TY - JOUR
T1 - Forecasting-based power ramp-rate control strategies for utility-scale PV systems
AU - Chen, Xiaoyang
AU - Du, Yang
AU - Wen, Huiqing
AU - Jiang, Lin
AU - Xiao, Weidong
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2019/3
Y1 - 2019/3
N2 - Passing cloud results in rapid changes of irradiance. The intermittency of photovoltaic (PV) power output has drawn serious concern especially for utility-scale PV system. Consequently, power ramp-rate control (PRRC) has been introduced to avoid significant PV power fluctuations. PRRC is usually implemented either by curtailing active power output or implementing energy storage system (ESS). However, current active power curtailment cannot deal with the irradiance ramp-down fluctuations, and the high cost of the ESS is still hindering its extensive application. In this paper, two innovative PRRC strategies are presented, which utilize the short-term forecasting. The first solution does not require any ESS, during the power ramp-down event, the PV generation will be curtailed before the actual shading occurs. The second solution requires only one-quarter of the energy capacity of the conventional ESS control strategy. To provide the PV generation forecasts, a dynamic model based on spatio-temporal theory is formulated. The effectiveness of the proposed forecasting model and control strategies have been verified through experiment and case studies.
AB - Passing cloud results in rapid changes of irradiance. The intermittency of photovoltaic (PV) power output has drawn serious concern especially for utility-scale PV system. Consequently, power ramp-rate control (PRRC) has been introduced to avoid significant PV power fluctuations. PRRC is usually implemented either by curtailing active power output or implementing energy storage system (ESS). However, current active power curtailment cannot deal with the irradiance ramp-down fluctuations, and the high cost of the ESS is still hindering its extensive application. In this paper, two innovative PRRC strategies are presented, which utilize the short-term forecasting. The first solution does not require any ESS, during the power ramp-down event, the PV generation will be curtailed before the actual shading occurs. The second solution requires only one-quarter of the energy capacity of the conventional ESS control strategy. To provide the PV generation forecasts, a dynamic model based on spatio-temporal theory is formulated. The effectiveness of the proposed forecasting model and control strategies have been verified through experiment and case studies.
KW - Active power curtailment (APC)
KW - energy storage sizing (ESS)
KW - power ramp-rate control (PRRC)
KW - solar forecasting
UR - http://www.scopus.com/inward/record.url?scp=85047987577&partnerID=8YFLogxK
U2 - 10.1109/TIE.2018.2840490
DO - 10.1109/TIE.2018.2840490
M3 - Article
AN - SCOPUS:85047987577
SN - 0278-0046
VL - 66
SP - 1862
EP - 1871
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 3
M1 - 8370779
ER -