TY - GEN
T1 - Quantifying photovoltaic fluctuation with 5 kHz data
T2 - IEEE Power and Energy Conference at Illinois, PECI 2016
AU - Magerko, John A.
AU - Cao, Yue
AU - Krein, Philip T.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/4/25
Y1 - 2016/4/25
N2 - We aim to systematically quantify photovoltaic (PV) variability contained within different frequency bands, primarily for applications in PV maximum power point tracking (MPPT) design. We first discuss the usefulness in quantifying energy capture for various maximum power point (MPP) update rates from nearly 500 days of 5 kHz photovoltaic recordings. Next, we justify the methods used to convert MPP sweep data to single-point, usable, current, voltage, and power values. We discuss fitting methods that yield the MPP under calm irradiance dynamics and explore the approach used during periods of more stochastic changes. This is followed by analysis of raw, high-frequency content and a proposed method to calculate associated energy capture reduction. The conclusion finds an absolute upper bound on solar data variability for a given MPP update rate in terms of energy capture. Finally, we use the previous results and demonstrate an economic analysis that can aid in designing future MPP tracker specifications.
AB - We aim to systematically quantify photovoltaic (PV) variability contained within different frequency bands, primarily for applications in PV maximum power point tracking (MPPT) design. We first discuss the usefulness in quantifying energy capture for various maximum power point (MPP) update rates from nearly 500 days of 5 kHz photovoltaic recordings. Next, we justify the methods used to convert MPP sweep data to single-point, usable, current, voltage, and power values. We discuss fitting methods that yield the MPP under calm irradiance dynamics and explore the approach used during periods of more stochastic changes. This is followed by analysis of raw, high-frequency content and a proposed method to calculate associated energy capture reduction. The conclusion finds an absolute upper bound on solar data variability for a given MPP update rate in terms of energy capture. Finally, we use the previous results and demonstrate an economic analysis that can aid in designing future MPP tracker specifications.
KW - Economic analysis
KW - Energy loss calculation
KW - Frequency domain analysis
KW - High frequency solar data
KW - Maximum power point tracking (MPPT)
KW - Photovoltaic (PV)
KW - Solar variability
KW - Stochastic energy
UR - http://www.scopus.com/inward/record.url?scp=84973891479&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84973891479&partnerID=8YFLogxK
U2 - 10.1109/PECI.2016.7459266
DO - 10.1109/PECI.2016.7459266
M3 - Conference contribution
AN - SCOPUS:84973891479
T3 - 2016 IEEE Power and Energy Conference at Illinois, PECI 2016
BT - 2016 IEEE Power and Energy Conference at Illinois, PECI 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 February 2016 through 20 February 2016
ER -