A Microgrid Energy Management System Based on the Rolling Horizon Strategy

TLDR

The study proposes a rolling‑horizon energy management system for a renewable microgrid, integrating forecast information and an economic comparison with standard unit commitment to enable practical deployment. The EMS solves a mixed‑integer optimization at each step, issuing generation set points and demand‑side signals for PV, wind, diesel, and storage units, using phenomenological solar/wind forecasts and a neural‑network consumption predictor, and is tested on real Chilean microgrid data. Simulation results under varied operating conditions demonstrate the economic advantage of the rolling‑horizon approach.

Abstract

A novel energy management system (EMS) based on a rolling horizon (RH) strategy for a renewable-based microgrid is proposed. For each decision step, a mixed integer optimization problem based on forecasting models is solved. The EMS provides online set points for each generation unit and signals for consumers based on a demand-side management (DSM) mechanism. The proposed EMS is implemented for a microgrid composed of photovoltaic panels, two wind turbines, a diesel generator and an energy storage system. A coherent forecast information scheme and an economic comparison framework between the RH and the standard unit commitment (UC) are proposed. Solar and wind energy forecasting are based on phenomenological models with updated data. A neural network for two-day-ahead electric consumption forecasting is also designed. The system is tested using real data sets from an existent microgrid in Chile (ESUSCON). The results based on different operation conditions show the economic sense of the proposal. A full practical implementation of the system for ESUSCON is envisioned.