KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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A Study on Real-Time Operation Method of Urban Drainage System using Data-Driven Estimation

실시간 자료지향형 예측을 활용한 내배수 시설 운영기법 연구

  • Son, Ahlong (Disaster Information Research Division, National Disaster Management Research Institute) ;
  • Kim, Byunghyun (National Civil Defense and Disaster Management Training Institute, Ministry of the Interior and Safety) ;
  • Han, Kunyeun (Kyungpook National University)
  • 손아롱 (국립재난안전연구원 재난정보연구실) ;
  • 김병현 (행정안전부 국가민방위재난안전교육원) ;
  • 한건연 (경북대학교 토목공학과)
  • Received : 2017.08.08
  • Accepted : 2017.09.19
  • Published : 2017.12.01
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Abstract

This study present an efficient way of operating drainage pump station as part of nonstructural measures for reducing urban flood damage. The water level in the drainage pump station was forecast using Neuro-Fuzzy and then operation rule of the drainage pump station was determined applying the genetic algorithm method based on the predicted inner water level. In order to reflect the topographical characteristics of the drainage area when constructing the Neuro-Fuzzy model, the model considering spatial parameters was developed. Also, the model was applied a penalty type of genetic algorithm so as to prevent repeated stops and operations while lowering my highest water level. The applicability of the development model for the five drainage pump stations in the Mapo drainage area was verified. It is considered to be able to effectively manage urban drainage facilities in the development of these operating rules.

본 연구는 도시홍수 피해저감을 위한 비구조적 대책의 일환으로 배수펌프장의 효율적인 운영방안을 제시하고자 한다. 배수펌프장 내의 수위를 뉴로-퍼지모형을 통하여 예측하고 예측되는 내수위에 따라 유전자 알고리즘 기법을 적용하여 배수펌프장의 운영룰을 결정하고자 한다. 뉴로-퍼지모형 구축시 배수구역의 지형적 특성을 반영하기 위하여 공간적 매개변수를 고려한 GeoANFIS모형을 개발하였고 배수펌프장 내 최고수위를 저하시키면서 반복적인 정지와 운영이 발생하지 않도록 벌칙유형의 유전자 알고리즘을 적용하였다. 마포 배수구역 내 5개의 배수펌프장(마포, 합정, 상수, 봉인, 당인)에 대하여 개발 모형의 적용성을 검증하였다. 이러한 운영룰의 개발로 효과적으로 내배수 시설을 운영할 수 있을 것으로 판단된다.

Keywords

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