Brianna grew up in Kona, Hawaii and is now a rising junior at The Pennsylvania State University. With the goal to be first line in the transition to renewable/green energy, she is studying Energy Engineering with a minor in Electrochemical Engineering. After her undergraduate career, she hopes to continue her graduate studies conducting research on new ways to harness energy and increasing efficiency in current energy production/storage. Her main interest consists of exploring how to utilize her studies in isolated areas/micro-grids to promote energy independence, design of power plants/fuel cells, and EV battery productions. She also wants to gain an audience to promote and share her sustainable STEM experiences with the hope it will influence next generations to explore careers in STEM and teach others about individual sustainable practices. Outside her studies, she always takes the opportunity to travel, scuba dive, snowboard, hike and practice fitness anyway she can.
Home Island: Big Island
Institution when accepted: Pennsylvania State University
Akamai Project: Updating and Increasing Accuracy of a Visualization Tool for System Operations to Include Future Renewable Energy Power Plants and Battery Energy Storage Systems
Project Site: Hawaii Electric Light Co. – Hilo, Hawai‘i Island HI
Mentors: Robert Kaneshiro, Lisa Dangelmaier
With the upcoming transition to a 100% renewable energy portfolio, system operations at HELCO is in need of updating their Microsoft Excel based Forecast Visualization Tool. This tool utilizes historical load data, general data of the power plants (PP) on island, and anticipated distributed generated photovoltaics (DGPV) load shedding values (rated by Hawaii Island irradiance) to determine generation needed for the next 24 hours. It outputs a 24-hour graph that illustrates the load line, the megawatt (MW) generation of PP at determined times, and if the regulation ranges of generation fit the load line. In order to increase the relevancy of this tool, there are several updates that need to be made in the accuracy of the data and the overall ability of the tool. With a single input to forecast a load line given DGPV, there are often dramatic differences between expected and actual load lines. Time intervals in which PP can be turned on and off in Unit Control were limited, making it difficult to visual needed power generation/degeneration during transition periods. The tool also did not include vital current and future PP, the most important being two 30 MW PV farms with a 120 MWh battery energy storage system (BESS) attached to both. Now, instead of relying on averaged historical data and a single rating to determine a load line, current hourly forecasted data of DGPV from Hawaiian Electric’s Solar and Wind Integrated Tool (SWIFT) can be inputted to create a load line specific to the upcoming day. I then expanded Unit Control to two-hour intervals from 5am-11pm and additional graphs focusing on vital transition phases assisted with regulation range visuals. The PV farms were more comprehensive to utilize, given irradiance data specific to their location had to be extrapolated from SWIFT. The tool then had to determine how attached BESS would charge during low load/high sun periods and discharge for high load/low sun periods as operators place limits to PV farm grid feeding. Users can then discharge BESS for peak periods instead of relying on non-renewable PP to make up for the shortage of generation. These revisions will allow system operators to properly forecast the day ahead and know at what times they can expect to limit or start generation from certain PP to maintain proper regulation ranges for the next 24 hours. It will also benefit system operation/planning engineers, providing them with a visualization of future problems and solutions to grid integration of renewable energy resources and BESS.