Intermittent renewable sources (wind and solar), electric vehicles, and smart loads will vastly change the behavior of the world’s biggest machine, the electric power grid.
Renewable energy sources like wind and solar farms are providing carbon-free energy and increasing flexibility for utility customers. Electricity uses become active and smarter to help the customers for energy savings, and the grid for better reliability and efficiency. However, the intermittent productivity of renewable energy and the unpredictable nature of electricity uses are introducing new challenges to an aging electric grid.
The growing penetration of renewables and consumer participation for smart, flexible energy choices leads to new dynamics and uncertainties that need to be included in planning for power grid expansion over a time horizon of decades. The current practice is to use a larger margin to accommodate dynamics and uncertainties, which leads to unnecessary conservativeness and cost in the annual asset investments of $6–19 billion.
The increasing pace of power grid modernization drives the urgency of solving such an expansion problem cost-effectively and securely within the next decade. To create models that can analyze data from the world’s largest machine—the electric grid—researchers need exascale computing power for decades-long expansion planning, so as to enable the cheapest, most reliable mix of energy generation and uses.