Search Results (3)

The overhead line (OHL)–cable hybrid transmission line, which connects floating photovoltaic (PV) power plants, needs to be considered regarding whether to block reclosing operations or not. However, due to the weak-feed characteristics of PV inverters, existing methods are difficult to apply in this scenario. This paper proposes a criterion for fault section identification in the transmission lines of floating PV power plants based on traveling wave power and the zero-sequence impedance angle. Firstly, the fault current characteristics of photovoltaic inverters under dual-vector control are analyzed, and the applicability of the sequence component impedance directional criterion in this scenario is discussed. Then, the transmission, refraction, and reflection processes of traveling waves in OHL–cable hybrid lines are analyzed, and a traveling wave energy criterion is designed to determine the fault section. Finally, based on the scope of application of the zero-sequence impedance angle and traveling wave energy criterion, a fault section identification method for the hybrid lines of floating PV power plants is established. A deployment method for the proposed method, based on feeder terminal units (FTUs) at the connection points between the OHL and cable is proposed. This method identifies fault sections through traveling waves and zero-sequence impedance angles, which are unaffected by PV week feed characteristics, can be applied to all the AC fault types, and do not rely on multi-terminal synchronous sampling. The proposed method is verified on a 1MW PV system built in the PSCAD. Full article

Environmental concerns and economic constraints have led to increasing installations of mixed conductor circuits comprising underground cables (UGCs) and overhead transmission lines (OHLs). Faults on the OHL sections of such circuits are usually temporary, while there is a higher probability that faults on UGC sections are permanent. To maintain power system reliability and security, auto-reclose (AR) schemes are typically implemented to minimize outage duration after temporary OHL faults while blocking AR for UGC faults to prevent equipment damage. AR of a hybrid UCG–OHL transmission line, therefore, requires effective identification of the faulty section. However, the different electrical characteristics of UGC and OHL sections present significant challenges to existing protection and fault location methods. This paper presents a selective AR scheme for mixed conductor circuits based on the evaluation of differential currents in multiple defined protection zones, using distributed current transformer (CT) measurements provided by passive optical sensing. Case studies are conducted with a number of different UGC–OHL configurations, and the results demonstrate that the proposed scheme can accurately identify the faulty section, enabling effective selective AR of a comprehensive range of mixed conductor circuit topologies. The proposed scheme is also more cost effective, with reduced hardware requirements compared to conventional solutions. This paper thereby validates the optimal solution for mixed circuit protection as described in CIGRE Working Group B5.23 report 587. Full article

Penetration level of solar photovoltaic (PV) energy in the utility network is steadily increasing. This changes the fault level and causes protection problems. Furthermore, multi-tapped structure of distribution network deployed to integrate solar PV energy to the grid and supplying loads at the same time also raised the protection challenges. Hence, this manuscript is aimed at introducing an algorithm to identify and classify the faults incident on the network of utilities where penetration level of the solar PV energy is high. This fault recognition algorithm is implemented in four steps: (1) calculation of Stockwell transform-based fault index (STFI) (2) calculation of Wigner distribution function-based fault index (WDFI) (3) calculation of combined fault index (CFI) by multiplying STFI and WDFI (4) calculation of index for ground fault (IGF) used to recognize the involvement of ground in a fault event. The STFI has the merits that its performance is least affected by the noise associated with the current signals and it is effective in identification of the waveform distortions. The WDFI employs energy density of the current signals for estimation of the faults and takes care of the current magnitude. Hence, CFI has the merit that it considers the current magnitude as well as waveform distortion for recognition of the faults. The classification of faults is achieved using the number of faulty phases. An index for ground fault (IGF) based on currents of zero sequence is proposed to classify the two phase faults with and without the ground engagement. Investigated faults include phase to ground, two phases fault without involving ground, two phases fault involving ground and three phase fault. Fault recognition algorithm is tested for fault recognition with the presence of noise, various angles of fault incidence, different impedances involved during faulty event, hybrid lines consisting of overhead line (OHL) and underground cable (UGC) sections, and location of faults on all nodes of the test grid. Fault recognition algorithm is also tested to discriminate the transients due to switching operations of feeders, loads and capacitor banks from the faulty transients. Performance of the fault recognition algorithm is compared with the algorithms based on discrete wavelet transform (DWT), Stockwell transform (ST) and hybrid combination of alienation coefficient and Wigner distribution function (WDF). Effectiveness of the fault recognition algorithm is established using a detailed study on the IEEE-13 nodes test feeder modified to incorporate solar PV plant of capacity 1 MW in MATLAB/Simulink. Algorithm is also validated on practical utility grid of Rajasthan State of India. Full article