Modern active distribution networks possess significant potential to deliver ancillary services to transmission networks owing to the rising integration of renewable energy sources. This study explores the provision of primary frequency support from active distribution network to transmission network via price-based transactive control of microgrid inverters. The proposed method aims to achieve efficient coordination among microgrids, optimizing their utility, while also assisting the active distribution network in optimal primary frequency support provision to transmission network. The feasibility of this approach for real-time application is validated using a real-time simulator.

With the phenomenal growth in renewable energy generation, the conventional synchronous generator-based power plants are gradually getting replaced by renewable energy sources-based microgrids. Such transition gives rise to the challenges of procuring various ancillary services from microgrids. We propose a distributed optimization framework that coordinates multiple microgrids in an active distribution network for provisioning passive voltage support-based ancillary services while satisfying operational constraints. Specifically, we exploit the reactive power support capability of the inverters and the flexibility offered by storage systems available with microgrids for provisioning ancillary service support to the transmission grid. We develop novel mixed-integer inequalities to represent the set of feasible active and reactive power exchange with the transmission grid that ensures passive voltage support. The proposed alternating direction method of multipliers-based algorithm is fully distributed, and does not require the presence of a centralized entity to achieve coordination among the microgrids. We present detailed numerical results on the IEEE 33-bus distribution test system to demonstrate the effectiveness of the proposed approach and examine the scalability and convergence behavior of the distributed algorithm for different choice of hyperparameters and network sizes.