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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2021.10
- 수록면
- 1,820 - 1,824 (5page)
이용수
초록· 키워드
오류제보하기
Striking a balance between power supply and demand is the most imperative target for any electricity grid system. In order to address variability of renewable energy in the modern grid, a robust and elastic balancing scheme is required. Conventional model-based approaches can suffer from great performance degradation given the uncertainty induced by the renewable energy. As such, this study explores a model-free approach by proposing a reinforcement learning based pricing scheme that balances the power supply and demand. A price signal is considered as the control signal for the balance management. Case studies involving different market parameters and different time resolutions were conducted to show the effectiveness of the proposed methodology.
목차
Abstract
1. INTRODUCTION
2. SYSTEM MODELS
3. REINFORCEMENT LEARNING BASED PRICE CONTROL
4. NUMERICAL ANALYSIS
5. CONCLUSION
REFERENCES
참고문헌 (0)
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