ISSN 2196-5625 CN 32-1884/TK
2020, 8(2):325-333.DOI: 10.35833/MPCE.2018.000750
Abstract:An analytical calculation method for the reliability sensitivity indexes of distribution systems is proposed to explicitly quantify the impact of various influence factors on system reliability. Firstly, the analytical calculation formulas for the reliability indexes of distribution systems are derived based on the fault incidence matrix (FIM). Secondly, the factors that affect system reliability are divided into two categories: quantifiable parameter factors and non-quantifiable network structure factors. The sensitivity indexes for the quantifiable parameter factors are derived using the direct partial derivation of the reliability calculation formulas. The sensitivity indexes for the non-quantifiable network structure factors are derived using the transformation of FIMs. Finally, the accuracy and efficiency of the proposed sensitivity calculation method are verified by applying them to an IEEE 6-bus RBTS system. This paper sums up the factors that influence system reliability in detail and gives the explicit analytical calculation method for the sensitivity of each factor. Repetitive calculation of the reliability index can be avoided during the sensitivity analysis. The bottleneck that affects the reliability level of distribution systems can be identified efficiently, and valuable information and guidance can be provided to enhance the reliability of distribution systems.
2025, 13(3):827-839.DOI: 10.35833/MPCE.2024.000367
Abstract:The single-ended fault location based on travelling waves (TWs) is commonly used for long-distance high-voltage AC transmission lines. However, it relies on high sampling frequency and accurate capturing of the TW head arrival time. Accordingly, this study establishes a transient analytical method for fault location based on the similarity between the transient recorded waveform and output waveforms of analytical calculation model. In the proposed method, fuzzy constraints of fault features are constructed through time-distance and waveform-scaling correlations while considering the deviation factors of the frequency-dependent wave velocity and TW head arrival time. Accordingly, the high-dimensional space of the fitting problem is transformed into a one-dimensional implicit function fitting problem containing only the fault distance, thereby enabling the waveform comparison problem to be quickly solved based on fault TW features. Under the fuzzy constraints proposed in this study, the proposed method requires only a relatively vague identification of the TW head, and the requirements for sampling frequency are also more lenient. In addition, a sliding window scheme is adopted for enhancing the TW morphology characteristics. Finally, the proposed method is tested using PSCAD, and the simulations validate the fault location accuracy of the proposed method.