A robust MPC method for microgrid energy management based on distributed optimization

Abstract

In this work we present a novel distributed MPC method for microgrid energy management based on distributed optimization. In order to cope with uncertainty in prices and renewable energy production, we adopt a robust min-max approach that optimizes at each time step the worst case scenario of the objective function. Combining the advantages of MPC and distributed optimization, the resulting algorithm is suitable for the control of large-scale microgrids in which renewable energy resources are employed. Moreover, since it is based on novel distributed optimization algorithms, the method allows the future power profiles to be computed for each microgrid component without sharing this information with the others. Simulation results for a DC microgrid system model show the effectiveness of the proposed method. The algorithm is tested in two different scenarios: in presence of uncertainties and considering perfect knowledge of the future price and power profiles.

Resilient Microgrid Energy Management Algorithm Based on Distributed Optimization

“…This article presents a DO-based MPC algorithm for energy management that guarantees the privacy of local information. Preliminary results have been presented in [34]. In particular, we design the EMS as an MPC controller in which the optimization problem is solved using a DO algorithm that allows all the local information of each agent to be kept private.…”

“…The microgrid is composed of five agents: renewable generators, loads, storage systems, EVs, and utility grid connections. The model presented in this section builds upon the model developed in [34] with the addition of EVs and fault models.…”