Towards Optimal Energy Management of Microgrids with a Realistic Model

TL;DR

This paper introduces a two-stage optimization method for energy management in grid-connected microgrids, effectively balancing cost, operational constraints, and uncertainties in load and renewable generation.

Contribution

It presents a novel two-stage scheduling approach combining day-ahead and hour-ahead optimization for microgrid energy management with realistic models.

Findings

Efficient scheduling reduces long-term operating costs.

Handles large uncertainties in load and renewable generation.

Provides solutions suitable for limited computational resources.

Abstract

This work considers energy management in a grid-connected microgrid which consists of multiple conventional generators (CGs), renewable generators (RGs) and energy storage systems (ESSs). A two-stage optimization approach is presented to schedule the power generation, aimed at minimizing the long-term average operating cost subject to operational and service constraints. The first stage of optimization determines hourly unit commitment of the CGs via a day-ahead scheduling, and the second stage performs economic dispatch of the CGs, ESSs and energy trading via an hour-ahead scheduling. The combined solution meets the need of handling large uncertainties in the load demand and renewable generation, and provides an efficient solution under limited computational resource which meets both short-term and long-term quality-of-service requirements. The performance of the proposed strategy is evaluated by simulations based on real load demand and renewable generation data.