Washington State University

04/10/2024 | News release | Distributed by Public on 04/10/2024 07:05

Grant supports helping the power grid prepare for the future

A Washington State University-led research team has been selected to receive a $2.4 million U.S. Department of Energy (DOE) grant to better prepare the power grid for the changing world of electricity production, including the increasing use of renewable power and the increase in extreme weather events related to climate change.

As part of the project, the researchers are developing open-source planning tools for modeling the complexities and uncertainties that come about from the use of renewables and from extreme weather events. The project, funded through the DOE's Solar Energy Technologies Office, is led by Mani Venkatasubramanian, Boeing Distinguished Professor of Electrical Engineering in the WSU School of Electrical Engineering and Computer Science and director of the Energy Systems Innovation Center. Collaborators include researchers from Iowa State University and Southwest Power Pool (SPP), a regional transmission organization (RTO) that manages the electric power grid across 14 states in the central U.S.

As the world tries to move away from fossil fuels because of their harmful climate impacts, power grid operators are planning for and seeing significant changes in the grid's management. The cost of renewable energy production has dropped dramatically in recent years so that solar and wind power are now the cheapest and most attractive ways to produce electricity. But renewables, unlike fossil fuels, provide variable amounts of energy during the day and are often distributed around a region instead of being centralized. In the region managed by SPP, power generation is currently powered primarily by natural gas, wind, and coal with solar capacity expected to grow rapidly in the next 10 years.

"Massive integration of inverter-based variable renewable energy and distributed energy resources, specifically photovoltaic and wind generation, is picking up pace in power grids on a global scale," said Venkatasubramanian, who also holds a joint appointment at Pacific Northwest National Laboratory. "This is posing serious challenges to planning and operation of the power system."

At the same time, power grid operators have to contend with more stress on the power grid due to extreme weather events. There has been a 67% increase in power outages since 2000 due to extreme weather, such as extreme heat, flooding, wildfires, or high-wind events. Extreme cold spells, such as one that occurred in Texas in 2021, have had disastrous consequences.

"Existing planning tools are not adequate for representing the uncertainties introduced by renewables and the high impact-low-probability extreme weather events posed by climate change," he said.

As part of the project, the research team will use stochastic optimization, artificial intelligence and machine learning methods in their tools to better manage uncertainty and optimize complex power grid planning of the future. Using AI will speed up computation and better model uncertainties. The researchers will also begin fully integrating climate datasets into power grid models.

"The work will provide a framework for stakeholders to make better planning decisions and to develop resilience," said Venkatasubramanian.

The project includes workforce development, including paid internships with project partners, undergraduate research opportunities, and integration of the work into undergraduate courses and training materials.

"This research effort is extremely timely as it aligns with the ongoing work of identifying the rapidly evolving needs of the industry," said Sunny Raheem, SPP Manager of Planning Policy. "SPP looks forward to supporting this proposal and its goal of developing emerging technology and cutting-edge tools to better manage uncertainty and planning as we look toward the grid of the future."

The researchers hope that their planning tools and algorithms will be ready in three years for a field demonstration and commercial-ready software that can be adopted by the power grid industry.