LAPSE:2023.26818
Published Article

LAPSE:2023.26818
Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System
April 3, 2023
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.
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.
Record ID
Keywords
availability cost, battery energy storage system, controllable loads, energy management system, intentional islanding, linear programming, microgrid modeling, microgrid optimization, optimal scheduling, shiftable loads
Subject
Suggested Citation
Silva VA, Aoki AR, Lambert-Torres G. Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System. (2023). LAPSE:2023.26818
Author Affiliations
Silva VA: Department of Electrical Engineering, Federal University of Parana, Curitiba 82590-300, Brazil [ORCID]
Aoki AR: Department of Electrical Engineering, Federal University of Parana, Curitiba 82590-300, Brazil [ORCID]
Lambert-Torres G: R&D Department, Gnarus Institute, Itajuba 37500-052, Brazil [ORCID]
Aoki AR: Department of Electrical Engineering, Federal University of Parana, Curitiba 82590-300, Brazil [ORCID]
Lambert-Torres G: R&D Department, Gnarus Institute, Itajuba 37500-052, Brazil [ORCID]
Journal Name
Energies
Volume
13
Issue
19
Article Number
E5188
Year
2020
Publication Date
2020-10-05
ISSN
1996-1073
Version Comments
Original Submission
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PII: en13195188, Publication Type: Journal Article
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LAPSE:2023.26818
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https://doi.org/10.3390/en13195188
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Apr 3, 2023
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