TY - JOUR
T1 - Frequency regulation in adaptive virtual inertia and power reserve control with high PV penetration by probabilistic forecasting
AU - Chang, Jiaming
AU - Du, Yang
AU - Chen, Xiaoyang
AU - Lim, Enggee
AU - Wen, Huiqing
AU - Li, Xingshuo
AU - Jiang, Lin
N1 - Funding Information:
This work was supported by the Xi’an Jiaotong-Liverpool University, Research Development Fund of XJTLU (RDF-17-01-28); and the AI University Research Centre (AI-URC) through the XJTLU Key Programme Special Fund (KSF-P-02).
Publisher Copyright:
Copyright © 2022 Chang, Du, Chen, Lim, Wen, Li and Jiang.
PY - 2022/11/2
Y1 - 2022/11/2
N2 - The large-scale deployment of sustainable energy sources has become a mandatory goal to reduce pollution from electricity production. As photovoltaic (PV) plants replace conventional synchronous generators (SGs), their significant inherent rotational inertia characteristics are reduced. The high penetration of PV results in reduced system inertia, leading to system frequency instability. Virtual inertial control (VIC) technology has attracted increasing interest because of its ability to mimic inertia. Adoption of the energy storage system (ESS) is hindered by the high cost, although it can be used to provide virtual inertia. The determined forecast gives PVs the ability to reserve power before shading and compensate the power when a system power drop occurs, which can increase system inertia. Nevertheless, it has forecast errors and energy waste in a stable state. To improve the stability of the microgrid and improve the ESS efficiency, this study proposes an adaptive forecasting-based (AFB) VIC method using probabilistic forecasts. The adaptive power reserve and virtual inertia control are proposed to reduce energy waste and increase system inertia. The simulation results reveal that the proposed method has adaptive system inertia to reduce the reserved power, required ESS power capacity, and battery aging.
AB - The large-scale deployment of sustainable energy sources has become a mandatory goal to reduce pollution from electricity production. As photovoltaic (PV) plants replace conventional synchronous generators (SGs), their significant inherent rotational inertia characteristics are reduced. The high penetration of PV results in reduced system inertia, leading to system frequency instability. Virtual inertial control (VIC) technology has attracted increasing interest because of its ability to mimic inertia. Adoption of the energy storage system (ESS) is hindered by the high cost, although it can be used to provide virtual inertia. The determined forecast gives PVs the ability to reserve power before shading and compensate the power when a system power drop occurs, which can increase system inertia. Nevertheless, it has forecast errors and energy waste in a stable state. To improve the stability of the microgrid and improve the ESS efficiency, this study proposes an adaptive forecasting-based (AFB) VIC method using probabilistic forecasts. The adaptive power reserve and virtual inertia control are proposed to reduce energy waste and increase system inertia. The simulation results reveal that the proposed method has adaptive system inertia to reduce the reserved power, required ESS power capacity, and battery aging.
KW - forecasting
KW - frequency regulation
KW - micro-grid
KW - power reserve
KW - virtual inertial control
UR - http://www.scopus.com/inward/record.url?scp=85142139773&partnerID=8YFLogxK
U2 - 10.3389/fenrg.2022.929113
DO - 10.3389/fenrg.2022.929113
M3 - Article
AN - SCOPUS:85142139773
SN - 2296-598X
VL - 10
JO - Frontiers in Energy Research
JF - Frontiers in Energy Research
M1 - 929113
ER -