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실시간 열량계 정보를 활용한 단기 열 수요 예측 모델 개발에 관한 연구
송상화 ( Sang Hwa Song ),신광섭 ( Kwangsup Shin ),이재훈 ( Jaehun Lee ),정윤재 ( Yunjae Jung ),이재승 ( Jaeseung Lee ),윤석만 ( Seokmann Yoon ) (사)한국빅데이터학회 2020 한국빅데이터학회 학회지 Vol.5 No.2
지역난방 시스템은 서비스 지역 내 열 수요처들을 네트워크로 연결하여 중앙의 저비용 고효율 열 생산설비를 통해 열을 공급하는 에너지 시스템이다. 효율적인 열 공급 시시스템 운영을 위하여 지역 내 열 수요를 정확하게 예측하고 이를 바탕으로 열 생산 계획을 최적화하는 것이 중요하다. 본 연구에서는 지역 내 열수요처별 열 사용량 패턴에 대한 빅데이터 정보로 기계실별 실시간 열량계 정보를 반영한 열수요 예측모형을 제시하였다. 기존에도 열 수요예측에 활용되던 지역 전체 열수요 실적 합계와 함께 수요처별로 설치되어 있는 열량계로부터 실시간으로 수집한 개별 열수요 실적을 예측모형에 반영함으로써 열 수요처별로 상이한 열사용 패턴을 반영한 열 수요 예측이 가능할 것으로 기대된다. 지역난방 기업의 실제 열수요 실적을 바탕으로 열수요 예측 정확도를 측정한 결과 계절에 상관없이 기본 모형 대비 열량계 빅데이터를 반영할 경우 정확도가 올라가는 것으로 분석되었으며, 향후 열수요처별 다양한 형태의 데이터를 추가로 반영함으로써 열 수요 예측 정확도 향상이 가능할 것으로 예츢된다. District heating system supplies heat from low-cost high-efficiency heat production facilities to heat demand areas through a heat pipe network. For efficient heat supply system operation, it is important to accurately predict the heat demand within the region and optimize the heat production plan accordingly. In this study, a heat demand forecasting model is proposed considering real-time calorimeter information from local heat demands. Previous models considered ambient temperature and heat demand history data to predict future heat demands. To improve forecast accuracy, the proposed heat demand forecast model added big data from real-time calorimeters installed in the heat demands within the target region. By employing calorimeter information directly in the model, it is expected that the proposed forecast model is to reflect heat use pattern of each demand. Computational experiemtns based on the actual heat demand data shows that the forecast accuracy of the proposed model improved when the calorimeter big data is reflected.
비선형 연료 제약 및 유지보수 비용을 고려한 Mixed Integer Linear Programming 기반 발전기 주간 운용계획 최적화
송상화(Sang Hwa Song),이경식(Kyung Sik Lee) 한국경영과학회 2008 經營 科學 Vol.25 No.1
This paper considers a profit-based unit commitment problem with fuel consumption constraint and maintenance cost, which is one of the key decision problems in electricity industry. The nature of non-linearity inherent in the constraints and objective functions makes the problem intractable which have led many researches to focus on Lagrangian based heuristics. To solve the problem more effectively, we propose mixed integer programming based solution algorithm linearizing the complex non-linear constraints and objectives functions. The computational experiments using the real-world operation data taken from a domestic electricity power generator show that the proposed algorithm solves the given problem effectively.
송상화 ( Sanghwa Song ),고양석 ( Yangseok Koh ) 대한소화기학회 2022 대한소화기학회지 Vol.79 No.1
Neuroendocrine tumors (NETs) are low-grade malignancies arising from neuroendocrine cells. Primary hepatic neuroendocrine tumors (PHNETs) are extremely rare and difficult to differentiate from other liver tumors, such as hepatocellular carcinoma (HCC) or cholangiocarcinoma. A 22-year-old male presented with intermittent abdominal pain. A preoperative imaging study revealed a 5.1cm-sized heterogeneously enhancing mass in S6 of the liver, suggesting HCC. Laparoscopic right hepatectomy was performed, and a well-demarcated brown solid mass was found. The pathology report revealed a neuroendocrine tumor of the liver. 18F-fluorodeoxyglucose- positron emission tomography/computed tomography was performed postoperatively to exclude extrahepatic lesions, and no lesions were found. This is a rare case of PHNET that developed at a young age and was misdiagnosed as HCC preoperatively. This suggests that PHNET should be considered one of the differential diagnoses when a non-specific enhanced hepatic tumor is found, even when the patient is young. (Korean J Gastroenterol 2022;79:35-40)