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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- 한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2022 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.13 No.1
- 발행연도
- 2022.1
- 수록면
- 218 - 226 (9page)
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초록· 키워드
오류제보하기
Pollutants emitted by ships have a major impact on global warming and climate change. And the International Maritime Organization (IMO) amended the Convention on the Prevention of Pollution from Ships to limit greenhouse gas emissions through ship energy efficiency regulations. The Hybrid Electric Propulsion System (HEPS), which meets these requirements and minimizes fuel consumption, provides the optimal solution.
Electric powered ships play a major role in reducing fuel consumption as well as increasing energy efficiency. However, in order for the battery and generator to be used in conjunction with each other, an optimization algorithm is required. Also, in the case of electric propulsion ships, propulsion loads and pulse loads have a great effect on the onboard power system.
To solve this, a reliable power management strategy is needed that can manage the distribution of power between different power sources in real time and reduce fuel consumption. Therefore, in this paper, we propose an LCS (Load Control System) algorithm for systematic power supply of generators and batteries. It also calculates the generator and battery capacity according to the maximum required power to apply the optimized algorithm.
And when the LCS algorithm was applied by creating a load scenario according to the operation mode of the ship, the operating ratio in the optimal efficiency range was investigated. In addition, if the abnormal state of the system interlocked with the LCS is identified, the operating loss can be minimized. To this end, based on the flight data acquired through LCS, basic research necessary to implement an ML (Machine Learning)-based anomaly detection function is performed.
Electric powered ships play a major role in reducing fuel consumption as well as increasing energy efficiency. However, in order for the battery and generator to be used in conjunction with each other, an optimization algorithm is required. Also, in the case of electric propulsion ships, propulsion loads and pulse loads have a great effect on the onboard power system.
To solve this, a reliable power management strategy is needed that can manage the distribution of power between different power sources in real time and reduce fuel consumption. Therefore, in this paper, we propose an LCS (Load Control System) algorithm for systematic power supply of generators and batteries. It also calculates the generator and battery capacity according to the maximum required power to apply the optimized algorithm.
And when the LCS algorithm was applied by creating a load scenario according to the operation mode of the ship, the operating ratio in the optimal efficiency range was investigated. In addition, if the abnormal state of the system interlocked with the LCS is identified, the operating loss can be minimized. To this end, based on the flight data acquired through LCS, basic research necessary to implement an ML (Machine Learning)-based anomaly detection function is performed.
목차
Abstract
I. INTRODUCTION
II. Proposed methodology
III. RESULTS
IV. DISCUSSION AND CONCLUSIONS
REFERENCES
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