This paper presents a grid-aware probabilistic approach to compute the aggregated flexibility at the grid connection point (GCP) of active distribution networks (ADNs) to allow the participation of DERs in ancillary services (AS) markets. Specifically, an optimal power flow (OPF) method is used to compute the aggregated capability for the provision of multiple AS at the GCP of an ADN over the full AS provision horizon. The proposed method extends current approaches for the time-coupled flexibility aggregation, allowing to consider multiple services simultaneously, ensure cost-effectiveness of the used DERs and handle uncertainties in a probabilistic way. The disaggregation of the total flexibility into individual DERs power flexibilities accounts for the operational costs associated to the provision of different services. This ensures cost-effectiveness while maximizing the value of the aggregated flexibility, assuming known service prices. Empirical uncertainty sets are obtained to achieve a predefined coverage of the probability distribution in line with recent developments in the Nordic AS markets. Finally, a feeder-decomposition approach is proposed to ensure applicability to realistic distribution networks with a large number of buses. Case studies show the effectiveness of the method, highlight the importance of network constraints and time-coupling and illustrate its applicability to realistic distribution systems.This paper presents a grid-aware probabilistic approach to compute the aggregated flexibility at the grid connection point (GCP) of active distribution networks (ADNs) to allow the participation of DERs in ancillary services (AS) markets. Specifically, an optimal power flow (OPF) method is used to compute the aggregated capability for the provision of multiple AS at the GCP of an ADN over the full AS provision horizon. The proposed method extends current approaches for the time-coupled flexibility aggregation, allowing to consider multiple services simultaneously, ensure cost-effectiveness of the used DERs and handle uncertainties in a probabilistic way. The disaggregation of the total flexibility into individual DERs power flexibilities accounts for the operational costs associated to the provision of different services. This ensures cost-effectiveness while maximizing the value of the aggregated flexibility, assuming known service prices. Empirical uncertainty sets are obtained to achieve a predefined coverage of the probability distribution in line with recent developments in the Nordic AS markets. Finally, a feeder-decomposition approach is proposed to ensure applicability to realistic distribution networks with a large number of buses. Case studies show the effectiveness of the method, highlight the importance of network constraints and time-coupling and illustrate its applicability to realistic distribution systems.
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Jacobs et al. (2026) studied this question.
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