Technology advancement for renewable energy resources and its integration to the distribution network (DN) has garnered substantial interest in the last few decades. Integrating such resources has proven to reduce power losses and improve the reliability of DN. However, the growing number of these resources in DN has imposed additional operational and control issues in voltage regulation, system stability, and protection coordination. Incorporation of various types of distributed generators (DG) into DN causes significant changes in the system. These including new fault current sources, new fault levels, a blinding effect in the protection scheme, reduction in the reach of relays, and decrement in the detection of lowlevel fault currents for existing relays. Such changes will jeopardize the effectiveness of the entire protection scheme in the DN. This research aims to propose a robust protection scheme in which the relay coordination settings are optimized based on the network layout. The potential impacts of DGs on the DN are mitigated by utilizing a user-defined overcurrent-based relay characteristic to obtain the minimum operating time while satisfying protection coordination constraints. A hybrid optimization algorithm based on Metaheuristic and Linear Programming that has the capability to attain the optimal solution and reduces computational time is proposed in this work. The performance of the proposed technique is tested on radial DN integrated with microgrid (MG). The results obtained show the proposed technique has successfully reduced the relay operating time while meeting the protection coordination requirements for dynamic operating modes of a network.
Harmonic distortion has garnered a lot of interest in the recent past due to the high advent of the non-linear electronic loads. Moreover, newer technologies including distributed generation and electric vehicles are anticipated to be part of the distribution systems at a mass scale in the near future. This makes it of utmost importance to evaluate the existing power distribution systems and analyze the possible constraints. This research study makes an effort to evaluate the harmonic distortion in the distribution systems caused by the various non-linear residential loads. The experimentally developed harmonic spectrums, of several home appliances, are deployed for the simulation of a typical UK distribution system using Electrical Transient Analyzer Program (ETAP). The results show high level of harmonic distortion, at the Point of Common Coupling (PCC), in the distribution system which becomes even more aggravated when a higher loading level, of the distribution transformer, is considered.
This paper considers the problem of anomaly detection in an outdoor environment where surveillance cameras are usually installed to monitor activities of general public. A novel solution is proposed which combines audio and visual data to automatically detect abnormal activities. The proposed anomaly detection algorithm makes use of both visual and audio features to automatically detect anomalous activities in scenes. Visual features such as optical flow technique combined with particle swam optimization and social force model are used, whereas, acoustic features such as, energy, zero crossing rate, volume, spectral-centroid, spectral spread, spectral roll-off, spectral flux, cross correlation and the mel-frequency cepstral coefficients (MFCCs) are used. An anomaly inference is developed which is based on both visual and audio features. The performance of the proposed algorithm is evaluated by testing it on the publicly available UMN datasets combined with the audio recordings. The proposed algorithm is compared with state-of-the-art techniques and is shown to achieve improved performance in terms of accuracy.
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