A Survey of Real-Time Optimal Power Flow

Erfan Mohagheghi, Mansour Alramlawi, Aouss Gabash and Pu Li
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Erfan Mohagheghi: Department of Process Optimization, Institute of Automation and Systems Engineering, Ilmenau University of Technology, 98693 Ilmenau, Germany
Mansour Alramlawi: Department of Process Optimization, Institute of Automation and Systems Engineering, Ilmenau University of Technology, 98693 Ilmenau, Germany
Aouss Gabash: Department of Process Optimization, Institute of Automation and Systems Engineering, Ilmenau University of Technology, 98693 Ilmenau, Germany
Pu Li: Department of Process Optimization, Institute of Automation and Systems Engineering, Ilmenau University of Technology, 98693 Ilmenau, Germany

Energies, 2018, vol. 11, issue 11, 1-20

Abstract: There has been a strong increase of penetration of renewable energies into power systems. However, the renewables pose new challenges for the operation of the networks. Particularly, wind power is intermittently fluctuating, and, therefore, the network operator has to fast update the operations correspondingly. This task should be performed by an online optimization. Therefore, real-time optimal power flow (RT-OPF) has become an attractive topic in recent years. This paper presents an overview of recent studies on RT-OPF under wind energy penetration, offering a critical review of the major advancements in RT-OPF. It describes the challenges in the realization of the RT-OPF and presents available approaches to address these challenges. The paper focuses on a number of topics which are reviewed in chronological order of appearance: offline energy management systems (EMSs) (deterministic and stochastic approaches) and real-time EMSs (constraint satisfaction-based and OPF-based methods). The particular challenges associated with the incorporation of battery storage systems in the networks are explored, and it is concluded that the current research on RT-OPF is not sufficient, and new solution approaches are needed.

Keywords: real-time optimal power flow (RT-OPF); active–reactive OPF; wind energy; feasibility; battery storage systems (BSSs) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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