Optimal operation of microgrids with risk-constrained state of charge

TL;DR

This paper introduces a stochastic MPC approach for islanded microgrids with renewable energy, using risk-based constraints to ensure reliable energy storage management under uncertainty.

Contribution

It presents a novel convex approximation of risk constraints for microgrid operation, enabling control over violation frequency and magnitude.

Findings

Risk constraints can be formulated as conic constraints.

The approach effectively manages energy storage within bounds under uncertainty.

Numerical case study demonstrates practical applicability.

Abstract

In this paper we present a stochastic scenario-based model predictive control (MPC) approach for the operation of islanded microgrids with high share of renewable energy sources. We require that the stored energy remains within given bounds with a certain probability using risk-based constraints as convex approximations of chance constraints. We show that risk constraints can generally be cast as conic constraints and, unlike chance constraints, can control both the number and average magnitude of constraint violations. Lastly, we demonstrate the risk-constrained stochastic MPC in a numerical case study.