Regression Monte Carlo for Microgrid Management

TL;DR

This paper presents a Regression Monte Carlo-based methodology for optimizing microgrid management, integrating renewable sources, storage, and diesel generation to improve efficiency and reliability.

Contribution

It introduces a novel application of Regression Monte Carlo algorithms to microgrid management, enabling better decision-making for system design and operation.

Findings

Optimal grid design identified through simulations

Improved management of renewable and storage integration

Enhanced reliability and efficiency of microgrid operations

Abstract

We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device is used to shift power from times of high renewable production to times of high demand. We introduce a methodology to solve microgrid management problem using different variants of Regression Monte Carlo algorithms and use numerical simulations to infer results about the optimal design of the grid.