Scenario-Based Hybrid Optimization and Exponential Smoothing Forecasting for Enhanced Microgrid Energy Management

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

This paper presents a hybrid energy management strategy for microgrids that integrates long-term global optimization with real-time dynamic adaptive control enhanced by predictive forecasting using exponential smoothing. The proposed method is designed to maximize self-consumption and minimize grid dependency while ensuring the battery's state-of-charge remains within safe operational limits. Simulation results across multiple scenarios demonstrate that the hybrid approach improves energy efficiency and reduces overall operational costs compared to baseline strategies. The method achieves a high self-consumption ratio and maintains battery stability, even under rapidly changing conditions. These findings highlight the potential of the hybrid approach to provide robust, cost-effective energy management for microgrids.

Article activity feed