Proving the Business Case for the Internet of Things

NSF funds Penn State engineer to design smart power grids

Steve Rogerson
August 9, 2016
An assistant professor at Pennsylvania Sate University has received $235,852 from the National Science Foundation to design smart power grids that factor in uncertainty in energy demand and renewable energy production.
Necdet Serhat Aybat is an assistant professor of industrial engineering and the principal investigator on the three-year project looking at decentralised power flow optimisation on electricity grids via distributed consensus methods.
The project is aimed at solving important dynamic problems with uncertain parameters that currently exist in energy production and distribution. The grids are intended to run efficiently in a decentralised manner while respecting the data privacy requirements of each grid note.
There already exists a massive amount of untapped intelligence in the form of computation resources such as smart meters, solar inverters and smart thermostats imbedded in the grid, explained Aybat.
“Through this research, we will be leveraging existing grid hardware that is capable of simple local computation and passing messages to neighbouring devices,” he said. “The goal is to develop a decentralised system that will use this distributed intelligence as a super computer to solve grid challenges more economically than the traditional central computing infrastructure.”
According to a 2015 report by the US Advanced Research Projects Agency-Energy, increasing the amount of renewables in the energy sector from 30 to 50 per cent by using new controls for grid stability can reduce the amount of consumed energy by 3.2 to 3.5 BTUs, and can reduce carbon dioxide emissions by between 290 and 315Mtons. However, renewable energy sources particularly wind are not correlated with the load, thus there is a need for dynamic response systems to stabilise the power system optimally to changes in the load.
“There are millions of smart meters deployed through the USA that sit idle over 90 per cent of the time,” said Aybat. “Thus, we know there is sufficient computation power without occupying additional land or powering and cooling new server farms or data centres. Knowing all this, it is my hope to develop techniques to enable greater renewables penetration while maintaining grid resiliency through dynamic decentralised control of energy storage and regulator devices.”
Nearly ten per cent of energy produced by power plants is lost in transmission and distribution, explained Aybat, so if successful this project could lead to significant energy savings and emission reductions in the power sector.
“This innovation strengthens grid security and resiliency, for when computation is distributed to the network, rather than in a central server, there is no single point of attack or failure,” he said.
The techniques developed in this project will help maintain grid reliability without having to burn more fossil fuel as backup, and in effect turn the smart grid into its own backup via intelligent control of the capacitor banks. This will lead to deeper integration of renewables and contribute to the reliable, robust and privacy-enabled operation of a stable power grid through the development of scalable computational tools for control and optimisation.
Industrial engineering graduate students Erfan Yazdandoost Hamedani, Zi Wang and Jinwei Zhang are assisting on the project.
A researcher at the University of California, Riverside’s Bourns College of Engineering has been awarded a $1.2m grant from the California Energy Commission to help the state meet its goal of adding 20GW of renewable power generation by 2020. Nanpeng Yu, an assistant professor of electrical and computer engineering, received the three-year grant to develop advanced technologies for the smart grid.