Adaptive Load Shedding for Stand-Alone Power Systems

Abstract

Load frequency control is commonly used to maintain power system frequency very close to its nominal value. A small deviation from the rated frequency may have harmful impact on the components of the system. Under-Frequency Load Shedding (UFLS) is to be used when the regular frequency control loops fail to restore the frequency to its rated value. In such conditions, the frequency continues to fall until adequate loads are disconnected from the network. Usually, renewable energy generation in microgrids represents a considerable percentage of the total generation. Therefore, application of UFLS in microgrids is crucial since they are exposed to rapid deficiency in generation due to weather conditions.

There are two main categories of UFLS: conventional and adaptive load shedding. Conventional UFLS has a fixed number of stages and fixed time delays while the adaptive UFLS applies shedding, in most cases, in one stage in the shortest possible delay.

This work introduces two adaptive UFLS schemes for an islanded microgrid both are based on artificial intelligence (AI). These schemes rely on estimating the value of load to be shed in one