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Revolutionizing Adaptive Simulation Frameworks for Microgrids

In January of 2017, President Obama honored Nurcin Celik, an associate professor in the University of Miami College of Engineering’s (UMCoE) Department of Industrial Engineering, with a Presidential Early Career Award for Scientists and Engineers (PECASE) for her innovative research and community service at the frontiers of science and technology. Since then, Celik has been using her award to continue her study on microgrids and smart-grids.

Microgrids, autonomous electricity environments that function within a larger electrical system, are highly important in electric utility resource planning, possessing the ability to separate and isolate themselves – known as “islanding” – from the utility’s distribution system during brownouts or blackouts. They have potential as a mechanism to increase the reliability and efficiency of electrical grid systems while also offering new services, which are unavailable under a traditional grid system.

“The economic security and reliability of microgrids is dependent on their connection to the main power grid, requiring real-time monitoring and management to ensure effective use,” explains Celik. “This requires real-time inferencing and decision making using the data available.”

Having a person making those real-time decisions can often be slow and inaccurate, not to mention costly and impractical. Because of this, Celik team has been working on developing a computation model that can autonomously interpret the data available and make a decision in real-time, transforming microgrids into smart-grids.

“Developing a computational model that can make those decisions is challenging for two main reasons,” continues Celik. “First, the excessive number of parameters and massive data loads involved strains the limited computational resources available, and second, the data available is dynamic, meaning that it is periodically updated, changing asynchronously over time as new information becomes available.”

Celik’s research has continued the development of a real-time computation model – officially called a dynamic data driven adaptive multi-scale simulation (DDDAMS) framework – for microgrids, focusing on the investigation and development of new algorithms and instrumentation methods. The current framework significantly accelerates the real-time computation of the resource allocation and controls decisions to optimize the operational cost, energy surety, as well as emissions per megawatt for a microgrid, without compromising the quality of the decisions made.

“We are investigating a basis for enabling the delivery of reliable, economical and environment friendly electricity while minimizing the damage of power events,” Celik says. “While the research effort to date has capitalized on the modeling and control of microgrid systems, the insights gained have significant potential to cross-pollinate to other fields and spawn new theoretical investigations, revolutionizing adaptive simulation frameworks.”

Celik has also extended her educational outreach activities to motivate students at different levels to pursuing careers that focus on the data driven technologies and their impact on national power critical infrastructures.

To learn more about Celik’s innovative research at the Simulation and Optimization Research Laboratory (SimLab) or to inquiry about open positions related to this research, please click here.

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