Authors: Felix Garcia-Torres, Pablo Baez-Gonzalez, Javier Tobajas, Francisco Vazquez, Emilio Nieto.
The transition to fully renewable energy systems will require increasing the number of reserves available to system operators to provide flexibility in the energy management process. The ability of microgrids to integrate distributed energy resources, loads and energy storage systems (ESS) is presented as a powerful flexibility tool. However, the control problem associated with microgrids increases with the number of connected devices. A structuring of distribution networks in micro-networks is proposed, focusing on their ability to provide flexible services. The complexity of the associated optimization algorithm is addressed using Distributed Model Predictive Control (MPC). The algorithm is divided into two steps. The first applies to the cooperative participation of microgrids in the day-ahead market. The second step encompasses the interaction with the OS that offers flexibility services in exchange for a financial benefit. The financial benefit is optimally distributed among the microgrids connected to the network to satisfy the power profile requested by the OS at the lowest cost. As the proposed control algorithm presents both continuous and binary variables, its associated optimization problem is formulated using the Mixed Logic Dynamics (MLD) framework, which gives rise to a Mixed Integral Quadratic Programming (MIQP) problem.