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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Online Access: | https://www.mdpi.com/1996-1073/13/19/5188 |
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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 |
work_keys_str_mv |
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