Volume 1 Issue 1
Authors: Pavol RAFAJDUS; Mircea RUBA; Rares TEREC; Loránd SZABÓ
Abstract: In the paper, a reconfigurable fault tolerant control system for a segmental stator switched reluctance machine is proposed. It can detect diverse winding faults and mask these faults by means of imposing increased currents in the healthy remained coils of the machine. The reconfiguration strategy depends on the type of the winding fault. By applying the proposed reconfiguration of the control strategy the continuation of the machine's movement can be assured despite of winding faults of diverse severity. The main hardware and software components of the control system are detailed in length in the paper. The correct reconfiguration is proved by laboratory measurements performed on a test bench specially built up for this purpose. The developed control system can be applied in safety-critical electrical equipment.
Keywords: Switched Reluctance Machine; Fault Tolerance; Reconfigurable Control
Authors: Rajesh Kumar; Dinesh Kumar; M. Rizwan
Abstract: The demand of electricity in India is increasing exponentially at the rate of 8-9% per annum. However, the installed power generation capacity of India as on 31st October 2012 was 209276 MW with a peak power shortage of more than 12%. In addition, the demand of electricity is increasing due to increased population, urbanization and comfort level of the peoples. These indicate that India’s future energy requirements are going to be very high. Keeping in view of aforesaid, proper energy management system is required. In this paper an attempt has been made for short term load forecasting which helps in load management with on line dynamic voltage control, load flow studies and exchange of power as requirement for load frequency control. In this paper, the daily hourly demand of Shahpura, Jaipur, India has been collected from Rajasthan Electricity Board (Shahpura Sub-station), India. To avoid the convergence problems, the input and output load data are scaled down such that they remain within the range of (0.1-0.9). The inputs of the fuzzy logic based models are the hourly electrical demand during the day for the four consecutive days of November 2012 and the output or forecasted value is the hourly demand of the fifth day. The results obtained from fuzzy logic model has been validated with the actual value and found accurate. The mean absolute percentage error (MAPE) in the forecasted demand is 1.39% in comparison with the desired demand.
Keywords: Fuzzy Logic; Load Forecasting; Energy Management