Novel Technique for Developing Linearized Convex System Models from Experimentally Derived Data
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
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.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- New Energy and Industrial Technology Development Organization (NEDO)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1602678
- Report Number(s):
- NREL/CP-5D00-76224
- Resource Relation:
- Conference: Presented at the 2019 IEEE Power & Energy Society General Meeting (PESGM), 4-8 August 2019, Atlanta, Georgia
- Country of Publication:
- United States
- Language:
- English
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