# Robust Power Scheduling for Microgrids with Uncertainty in Renewable Energy Generation

## TL;DR

This paper introduces a robust, model predictive power scheduling algorithm for microgrids with renewable energy, effectively managing uncertainty in solar generation while avoiding over-conservatism.

## Contribution

It proposes a novel soft constraint approach within a model predictive framework to handle battery State of Charge limits under renewable energy uncertainty.

## Key findings

- The approach effectively manages SoC constraints with minimal violations.
- Quadratic programming solves the scheduling problem efficiently.
- Results show improved robustness and flexibility in microgrid power management.

## Abstract

A robust power scheduling algorithm is proposed to schedule power flow between the main electricity grid and a microgird with solar energy generation and battery energy storage subject to uncertainty in solar energy production. To avoid over-conservatism in power scheduling while guaranteeing robustness against uncertainties, time-varying "soft" constraints on the State of Charge (SoC) of the battery are proposed. These soft constraints allow SoC limit violation at steps far from the current step but aim to minimize such violations in a controlled manner. The model predictive formulation of the problem over a receding time horizon ensures that the resulting solution eventually conforms to the hard SoC limits of the system at every step. The optimization problem for each step is formulated as a quadratic programming problem that is solved iteratively to find the soft constraints that are closest to the hard ones and still yield a feasible solution. Optimization results demonstrate the effectiveness of the approach.