TY - JOUR
T1 - Robust Reactive Power Scheduling of Distribution Networks Based on Modified Bootstrap Technique
AU - Liao, Wenlong
AU - Wang, Shouxiang
AU - Bak-Jensen, Birgitte
AU - Pillai, Jayakrishnan Radhakrishna
AU - Yang, Zhe
PY - 2024/1/1
Y1 - 2024/1/1
N2 - The uncertainties of the power load, wind power, and photovoltaic power lead to errors between point prediction values and real values, which challenges the safe operation of distribution networks. In this paper, a robust reactive power scheduling (RRPS) model based on a modified bootstrap technique is proposed to consider the uncertainties of power loads and renewable energy sources. Firstly, a deterministic reactive power scheduling (DRPS) model and an RRPS model are formulated. Secondly, a modified bootstrap technique is proposed to estimate prediction errors of power loads and renewable energy sources without artificially assuming the probability density function of prediction errors. To represent all possible scenarios, point prediction values and prediction errors are combined to construct two worst-case scenarios in the RRPS model. Finally, the RRPS model is solved to find a scheduling scheme, which ensures the security of distribution networks for all possible scenarios in theory. Simulation results show that the worstcase scenarios constructed by the modified bootstrap technique outperform popular baselines. Besides, the RRPS model based on the modified bootstrap technique balances economics and security well.
AB - The uncertainties of the power load, wind power, and photovoltaic power lead to errors between point prediction values and real values, which challenges the safe operation of distribution networks. In this paper, a robust reactive power scheduling (RRPS) model based on a modified bootstrap technique is proposed to consider the uncertainties of power loads and renewable energy sources. Firstly, a deterministic reactive power scheduling (DRPS) model and an RRPS model are formulated. Secondly, a modified bootstrap technique is proposed to estimate prediction errors of power loads and renewable energy sources without artificially assuming the probability density function of prediction errors. To represent all possible scenarios, point prediction values and prediction errors are combined to construct two worst-case scenarios in the RRPS model. Finally, the RRPS model is solved to find a scheduling scheme, which ensures the security of distribution networks for all possible scenarios in theory. Simulation results show that the worstcase scenarios constructed by the modified bootstrap technique outperform popular baselines. Besides, the RRPS model based on the modified bootstrap technique balances economics and security well.
KW - Reactive power
KW - Renewable energy sources
KW - Robust programming
KW - Uncertainty
KW - distribution network
KW - robust programming
KW - worst-case scenario
KW - bootstrap technique
KW - prediction error
KW - Distribution network
UR - http://www.scopus.com/inward/record.url?scp=85184073335&partnerID=8YFLogxK
U2 - 10.35833/MPCE.2022.000850
DO - 10.35833/MPCE.2022.000850
M3 - Journal article
SN - 2196-5625
VL - 12
SP - 154
EP - 166
JO - Journal of Modern Power Systems and Clean Energy
JF - Journal of Modern Power Systems and Clean Energy
IS - 1
M1 - 10130019
ER -