Tackling Daily and Long-Term Grid Challenges
The effort aims to solve two distinct but connected problems — grid operators’ ability to smoothly shift operations when clouds or changing winds impact renewable energy outputs, and planners’ long-term decisions on how to balance renewables and other power sources in expanding the grid to meet increasing demand.
Risk Allocation Insights from Finance to Energy
Banks are required to report risk measurements for sets of investments — for example, that they have a 5% probability of losing $200 million overnight — and to attribute that risk to specific assets or traders. “That’s the risk allocation problem,” said Ronnie Sircar, Princeton University’s Eugene Higgins Professor of Operations Research and Financial Engineering (ORFE). Similarly, the Princeton University team’s system can calculate a power grid’s risk of failure, determine which sources contribute most to that risk, and guide both the daily and long-term reallocation of power sources to minimize the risk.
Groundbreaking Support and Research Tools
Led by Sircar and ORFE professor René Carmona, the effort has been funded by a five-year, $4.25-million grant from the Advanced Research Projects Agency – Energy (ARPA-E), a division of the U.S. Department of Energy that supports early-stage energy technology development. The researchers call their project ORFEUS, for Operational Risk Financialization of Electricity Under Stochasticity, an acronym echoing that of the ORFE department. Stochasticity is a term describing systems where changing conditions are extremely challenging to predict.
Sophisticated Modelling for Future Energy Scenarios
Carmona and former postdoctoral research associate Xinshuo Yang (now a quantitative strategist at Goldman Sachs) created a simulation engine that combines high-resolution weather forecasts with localized hourly data on the Texas energy grid’s production and demand during 2017 and 2018, and produces realistic scenarios of what to expect in the future. This data was made available by the National Renewable Energy Laboratory as part of the ARPA-E PERFORM program, which supports modernization of grid reliability through risk management strategies.
From Simulation to Practical Grid Management
The team used these scenarios as a test case to develop measurements of system-level risk in the grid and attribute risk levels to individual renewable energy assets. This allowed them to propose a method for adjusting the unit commitment process that grid operators use daily and hourly to optimize energy production based on cost, supply, and demand.
Balancing Renewable Energy’s Uncertainty and Costs
In a paper co-authored by Sircar, Yang and Arvind Shrivats, the method accounts for the element of chance inherent in renewable energy, unlike current models that assume more control over power outputs. The risks of solar and wind generators are factored into their costs, and the software can suggest when to plan for increased output from natural gas plants, which is less costly than unplanned changes. The method also points to advantageous spots for increasing wind and solar capacity to reduce overall vulnerability.
Maximising Efficiency and Incentivising Renewable Production
“The goal is to put a number on the uncertainty of renewable assets, not to punish them, but to incentivize more production where it’s needed,” said Sircar. “We’re trying to mitigate the worst 5% of days when renewables underperform and you have to go to very costly natural gas or possibly even coal power plants to make up the shortfall.”
Commercial Potential and Industry Collaboration
The software could empower energy industry leaders to improve grid management and build new power assets that optimize earnings and overall grid resilience. The project’s technical adviser, Rana Mukerji, recently retired as senior vice president of the New York Independent System Operator, which monitors and coordinates the state’s power system. Mukerji is collaborating with the team to transform the research method into commercial-grade software through market research and detailed modelling of regional energy markets.
Princeton University’s Role in Shaping the Energy Future
When he met the Princeton University team in 2019, Mukerji saw the tool’s immediate value. “It’s a tremendously exciting time for the industry because essentially everything is being electrified, not by burning fossil fuel but with renewable resources like wind and solar. It is being built at a rapid pace in every grid around the world.”
