Wavelet-based systems for frequency monitoring and islanding detection of AC microgrids

Abstract

The modern distribution system widely uses renewable energy sources (RESs) as a distributed generation that introduces problems like unintentional islanding, protection concerns, and reverse power flow. The RES intermittent characteristics can cause frequency deviations that could result in systems instabilities. In general, hierarchical structures implement power flow control management of these microgrids, composed of primary, secondary, and tertiary control layers. The primary control layer consists of inner current and voltage control loops, typically implemented via droop control loops, for the purpose of maintaining stabilization of frequency and voltage amplitudes, as well as power-sharing. The principal drawbacks of droop control approaches are steady-state frequency and voltage deviations. For that reason, the secondary control layer is introduced to mitigate these deviations. The accurate knowledge of microgrid frequency deviations permits the implementation of proper frequency restoration. Besides, those microgrids could operate in the connected or islanding modes. Islanding or fault occurrences must be detected and treated to ensure system stability. This way, the continuous wavelet transform is employed to develop a hybrid islanding detection and a frequency monitor to fulfill the microgrid requirements related to a secure islanding detection and a frequency restoration. In this thesis, the development of both systems is carried out, with the effectiveness of proposed methods evaluated and validated through experimental results.