The Development of Model for the Prediction of Water Demand using Kalman Filter Adaptation Model in Large Distribution System

칼만필터의 적응형모델 기법을 이용한 광역상수도 시스템의 수요예측 모델 개발

  • Published : 2001.03.01

Abstract

Kalman Filter model of demand for residental water and consumption pattern wore tested for their ability to explain the hourly residental demand for water in metro-politan distribution system. The daily residental demand can be obtained from Kalman Filter model which is optimized by statistical analysis of input variables. The hourly residental demand for water is calculated from the daily residental demand and consumption pattern. The consumption pattern which has 24 time rates is characterized by data granulization in accordance with season kind, weather and holiday. The proposed approach is applied to water distribution system of metropolitan areas in Korea and its effectiveness is checked.

본 논문에서는 광역상수도 시스템의 취·송수 설비의 최적운영계획에 필수적으로 요구되는 시간 단위 용수 수요량 예측을 위하여 칼만 필터에 의한 수요 예측 모델 구축 및 배수패턴 해석 기법을 제안하고, 기존 시스템의 실 데이터를 이용하여 시뮬레이션 수행 결과 제안된 기법의 유용성이 검증되었다. 광역상수도 시스템에서 취·송수 설비의 최적운영계획 수립을 위해서는 예측 시간 범위를 최소 하루 단위 이상으로 유지해야 한다. 따라서, 제안된 기법에서는 기존의 시간별 실적데이터의 시계열에 의한 예측을 이용하는 것이 아니라 모델로부터 예측된 일 수요량에 배수패턴을 곱하여 24시간의 시간별 용수 수요량을 예측한다. 일 수요량 예측을 위한 칼만 필터 모델은 입력변수의 통계적 분석에 의해 모델 구조 최적화가 효과적으로 구현되고 배수패턴은 데이터 Granulization에 의해 얻어진다.

Keywords

References

  1. Proceeding of JSCE v.246 Prediction of Water Quality by Heuristic Self-Oraganization Ichikawa. A;Ikeda. S
  2. Holden-day Time Series Analysis Forecasting and Control Box. G. E;Jenkins. C. m
  3. TIME SERIES ANALYSIS. THEORY AND PRACTICE 7 Ilustration of the Use of a General Time Series Model Melard. G
  4. Proceeding of JSCE, No. 407/Ⅳ-11 Time-Series Prediction System and AROP Model in Transportation Demand Analysis Tsutsumi. M;Chishaki. T
  5. JOURNAL OF TIME SERIES ANALYSES v.9 no.2 On a Class of Nonstationary Process Gray. H. L;Nein. F. Z
  6. North Atlantic Treaty Organization AGARD Report, No. 139 Theory and Application of Kalman Filtering C. T. Leondes(ed.)
  7. Advances in Control Systems v.3 Kalman Filtering Techniques H. W. Sorenson;C. T. Leondes(ed.)
  8. Kalman Filtering: Theory and Application H. W. Sorenson(ed.)
  9. Appllication of Kalman Filtering in Computer Relaying of Power Systems A. A. Girgis
  10. IEEE Trans. on power Apparatus and Systems v.PAS-100 no.7 Application of Kalman Filtering in Computer Relaying A. A. Girgis;R. G. Brown
  11. Transportation Research Record v.1556 Artificial Neural Network-Based Approach To Modeling Trip Production Ardeshir Faghri;Sandeep Aneja
  12. Journal of EICA v.1 no.1 Altitude of Water Operation Control Package Kubota Masakazu;Kurotani Kenichi;Akiyama Hirohide;Morimoto Masanori
  13. Proceeding of JSCE Practical Examples of ARUMA Modelling Anderson. O. D
  14. TIME SERIES ANALYSIS. THEORY AND PRACTICE 7 Seasonal Moving Average for Irregular in the Series and with Moving Seasonality Cholette. P. A
  15. Stochastic Processes and Filtering Theory A. H. Jazwinski
  16. Second Edition Introduction to Random singals and Applied Kalman Filtering Robert G. Brown;Patrick Y. C. whang
  17. Lessons in Estimation Theory for Signal Processing, Communication, and Control Jerry M. Mendel