Under-frequency load shedding (UFLS) schemes are designed by specifying a given amount of load to shed at various frequency thresholds to prevent the collapse of the electrical power system in the event of a large generation-load imbalance. An UFLS step is constituted of a group of medium-voltage feeders that trip when a given frequency threshold is reached. This study focuses on the method to be used when allocating a given feeder to a given step. First, the authors introduce performance metrics to quantify the accuracy level with which the UFLS target is met. Second, they model: the allocation method currently used in France; a variant of that method; and a new method introduced in this study, based on an automated clustering technique. Third, based on real consumption patterns measured from a vast area in France, and using the introduced performance metrics, they compare the efficiency of the three described methods. This study is conducted for the current state of loading of the considered distribution network and for a hypothetical situation with an increased share of distribution-side photovoltaic generation. For the chosen performance metrics, they demonstrate that the first two methods provide similar results while the clustering-based method performs remarkably better.

Our work focuses on the European Network Code on Emergency and Restoration (NC-ER) which introduced an harmonization requirement of Under-frequency Load Shedding (UFLS) schemes. This new requirement implies that in the medium term, the UFLS scheme of all European countries will have to evolve. It stipulates an acceptable range for the main factors that define an UFLS scheme, namely: the number of load shedding steps, the percentage of load shed in each step, and the accuracy of the frequency measurement that is implemented in the protection relays. In this context, the contribution of this paper is twofold: first, we define a new performance criterion for UFLS schemes; and second, we apply this criterion to two opposite archetypal schemes, in order to highlight the pros and cons of both approaches.

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