A framework for data-driven decision support for operational planning in active distribution networks

This paper describes a framework envisioned to be part of operational planning to help Distribution System Operators (DSOs) securely operate the grid. The main two components of the framework are workflows for grid situational awareness and dynamic tariffs for implicit control of demand and distributed generation. Digital Twins (DT) and Internet of Things (IoT) technologies are leveraged to compose a modular framework to execute specific workflows aimed at increasing the observability of the grid state and to analyse the impact of dynamic tariffs on alleviating grid violations. Data analytics and grid modelling are applied to assimilate data, detect anomalies either due to incipient grid faults or demand and generation irregularities, calculate power flows, estimate the risk of grid violations such as cable overloading, and aid the design of effective grid tariffs. In addition to presenting the concept of the AISOP project, the Digital Process Twin (DPT) framework, progress on anomaly detection and power flow forecasting is presented, and an outlook on implementation aspects is given.