한국산학기술학회논문지 (Journal of the Korea Academia-Industrial cooperation Society)

  • 제16권1호
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  • Pages.860-867
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  • 2015
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  • 1975-4701(pISSN)
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  • 2288-4688(eISSN)
한국산학기술학회 (The Korea Academia-Industrial cooperation Society)
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PSO를 이용한 물 재이용 펌프시스템의 에너지 비용 제어

Energy Cost Saving Control of Water Reuse Pumping System Using Particle Swarm Optimization

  • 부창진 (제주국제대학교 전기에너지공학과) ;
  • 김호찬 (제주대학교 전기공학과) ;
  • 강민제 (제주대학교 전기공학과)
  • Boo, Chang-Jin (Department of Electrical Energy Eng., Jeju International University) ;
  • Kim, Ho-Chan (Department of Electrical Engineering, Jeju National University) ;
  • Kang, Min-Jae (Department of Electrical Engineering, Jeju National University)
  • 투고 : 2014.12.15
  • 심사 : 2015.01.08
  • 발행 : 2015.01.31
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초록

본 논문은 PSO 알고리즘을 이용하여 물 재이용 펌프 시스템의 에너지비용을 최소화 할 수 있는 방법을 제안한다. 1시간 단위의 시간대에서 펌프제어를 위해 계시별 요금제를 기반으로 하여 최적화 구간을 설정하고 PSO알고리즘을 이용하여 에너지 비용을 절감할 수 있도록 펌프동작을 제어한다. 물 재이용 펌프시스템에서 고정된 유량을 출력하는 펌프와 입력전력을 가변할 수 있는 펌프에 대해 TOU 기반에서 에너지 비용을 최대로 줄일 수 있도록 시스템을 동작시킨다. 시뮬레이션을 통해 제안한 에너지 비용 절감 방법이 기존 수위기반의 제어방법보다 비용을 절감할 수 있음을 확인할 수 있다.

This paper presents a control method for energy cost saving in the water reuse pumping system. An optimize horizon switching strategy is proposed to implement an pump control. And Particle Swarm Optimization (PSO) algorithm is used to solve optimal problems in each time step. Energy costs are calculated for electricity on both TOU in the light, heavy, and maximum load time period and peak charges. The control method in water reuse pumping systems is determined to reduce the TOU cost. The simulation results show a energy cost saving for water reuse pumping systems.

키워드

참고문헌

  1. Yong Tae Kang, Jeong Hyun Kim, "Configuration of the Optimum System for the Reuse of Wastewater", Korean Society of Water Science and Technology, Vol. 3, No. 1, pp. 3-14, 1995.
  2. K. W. Little and B. J. McCrodden. "Minimization of raw water pumping costs using milp", Journal of Water Resources Planning and Management, Vol. 115, No. 4, pp. 511-522, 1989. DOI:http://dx.doi.org/10.1061/(ASCE)0733-9496(1989) 115:4(511)
  3. C. Gopal, M. Mohanraj, P. Chandramohan, P. Chandrasekar, "Renewable energy source water pumping systems- A literature review", Renewable and Sustainable Energy Reviews, Vol. 25, pp. 351-370, 2012. DOI: http://dx.doi.org/10.1016/j.rser.2013.04.012
  4. Mahdi Moradi-Jalal and Bryan W. Karney., "Optimal design and operation of irrigation pumping stations using mathematical programming and genetic algorithm (GA)", Journal of Hydraulic Research, Vol. 46, No. 2, pp. 237- 246, 2008. DOI: http://dx.doi.org/10.1080/00221686.2008.9521858
  5. Van Zyl, J.E., Savic, D.A., Walters, G.A., "Operational optimization of water distribution systems using a hybrid genetic algorithm", Journal of Water Resources Planning and Management, pp. 160-170, 2004. DOI:http://dx.doi.org/10.1061/(ASCE)0733-9496(2004) 130:2(160)
  6. G. McCormick and R.S. Powell, "Derivation of near-optimal pump schedules for water distribution by simulated annealing", Journal of the Operational Research Society, Vol. 55, No. 7, pp. 728-736, 2004. DOI: http://dx.doi.org/10.1057/palgrave.jors.2601718
  7. M .H .Afshar, R. Rajabpour. "Optimal design and operation of irrigation pumping systems using particle swarm optimization algorithm", International Journal of Civil Engineerng, Vol. 5, No. 4, pp. 302-311, 2007.
  8. Chang Jin Boo and Ho Chan Kim, "Optimal Operation Control for Energy Saving in Water Reuse Pumping System", Journal of the Korea Academia-Industrial cooperation Society, Vol. 13, No. 5 pp. 2414-2419, 2012 DOI: http://dx.doi.org/10.5762/KAIS.2012.13.5.2414
  9. Eberhart R and Kennedy J., "A New Optimizer Using Particles Swarm Theory", Proc. Sixth International Symposium on Micro Machine and Human Science (Nagoya, Japan) IEEE Service Center, Piscataway, pp. 39-43, 1995. DOI: http://dx.doi.org/10.1109/MHS.1995.494215
  10. X. Meng, H. Wang, "Application of hybrid genetic algorithm in frequency speed control pumping station", in 4th international Conference on Natural computation, Shan Dong, China, pp. 337-341, 2008. DOI: http://dx.doi.org/10.1109/ICNC.2008.195