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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2016.10
- 수록면
- 562 - 567 (6page)
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초록· 키워드
오류제보하기
A novel load forecasting mechanism that uses fuzzy logic and big data, termed multipoint fuzzy prediction (MPFP), is proposed. The prediction mechanism is based on historical data and, therefore, is adaptive to dynamic changes over time when the database is updated properly. The MPFP can be combined with green buildings and renewable energy sources to reduce peak loads and energy consumption. An energy management system (EMS) can be integrated into the framework to achieve an improved level of performance. On the basis of a prediction of load curves, the EMS can discharge energy storage devices when electricity prices are high and charge them when electricity prices are low, reducing costs. Real power demand data were employed to illustrate the validity of the proposed MPFP scheme.
목차
Abstract
1. INTRODUCTION
2. SYSTEM ARCHITECTURE
3. MULTIPOINT FUZZY PREDICTION SCHEME
4. EXPERIMENTAL RESULTS
5. CONCLUSION
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2017-003-001868737