Following extreme weather events, electrical blackouts can make life difficult for an entire city, affecting everything thing from emergency responders and traffic signals to healthcare facilities and residential areas. Power system restoration can take days, or even weeks, costing a considerable amount of money, not including revenue loss due to the outage.
In the UH Systems Optimization and Computing Laboratory, second-year Ph.D. student Saeedeh Abbasi is close to unveiling a solution that may revolutionize utility operations following such weather-related power system failures.
As part of her industrial engineering research, Abbasi, her faculty adviser and a second adviser from electrical engineering, have partnered to develop an innovative strategy based on pre-emptive programming. The team has developed a mathematical model to run real-time scenarios before and during imminent weather events to provide utility companies with the most beneficial sequence to restoring power to large sections of the network.
“Our model factors in all the variables you might expect during extreme weather, such as wind speed and flooding,” says Abbasi, who also explains that the model includes parameters that need to be prioritized, such as the need to restore power in hospital districts and data centers before other consumers.
“Our model generates what’s known as Pareto-frontier solutions to provide a group of stakeholders with various possible outcomes for key decision-making,” she says.
With hopes of publishing findings soon on the performance of their model, Abbasi is optimistic about the future of power systems engineering in this area.
“This is a hugely important area of research, especially for this region,” she says. “We need to find a global solution to these issues because extreme weather will continue to happen.”