Multi-layer fuzzy-based under-frequency load shedding in back-pressure smart industrial microgrids

Abstract

In industrial microgrids (MGs), various operating conditions may lead to severe frequency fluctuations. If no any particular remedy is thought, these fluctuations may jeopardize the system stability against which load shedding is recognized as an effective countermeasure. This issue has not been properly addressed in back-pressure MGs where cogeneration of steam and electricity is required. If the permissible operating range is violated, under frequency load shedding (UFLS) scheme propagates suitable commands to disconnect a set of loads and hence assuring the frequency stability. This manuscript proposes an efficient multi-layer fuzzy-based load shedding (MLFLS) approach to enhance the MG overall performance. In comparison with conventional UFLS scheme, the amount of shed load is determined through a multi-layer mechanism. Frequency deviation and steam pressure are selected as two control inputs and the output signal is a control command to keep a specific load in connected or disconnected mode. To this end, suitable rule basis is embedded in MLFLS inference system to determine the amount of required load to be shed. The proposed approach is tested on a simulation model of a real-world autonomous MG and a suitable comparison is performed against the conventional UFLS scheme. The obtained results are discussed in depth.