Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Fuzzy logic. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Overcurrent relays coordination considering transient behaviour of fault current limiter and distributed generation in distribution power network

Abstract: The connecting of distributed generation (DG) to the distribution network has numerous advantages. However, in the presence of DG some problems in coordination of protection devices will occur, due to changes in short-circuit levels at different points. Fault current limiter (FCL) is applied to limit the fault current levels and the effect of DGs on coordination of overcurrent (O/C) relays during the faults. The use of DG and FCL in distribution networks causes to some transient currents during fault conditions. Steady-state coordination methods do not result in accurate settings in such networks. A new method is proposed for coordination of O/C relays by considering the transient behaviour of the network. This method is based on the genetic algorithm and uses the dynamic model of O/C relays instead of the fixed characteristic curves. For this purpose, transient behaviour of DG and FCL are simulated and the relay operating status is calculated for all primary and backup relays to achieve the optimal settings of relays in transient condition. Simulations are carried out on a sample network and the results demonstrate that the method gives feasible and effective solutions for optimal coordination in the practical power system networks in comparison to the previous steady-state methods.

Public transport trip purpose inference using smart card fare data

Abstract: Although smart card fare data has recently become more prevalent as a rich, comprehensive and continuous source of information, there is still some missing information which inhibits its capability in the research field. One key missing piece of information is the passengers’ trip purpose. This paper investigates the potential of the smart card data to infer passengers’ trip purpose, thereby reducing the use of the expensive and time-consuming Household Travel Surveys (HTS). On this basis, an improved model has been proposed, calibrated and validated for trip purpose inference by integrating different data sources, namely: HTS, a land use database, the South East Queensland Strategic Transport Model (SEQSTM), the General Transit Feed Specification (GTFS) data, O-D survey data, and most importantly the unique smart card fare data from Brisbane, Queensland. As smart card fare data does not record passengers’ trip purpose, the calibration and validation procedures are performed on HTS data. Based on the validation results, the proposed methodology shows a strong capability to predict trip purpose at a high level of accuracy. The results show an overall 67% correct inference after applying spatial attributes, but the correct inference increases to 78% after applying temporal attributes. Different trip purposes show different sensitivities to the applied spatial and temporal attributes. Work and home trips have the highest correct inference results, at 92% and 96%, respectively. Furthermore, the results of correct inference for shopping and education trips improved after applying the temporal attributes.