Managing Load Uncertainty Using inter/intra-Day Scheduling of BESS/EV
배터리 에너지 저장장치/전기차량 스케줄링을 통한 부하 불확실성 관리 기법
- 주제(키워드) dynamic programming , Energy Storage System , Battery degradation , peak shaving , Optimal scheduling , forecast error
- 발행기관 서강대학교 일반 대학원
- 지도교수 김홍석
- 발행년도 2017
- 학위수여년월 2017. 8
- 학위명 석사
- 학과 및 전공 일반대학원 전자공학과
- 실제URI http://www.dcollection.net/handler/sogang/000000062032
- 본문언어 영어
- 저작권 서강대학교 논문은 저작권보호를 받습니다.
초록/요약
to minimize total cost and loss caused by prediction error. To minimize total cost, we should consider time of use(TOU), peak power and battery degradation. In order to consider degradation cost, dynamic programming is used for making optimal schedule. Meanwhile, Under the Korea commercial and industrial tariff, peak power measured for only 15min determines the monthly base cost and affects for a year. Thus peak shaving is critical to minimize total cost. Peak shaving operation is very vulnerable to prediction errors because the result from day-ahead optimization is deterministic. For this reason conservative strategies are more suitable even though those have an extra cost due to surplus power against uncertainty. Our approach is to be robust prediction error and minimize unnecessary surplus power. By using correlation between error and margin power, we estimated it with measured error and adjust day-ahead schedule to get closer to optimum. In addition, calibration method is designed to allocate margin power in real time. In this way we reduce the loss of peak power due to prediction error by 59%
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