화학공학소재연구정보센터
홈 로그인 로그아웃 연락처 사이트맵
Korean Chemical Engineering Research, Vol.48, No.5, 589-597, October, 2010
Export Citation
하수처리장의 고도처리 upgrading 설계와 공정 최적화를 위한 다변량 통계분석
Design of a Wastewater Treatment Plant Upgrading to Advanced Nutrient Removal Treatment Using Modeling Methodology and Multivariate Statistical Analysis for Process Optimization
김민정, 김민한, 김용수, 유창규†
  • 경희대학교 공과대학 환경학 및 환경공학과/환경연구센터, 446-701 경기도 용인시 기흥구 서천동 1번지
MinJeong Kim, MinHan Kim, YongSu Kim, and ChangKyoo Yoo†
  • Center for Environmental Studies, Dept. of Environmental Science and Engineering, College of Engineering, Kyung Hee University, 1 Seocheon-dong, Giheung-gu, Yongin-Si, Gyeonggi 446-701, Korea
E-mail:
초록
하수처리 시스템에서의 생물학적 영양염류 기준이 강화됨에 따라, 표준활성슬러지공법으로 운전 중인 하수처리장의 고도처리 공법으로의 개보수 필요성이 증가하고 있다. 그러나 실제 하수처리 시스템에서의 다양한 유입조건 및 운전조건의 복잡한 반응 구성으로 인해 실험을 통하여 개보수된 고도처리공법의 최적조건을 찾는 것은 쉽지 않은 일이며, 이는 많은 시간과 비용을 소모하여 비효율적이다. 따라서 본 연구에서는 활성슬러지공정모델(ASMs)을 기반으로 한 하수처리장의 모델링 및 시뮬레이션 기법을 통하여 하수처리장의 고도처리공법으로의 upgrading 설계를 수행하며, 이를 통계적이며 체계적으로 접근하기 위해 반응표면분석법(Response surface method)을 통한 고도처리공법의 설계 최적화를 수행하였다. 또한 실규모 하수처리장에서의 운전 최적화를 위해서는 하수처리의 동력학적 매개변수에 대한 정확한 분석이 수행되어야 한다. 본 연구에서는 다변량 통계분석 기법인 부분최소승자법(PLS)을 통하여 하수처리 시스템의 동력학적 매개변수 간의 상관관계를 파악하며, 고도처리공법 하수처리장의 운전 결과에 가장 큰 영향을 미치는 매개변수를 도출하였다. 본 연구를 통해 하수처리장의 고도처리공법 upgrading 설계 및 운전 최적화를 위한 방법론을 제시하였으며, 이를 통하여 설계시간 및 경비 절감 등 고도처리공법으로의 고효율적인 개보수가 가능할 것으로 예상된다.
Strengthening the regulation standard of biological nutrient in wastewater treatment plant(WWTP), the necessity of repair of WWTP which is operated in conventional activated sludge process to advanced nutrient removal treatment is increased. However, in full-scale wastewater treatment system, it is not easy to fine the optimized operational condition of the advanced nutrient removal treatment through experiment due to the complex response of various influent conditions and operational conditions. Therefore, in this study, an upgrading design of conventional activated sludge process to advanced nutrient removal process using the modeling and simulation method based on activated sludge model(ASMs) is executed. And a design optimization of advanced treatment process using the response surface method(RSM) is carried out for statistical and systematic approach. In addition, for the operational optimization of fullscale WWTP, a correct analysis about kinetic variables of wastewater treatment is necessary. In this study, through partial least square(PLS) analysis which is one of the multivariable statistical analysis methods, a correlation between the kinetic variables of wastewater treatment system is comprehended, and the most effective variables to the advanced treatment operation result is deducted. Through this study, the methodology for upgrading design and operational optimization of advanced treatment process is provided, and an efficient repair of WWTP to advanced treatment can be expected reducing the design time and costs.
Keywords:Repair to Advanced Treatment Process;GPS-X Modeling;Activated Sludge Model(ASMs);Response Surface Method;Optimization of Advanced Treatment Process;PLS Analysis
  1. Heo HS, “Optimization of Advanced Sewage Treatmentprocess Treating High Fraction of Non Degradable Material,” Ph. D. thesis, the Univ. of Seoul, Korea (2006)
  2. Jin HJ, “A Study on the Optimum Design of Petrochemical Wastewater Treatment Process Using a GPS-X Model,” Ph. D. thesis, Chonnam national Univ., Korea (2007)
  3. Lee JM, “A Study on Converting a Existing Activated Sludge Plant into Biological Nutrient Removal Plant Using a Computer Model,” Ph. D. thesis, Kyung-gee Univ., Korea (2007)
  4. No YK, “A study on Optimization of Intermittently Aerated Contact Oxidation Process by Simulation,” Ph. D. thesis, the Univ. of Seoul, Korea (2006)
  5. Rho HY, Gil KI, J. Korean Society on Water Quality, 23, 309 (2007)
  6. Park JM, Lee HW, DICER Tech. Info Part 1, 3, 193 (2004)
  7. Kim M, Yoo C, Korean Chem. Eng. Res., 46(3), 610 (2008)
  8. Mogens H, Willi G, Takashi M, Mark L, Activated Sludge Models ASM1, ASM2, ASM2d, and ASM3., IWA Publishing in its Scientific and Technical Report series (2000)
  9. Henze M, Gujer W, Mino T, Loosdrecht M, Activated Sludge Models ASM1, ASM2, ASM2d and ASM3, IWA Scientific and Technical report No.9, IWA, UK (1999)
  10. Henze M, Gujer W, Mino T, Matsuo T, Wentzel MC, Marais GR, Loosdrecht MCM, Wat. Sci. Technol., 39, 165 (1999)
  11. Kim M, Rao AS, Yoo C, Ind. Eng. Chem. Res., 48(13), 6363 (2009)
  12. Sung SY, “Comparison of A Weight of Desirability Function for Multiresponse Optimization,” Ph. D. thesis, Ewha womans Univ., Korea (2003)
  13. Yamamoto T, Shimameguri A, Ogawa M, Hashimoto I, Kano M, IFAC Syposium on Advanced Control of Chemical Processes, 405-410 (2004)
  14. Rosen C, “A Chemometric Approach to Process Monitoring and Control with Applications to Wastewater Treatment Operation,” Ph. D. thesis, Lund Univ., Sweden (2001)
  15. Lee SW, “The Environmental Engineer for Water Quality,” SeongAn-dang (2006)
  16. Park SH, “The Application of Media to Enhance Phosphorus Removal Efficiency in A2O Process of Wastewater Treatment Plant,” Ph. D. thesis, Kyungnam national Univ., Korea (2008)
  17. Reynolds TD, Richards PA, “Unit Operations and Processes in Environmental Engineering, 2nd Edition,” BS:PWS publishing company (1996)
  18. Syed RQ, “Wastewater Treatment Plants(Planning, Design, and Operation), 2nd Edition,” University of Texas at Arlington (1998)
  19. Hydromantis, Inc., GPS-X Tutorial Guide, Hydromantis (2004)
  20. Lee CH, “Determination of the Optimal Design Parameters of Advanced Wastewater Treatment Process with Acid Fermentation using GPS-X Model,” Ph. D. thesis, the Univ. of Hanyang, Korea (2006)
  21. Kurt B, “The Monte Carlo Method in Condensed Matter hysics,” Springer, New York (1995)