Coincident Peak Prediction for Capacity and Transmission Charge Reduction
arxiv(2024)
Abstract
Meeting the ever-growing needs of the power grid requires constant
infrastructure enhancement. There are two important aspects for a grid ability
to ensure continuous and reliable electricity delivery to consumers: capacity,
the maximum amount the system can handle, and transmission, the infrastructure
necessary to deliver electricity across the network. These capacity and
transmission costs are then allocated to the end-users according to the cost
causation principle. These charges are computed based on the customer demand on
coincident peak (CP) events, time intervals when the system-wide electric load
is highest. We tackle the problem of predicting CP events based on actual load
and forecast data on the load of different jurisdictions. In particular, we
identify two main use cases depending on the availability of a forecast. Our
approach generates scenarios and formulates Monte-Carlo estimators for
predicting CP-day and exact CP-hour events. Finally, we backtest the prediction
performance of strategies with adaptive threshold for the prediction task. This
analysis enables us to derive practical implications for load curtailment
through Battery Energy Storage System (BESS) solutions.
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