Dependability measures are essential for various engineering problems, including those related to the planning and development of a wind farm. In this work, we address the problem of quantifying the mismatch between wind production and energy demand within energy communities by extending classical dependability metrics into a more general framework. The main contributions are threefold: (i) the introduction of a dependability analysis framework tailored to renewable generation and energy demand mismatch; (ii) the use of a discrete-time semi-Markov process to model wind speed for more accurate reliability assessment; (iii) the computation of dependability measures with demand acting as a time-varying barrier, providing a dynamic and realistic evaluation of system performance. We assess the model’s applicability by analyzing different energy communities formed either through random aggregation of users or via an optimization minimizing the mismatch between wind production and demand. The results demonstrate that the proposed model and metrics effectively assess wind production against energy demand, offering valuable insights for managing and designing energy communities.
Quantifying the mismatching of energy community demand and wind power: A reliability approach
D'Amico, Guglielmo
;Vergine, Salvatore
2026-01-01
Abstract
Dependability measures are essential for various engineering problems, including those related to the planning and development of a wind farm. In this work, we address the problem of quantifying the mismatch between wind production and energy demand within energy communities by extending classical dependability metrics into a more general framework. The main contributions are threefold: (i) the introduction of a dependability analysis framework tailored to renewable generation and energy demand mismatch; (ii) the use of a discrete-time semi-Markov process to model wind speed for more accurate reliability assessment; (iii) the computation of dependability measures with demand acting as a time-varying barrier, providing a dynamic and realistic evaluation of system performance. We assess the model’s applicability by analyzing different energy communities formed either through random aggregation of users or via an optimization minimizing the mismatch between wind production and demand. The results demonstrate that the proposed model and metrics effectively assess wind production against energy demand, offering valuable insights for managing and designing energy communities.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
