Grid Services Optimization From Multiple Microgrids

We propose a multi-case, multi-period AC model to coordinate the procurement of grid services from an aggregation of connected distributed energy resources and microgrids. The proposed model aggregates the capabilities of all resources in the system to manage the network's power flow and provide services to the power grid at the point of common coupling. The modeling approach enables incorporating a number of services (e.g., reserve, regulation, and reactive power capacity) with simple addition of service defining equations. We also propose a solution methodology for the resultant mixed-integer quadratically-constrained programming (MICQP) problem based on successive linear programming (SLP). The SLP is augmented with a fix-binary algorithm that promises efficient handling of discrete variables. The paper also provides a decentralized formulation that decomposes the problem into an aggregator problem and multiple small $\mu $ Gs' problems. We integrate the SLP method with the analytical target cascading (ATC) algorithm to optimize the overall system with minimal shared information between the aggregator and the $\mu $ Gs. Case studies analyze the convergence of the centralized and the decentralized approaches, present the optimal power and service schedules of the tested system, and study the network conditions under service calls.