Model Future: Optimized Electric Power System Planning

Renewable energy offers promise for cleaner, cheaper electricity, but the variability in its production levels introduces new levels of uncertainly into the electric power system. Sarah Ryan, Joseph Walkup Professor in Industrial and Manufacturing Systems Engineering, is developing new stochastic optimization techniques to help electric system operators effectively plan for deeper integration of renewables.

More renewables, more uncertainty

Introducing wind and solar generation into electrical grids also introduces a new level of day-to- day uncertainty about tomorrow’s weather and energy generation.

“When the amount of electricity generated by renewables was small, it was good enough to merely do conventional capacity scheduling and build in a small margin in case the wind wasn’t blowing or the sun didn’t shine,” said Ryan. “But as the amount of renewables in the electric system grows, so does the necessity for data-driven optimization that accounts for forecast uncertainty.”

Ryan is developing new models that consider a number of different energy-generation scenarios and optimizations based on the level of uncertainty.

“We classify historical weather data and see patterns in different sets of historical days that have different levels of uncertainty associated with them,” said Ryan. “One major challenge is figuring out the ideal number of scenarios to consider in a model to ensure accuracy while finding a solution fast enough for use by utility operators on a day-to-day basis.”

Long-term planning

Long-term electric generation and transmission capacity planning contends with significant uncertainties in changing fuel sources, costs and policy, in addition to new uncertainty associated with renewables.

Ryan is using improvements in both computing power and software tools to optimize long-term planning for the integration of electrical systems with other forms of energy. She recently examined the risk associated with electric power systems becoming increasingly dependent on natural gas fuel sources, and how that risk relates to the expanded use of renewable energy sources.

Ryan is using improvements in both computing power and software tools to optimize long-term planning for the integration of electrical systems with other forms of energy. She recently examined the risk associated with electric power systems becoming increasingly dependent on natural gas fuel sources, and how that risk relates to the expanded use of renewable energy sources.

Preparing tomorrow’s food-energy-water systems experts

DataFEWsion infographic

Iowa State is home to a new National Science Foundation traineeship program preparing the next generation of food-energy-water (FEW) systems innovators. Open to both masters and Ph.D. students, the DataFEWSion program offers a unique focus on data-rich systems modeling at the intersection of energy transformation, water management, and cropping and livestock systems.

Faculty members from industrial and manufacturing systems engineering, agricultural and biosystems engineering, aerospace engineering, mechanical engineering, agronomy, economics, sociology and natural resource ecology and management will come together to prepare students for careers in research, policy making and bioeconomy entrepreneurship.

“Iowa State is a land grant university with a longtime strength in both agriculture and engineering – and valuable collaborations among experts in different aspects of FEW systems. It makes Iowa State the place to be if students are interested in any type of FEW career,” said Sarah Ryan, Joseph Walkup Professor in Industrial and Manufacturing Systems Engineering, who leads the DataFEWSion program. “We’re looking forward to our first cohort of students starting this valuable interdisciplinary experience later this year.”