Spike removal technology for grid-connected power converters
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Date
2012
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University of New Brunswick
Abstract
Power Electronic Converters (PECs) are routinely used to control the energy supplied to the electric grid by distributed generators. The operation of PECs involves
the control of voltage and current by rapidly switching power semiconductor devices. The rapid switching of these devices causes a certain class of high frequency noise called spikes to be induced into sensor measurements. In addition to PEC control functions, the sensor measurements are also used to detect over current (OI), over voltage ( OV) and under voltage (UV) faults. The presence of noise spikes compromises the performance and leads to unnecessary triggering of fault protection circuitry as a result of false detection of over/under voltage and current faults. The development of a new algorithm to remove short time electrical spikes from PEC sensors is the focus of this thesis. In such a way, the PEC is unaffected and false OI, OV, and UV alarms are eliminated. The methodology uses the discrete wavelet transform (DWT) to generate a feature space where the spike feature is detected and removed, and the inverse DWT to reconstruct spike-free measurements. A Field-Programmable Gate Array (FPGA)-based interface board is designed to test the new algorithm within an actual PEC system. The designed FPGA board along with the new algorithm will be used in the integration of distributed generators into power systems.