Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty
Optimal operation of the battery energy storage system (BESS) is very important to reduce the running cost of a microgrid. Rolling horizon-based scheduling, which updates the optimal decision based on the latest information, is widely applied to microgrid operation. In this paper, the optimal schedu...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-05-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/6/1371 |
| _version_ | 1811186421415804928 |
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| author | Hong-Chao Gao Joon-Ho Choi Sang-Yun Yun Hak-Ju Lee Seon-Ju Ahn |
| author_facet | Hong-Chao Gao Joon-Ho Choi Sang-Yun Yun Hak-Ju Lee Seon-Ju Ahn |
| author_sort | Hong-Chao Gao |
| collection | DOAJ |
| description | Optimal operation of the battery energy storage system (BESS) is very important to reduce the running cost of a microgrid. Rolling horizon-based scheduling, which updates the optimal decision based on the latest information, is widely applied to microgrid operation. In this paper, the optimal scheduling of a microgrid, considering the energy cost, demand charge, and the battery wear-cost, is formulated as a mixed integer linear programming (MILP) problem. This paper also deals with two practical and important issues when applying the rolling-horizon strategy to BESS scheduling. First, to mitigate the high dependency of the load forecast on the latest information, a confidence weight parameter method is proposed. Second, a new target state of charge (SOC) assignment method is proposed to avoid the depletion of BESS and to reduce the wear-cost of the battery. In addition to the optimal scheduling, a novel real-time control scheme is proposed to mitigate the effect of the forecast uncertainty. The performance of the proposed methods is tested with data measured from a campus microgrid. |
| first_indexed | 2024-04-11T13:45:30Z |
| format | Article |
| id | doaj.art-72c69878ff404e4baf0bac8b55f9f6b2 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-11T13:45:30Z |
| publishDate | 2018-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-72c69878ff404e4baf0bac8b55f9f6b22022-12-22T04:21:07ZengMDPI AGEnergies1996-10732018-05-01116137110.3390/en11061371en11061371Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast UncertaintyHong-Chao Gao0Joon-Ho Choi1Sang-Yun Yun2Hak-Ju Lee3Seon-Ju Ahn4Department of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, KoreaDepartment of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, KoreaDepartment of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, KoreaEnergy System Group Energy New Business Laboratory, Korea Electric Power Research Institute, Daejeon 34056, KoreaDepartment of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, KoreaOptimal operation of the battery energy storage system (BESS) is very important to reduce the running cost of a microgrid. Rolling horizon-based scheduling, which updates the optimal decision based on the latest information, is widely applied to microgrid operation. In this paper, the optimal scheduling of a microgrid, considering the energy cost, demand charge, and the battery wear-cost, is formulated as a mixed integer linear programming (MILP) problem. This paper also deals with two practical and important issues when applying the rolling-horizon strategy to BESS scheduling. First, to mitigate the high dependency of the load forecast on the latest information, a confidence weight parameter method is proposed. Second, a new target state of charge (SOC) assignment method is proposed to avoid the depletion of BESS and to reduce the wear-cost of the battery. In addition to the optimal scheduling, a novel real-time control scheme is proposed to mitigate the effect of the forecast uncertainty. The performance of the proposed methods is tested with data measured from a campus microgrid.http://www.mdpi.com/1996-1073/11/6/1371BESS schedulingforecast uncertaintyrolling-horizonreal-time control scheme |
| spellingShingle | Hong-Chao Gao Joon-Ho Choi Sang-Yun Yun Hak-Ju Lee Seon-Ju Ahn Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty Energies BESS scheduling forecast uncertainty rolling-horizon real-time control scheme |
| title | Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty |
| title_full | Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty |
| title_fullStr | Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty |
| title_full_unstemmed | Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty |
| title_short | Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty |
| title_sort | optimal scheduling and real time control schemes of battery energy storage system for microgrids considering contract demand and forecast uncertainty |
| topic | BESS scheduling forecast uncertainty rolling-horizon real-time control scheme |
| url | http://www.mdpi.com/1996-1073/11/6/1371 |
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