Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System

Abstract

Optimal scheduling is a requirement for microgrids to participate in current and future energy markets. Although the number of research articles on this subject is on the rise, there is a shortage of papers containing detailed mathematical modeling of the distributed energy resources available in a microgrid. To address this gap, this paper presents in detail how to mathematically model resources such as battery energy storage systems, solar generation systems, directly controllable loads, load shedding, scheduled intentional islanding, and generation curtailment in the microgrid optimal scheduling problem. The proposed modeling also includes a methodology to determine the availability cost of battery and solar systems assets. Simulations were carried out considering energy prices from an actual time-of-use tariff, costs based on real market data, and scenarios with scheduled islanding. Simulation results provide support to validate the proposed model. Data illustrate how energy arbitrage can reduce microgrid costs in a time-of-use tariff. Results also show how the microgrid's self-sufficiency and the storage system's capacity can impact the microgrid's energy bill. The findings also bring out the need to consider the scheduled islanding event in the day-ahead optimization for microgrids.