Methodology for robust monitoring of voltage sags based on equipment trip probabilities

This paper presents a new methodology for installing monitors into a distribution network to optimally and robustly monitor the voltage sag performance of the entire network. The developed methodology allows distribution network planners to specify budgetary requirements and future loading forecasts and output a robust set of monitoring locations for voltage sag performance monitoring. The research utilizes an artificial immune system optimization (AIS) algorithm to discover a range of near-optimal monitoring locations based on minimization of expected equipment trips at a bus. An estimate for the probable number of equipment trips is defined using a new probabilistic measure known as sag trip probability (STP). The optimized solutions are analyzed for robustness across a range of uncertain future network loading and topology scenarios. The results show the methodology applied to a 295 bus generic distribution network with uncertain load growth for the next 15 years.

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► An AIS algorithm is used to find near-optimal monitoring locations based on minimization of expected equipment trips.
► An estimate for the probable number of trips is defined using a new probabilistic measure known as sag trip probability.
► The solutions are analyzed for robustness across a range of uncertain future network loading and topology scenarios.
► Monitors were placed with the objective of estimating the likelihood of equipment trips during voltage sags.