Consensus-based distributed optimal power flow using gradient tracking technique for short-term power fluctuations

Zhaoyi Zhang, Lei Shang, Chengxi Liu, Qiupin Lai and Youjin Jiang

Energy, 2023, vol. 264, issue C

Abstract: This paper proposes a consensus-based distributed optimal power flow (CD-OPF) scheme to fast track the sub-optimal operating point, considering the power systems’ state deviance caused by short-term fluctuations of renewable generations. By combining the chance-constraint optimal power flow (CC-OPF) and gradient tracking technique (GTT), the proposed scheme could achieve more precise optimization for power system. Firstly, for a time interval, the optimal power flow is applied to obtain the optimal state by chance-constrained programming according to the measured operating states. Then, for the moments within the time interval, a communication-less distributed GTT is performed at each local renewable generation unit to track the sub-optimal point considering its generation fluctuations. Next, the CD-OPF is achieved based on the consensus that each renewable generation unit performs its own tracking optimization by GTT independently, so as to reduce the dependence on global information and fast communication. Finally, the simulations on the IEEE-39 bus power system, the IEEE-118 bus power systems and the wind farm validate the effectiveness of proposed scheme. The results show that the proposed method can decrease the power loss, prevent the voltage violation, and reduce the time-cost.

Keywords: Distributed optimal power flow; Gradient tracking technique; Short-term fluctuations of renewable generation; Consensus-based (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:264:y:2023:i:c:s036054422202521x

DOI: 10.1016/j.energy.2022.125635

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