECE Professor Santiago Grijalva.

Zhang received this award for his paper entitled “A Fast Quasi-Static Time Series (QSTS) Simulation Method for PV Impact Studies Using Voltage Sensitivities of Controllable Elements.” His coauthors on the paper are Grijalva, who holds the Georgia Power Distinguished Professorship; Jeremiah Deboever, a Ph.D. student in the ACES Lab; and Matthew Reno and Robert Broderick of Sandia National Laboratories in Albuquerque, New Mexico. Zhang currently works at Sapientrazorfish as a data scientist. 

Solar energy is booming in the United States. As the adoption of solar panels continues to grow, uncoordinated solar energy integration could lead to disastrous consequences to the traditional grid. As a result, it is critical to perform a thorough impact study of all potential solar system adoptions beforehand, which currently is computationally very expensive.

The research published in this paper proposes a novel linearized model of the power grid, which significantly reduces the computational time for solar system impact studies. The proposed model not only makes rigorous solar impact study computationally feasible, but also provides researchers a more intuitive understanding of how power grid elements work in practice.