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GPA teams up with national labs and industry experts on advanced data analytics and grid modernization



By Pacific Island Times News Staff


As the Guam Power Authority integrates more renewable energy to meet Guam’s clean energy goals, efficient tools and methods will be needed to ensure the reliability and resiliency of the grid.


This includes using advanced data analytics to monitor and address grid health in real-time.


Recognizing GPA’s efforts to modernize its grid and the potential for nationwide implementation of the project, the U.S. Department of Energy Office of Electricity awarded GPA $1 million from the Grid-Enhancing Data Analytics Demonstrations for Operations, Monitoring and Control grant.


In partnership with the Pacific Northwest National Laboratory, National Renewable Energy Laboratory, and PXiSE Energy Solutions, GPA will develop a real-time management and analytical tool to model grid behavior to provide real-time detection of grid events and impact. Existing power measurement and control strategies are unable to address frequency issues often associated with renewable energy.


GPA intends to utilize innovative data analytics using real-time grid data to address issues almost instantaneously and reduce the likelihood of under-frequency load shedding.


“The road to 100 percent renewable energy will not be easy, but GPA is taking the necessary steps to protect the grid and meet customer demand as we go through the clean energy transition," said John M. Benavente, GPA's general manager.


"We’re seeing explosive growth in data analytics in the energy sector. By partnering with national labs and industry experts, we can use this innovative technology to help push our clean energy goals while increasing the reliability of our power system," he added.


This grant funding is used to support projects that will enhance the electric power systems’ reliability and resilience via grid-enhancing data analytics demonstrations for operations, monitoring and control. These projects must demonstrate the various geographic, economic, and climate conditions that help assess the deployment of advanced data analytics. (GPA)





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