This page has only limited features, please log in for full access.
Penetration of DC networks is rapidly increasing in modern power systems. As transient behavior of DC grids is different from that of AC ones, AC grid protection schemes might not be applicable to protect DC networks. Exact fault location is vital for protection of DC networks to reduce repair cost and achieve fast power recovery. This paper proposes a novel topology independent multi-terminal DC scheme to identify fault section and location for DC transmission systems. Voltage and current signals measured at the terminals are analyzed by the least squares error (LSE) algorithm. Then, the proposed scheme uses low frequency components of the signals to locate DC faults offline. Unlike some other methods, it does not require sophisticated sensors and hardware to capture very high frequency content of the signals. Hence, the proposed scheme can be implemented in practice without additional measuring infrastructure. The performance of the proposed scheme is evaluated under various fault conditions for different topologies of DC networks in both overhead lines and cables. Numerous simulations carried out demonstrate that the proposed scheme is quite accurate and provides excellent performance under different fault resistances, sections, and locations.
Habib Panahi; Majid Sanaye-Pasand; Seyed Hassan Ashrafi Niaki; Reza Zamani. Fast Low Frequency Fault Location and Section Identification Scheme for VSC-Based Multi-Terminal HVDC Systems. IEEE Transactions on Power Delivery 2021, PP, 1 -1.
AMA StyleHabib Panahi, Majid Sanaye-Pasand, Seyed Hassan Ashrafi Niaki, Reza Zamani. Fast Low Frequency Fault Location and Section Identification Scheme for VSC-Based Multi-Terminal HVDC Systems. IEEE Transactions on Power Delivery. 2021; PP (99):1-1.
Chicago/Turabian StyleHabib Panahi; Majid Sanaye-Pasand; Seyed Hassan Ashrafi Niaki; Reza Zamani. 2021. "Fast Low Frequency Fault Location and Section Identification Scheme for VSC-Based Multi-Terminal HVDC Systems." IEEE Transactions on Power Delivery PP, no. 99: 1-1.
Different issues will be raised and highlighted by emerging distributed generations (DGs) into modern power systems in which the islanding detection is the most important. In the islanding situation, a part of the system which consists of at least one DG, passive grid, and local load, becomes fully separated from the main grid. Several detection methods of islanding have been proposed in recent researches based on measured electrical parameters of the system. However, islanding detection based on local measurements suffers from the non-detection zone (NDZ) and undesirable detection during grid-connected events. This paper proposes a passive islanding detection algorithm for all types of DGs by appropriate combining the measured frequency, voltage, current, and phase angle and their rate of changes at the point of common coupling (PCC). The proposed algorithm detects the islanding situation, even with the exact zero power mismatches. Proposed algorithm discriminates between the islanding situation and non-islanding disturbances, such as short circuit faults, capacitor faults, and load switching in a proper time and without mal-operation. In addition, the performance of the proposed algorithm has been evaluated under different scenarios by performing the algorithm on the IEEE 13-bus distribution system.
Arash Abyaz; Habib Panahi; Reza Zamani; Hassan Haes Alhelou; Pierluigi Siano; Miadreza Shafie-Khah; Mimmo Parente. An Effective Passive Islanding Detection Algorithm for Distributed Generations. Energies 2019, 12, 3160 .
AMA StyleArash Abyaz, Habib Panahi, Reza Zamani, Hassan Haes Alhelou, Pierluigi Siano, Miadreza Shafie-Khah, Mimmo Parente. An Effective Passive Islanding Detection Algorithm for Distributed Generations. Energies. 2019; 12 (16):3160.
Chicago/Turabian StyleArash Abyaz; Habib Panahi; Reza Zamani; Hassan Haes Alhelou; Pierluigi Siano; Miadreza Shafie-Khah; Mimmo Parente. 2019. "An Effective Passive Islanding Detection Algorithm for Distributed Generations." Energies 12, no. 16: 3160.