Abstract
This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.
Original language | American English |
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Number of pages | 5 |
DOIs | |
State | Published - Aug 2019 |
Event | 2019 IEEE Power and Energy Society General Meeting, PESGM 2019 - Atlanta, United States Duration: 4 Aug 2019 → 8 Aug 2019 |
Conference
Conference | 2019 IEEE Power and Energy Society General Meeting, PESGM 2019 |
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Country/Territory | United States |
City | Atlanta |
Period | 4/08/19 → 8/08/19 |
Bibliographical note
See NREL/CP-5D00-72754 for preprintNREL Publication Number
- NREL/CP-5D00-76224
Keywords
- clustering
- convex hull
- DB-scan
- piece-wise linear models
- system model
- vanadium redox flow battery