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

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...

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Main Authors: Vanderlei Aparecido Silva, Alexandre Rasi Aoki, Germano Lambert-Torres
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/19/5188
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spelling doaj-e4f0ed6770874d908c6a99198d99af9a2020-11-25T03:59:17ZengMDPI AGEnergies1996-10732020-10-01135188518810.3390/en13195188Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage SystemVanderlei Aparecido Silva0Alexandre Rasi Aoki1Germano Lambert-Torres2Department of Electrical Engineering, Federal University of Parana, Curitiba 82590-300, BrazilDepartment of Electrical Engineering, Federal University of Parana, Curitiba 82590-300, BrazilR&D Department, Gnarus Institute, Itajuba 37500-052, BrazilOptimal 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.https://www.mdpi.com/1996-1073/13/19/5188optimal schedulingmicrogrid modelingmicrogrid optimizationbattery energy storage systemenergy management systemlinear programming
collection DOAJ
language English
format Article
sources DOAJ
author Vanderlei Aparecido Silva
Alexandre Rasi Aoki
Germano Lambert-Torres
spellingShingle Vanderlei Aparecido Silva
Alexandre Rasi Aoki
Germano Lambert-Torres
Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
Energies
optimal scheduling
microgrid modeling
microgrid optimization
battery energy storage system
energy management system
linear programming
author_facet Vanderlei Aparecido Silva
Alexandre Rasi Aoki
Germano Lambert-Torres
author_sort Vanderlei Aparecido Silva
title Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
title_short Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
title_full Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
title_fullStr Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
title_full_unstemmed Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
title_sort optimal day-ahead scheduling of microgrids with battery energy storage system
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-10-01
description 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.
topic optimal scheduling
microgrid modeling
microgrid optimization
battery energy storage system
energy management system
linear programming
url https://www.mdpi.com/1996-1073/13/19/5188
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