Grid-aware Distributed Model Predictive Control of Heterogeneous Resources in a Distribution Network: Theory and Experimental Validation

TL;DR

This paper introduces a grid-aware distributed MPC framework for heterogeneous DERs in distribution networks, validated through real-scale microgrid experiments, ensuring grid constraints and dispatch plan tracking.

Contribution

It presents a novel two-layer scheduling and control framework combining day-ahead planning with real-time distributed MPC for heterogeneous resources.

Findings

Successfully tracks day-ahead dispatch plans in experiments

Maintains grid constraints on voltages and line capacities

Demonstrates effectiveness on a real-scale microgrid

Abstract

In this paper, we propose and experimentally validate a scheduling and control framework for distributed energy resources (DERs) that achieves to track a day-ahead dispatch plan of a distribution network hosting controllable and stochastic heterogeneous resources while respecting the local grid constraints on nodal voltages and lines ampacities. The framework consists of two algorithmic layers. In the first one (day-ahead scheduling), we determine an aggregated dispatch plan. In the second layer (real-time control), a distributed model predictive control (MPC) determines the active and reactive power set-points of the DERs so that their aggregated contribution tracks the dispatch plan while obeying to DERs operational constraints as well as the grids ones. The proposed framework is experimentally validated on a real-scale microgrid that reproduces the network specifications of the CIGRE microgrid benchmark system.