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| تعداد شماره‌ها | 610 |
| تعداد مقالات | 9,029 |
| تعداد مشاهده مقاله | 67,082,973 |
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ارائه مدل بهینه‌سازی برای کاهش هزینه‌های پمپاژ در سیستم‌های توزیع آب | ||
| مدل سازی در مهندسی | ||
| دوره 22، شماره 79، دی 1403، صفحه 255-265 اصل مقاله (746.99 K) | ||
| نوع مقاله: مقاله عمران | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2024.33389.2630 | ||
| نویسنده | ||
| عباسعلی رضاپور* | ||
| گروه مهندسی عمران، دانشگاه صنعتی بیرجند، بیرجند، ایران | ||
| تاریخ دریافت: 08 اسفند 1402، تاریخ بازنگری: 01 اردیبهشت 1403، تاریخ پذیرش: 04 اردیبهشت 1403 | ||
| چکیده | ||
| سیستم‌های توزیع آب ساختار پیچیده‌ای دارند که شامل برنامه‌ریزی پمپها، تنظیم سطوح آب در مخازن و تحویل آب با جریان و فشار مناسب به مشتریان می‌شود. برنامه‌ریزی برای پمپها از جمله وظایف اصلی عملکرد سیستم توزیع آب است که اثر مهمی بر هزینه‌های عملیاتی دارد. در این پژوهش، یک مدل بهینه‌سازی برای برنامه‌ریزی زمان کار پمپها با هدف کاهش مصرف انرژی معرفی می‌گردد. این مدل قابلیت محدودسازی تعداد دفعات روشن و خاموش‌شدن پمپها را دارد و زمان کار پمپها را به عنوان متغیرهای گسسته (متغیرهای دودویی) و مقدار جریان در هر لوله را به عنوان متغیر پیوسته در دوره برنامه‌ریزی بکار می گیرد. برای دستیابی به این مدل، ابتدا مسئله به عنوان یک مسئله برنامه‌ریزی غیرخطی آمیخته مدل‌سازی شد، سپس با استفاده از تکنیک‌های خطی‌سازی به یک مدل بهینه‌سازی خطی آمیخته تبدیل گردید. عملکرد مدل پیشنهادی با استفاده از یک مثال کاربردی مورد ارزیابی قرار گرفت. بررسی نتایج نشان می‌دهد که استفاده از روش بهینه‌سازی پیشنهادی منجر به کاهش هزینه‌های انرژی در حدود ۱۶ درصد و افزایش کارایی سیستم توزیع آب می‌گردد. | ||
| کلیدواژه‌ها | ||
| سیستم توزیع آب؛ کاهش هزینه پمپاژ؛ مدل بهینه‌سازی؛ مدل‌های خطی آمیخته؛ مخازن آب | ||
| عنوان مقاله [English] | ||
| An Optimization Model for Reducing Pumping Costs in Water Distribution Systems | ||
| نویسندگان [English] | ||
| Abbasali Rezapour | ||
| Department of Civil Engineering, Birjand Univerdity of Technology, Birjand, Iran | ||
| چکیده [English] | ||
| The architecture of water distribution networks is inherently intricate, encompassing the strategic management of pumping mechanisms, modulation of reservoir water levels, and ensuring the delivery of water to consumers with adequate flow and pressure. A pivotal element of operating these systems is the strategic planning of pump schedules, which exerts a considerable influence on the operational expenditures. The present study introduces an optimization framework designed to schedule pump operations with the objective of minimizing energy consumption. This framework is equipped with the capability to regulate the frequency of pump activation and deactivation cycles, employing the operational durations of the pumps as binary variables and the volumetric flow rates within each conduit as continuous variables throughout the scheduling horizon. The development of this framework commenced with the formulation of the issue as a mixed nonlinear programming problem, which subsequently underwent transformation into a mixed linear programming model through the application of linearization methodologies. An empirical case study was conducted to assess the efficacy of the proposed model. The examination of the results indicates that the use of the proposed optimization method leads to a reduction in energy costs by approximately 16 percent and an increase in the efficiency of the water distribution system. | ||
| کلیدواژه‌ها [English] | ||
| Water distribution system, Pumping cost reduction, Optimization model, Mixed linear models, Water tanks | ||
| مراجع | ||
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[1] Gh. Fallahi, and M. Salehzadeh. " Pressure Management in Water Distribution Networks using Geographic Information System and Spatial Open Source Database (Case Study: Golestan Town of Shiraz)." Journal of Water and Sustainable Development 4, no. 2 (2018): 151-158. (in Persian) [2] M. Herman, M. Romi Syahputra, S. Sutarman, and G.W. Weber. "Water Distribution Network Optimization Model with Reliability Considerations in Water Flow (Debit)." Water 15, no. 17 (2023): 3119. [3] O. Ormbsee, and L. Lansey. "Optimal control of water supply pumping systems." Journal of Water Resources Planning and Management 120, no. 2 (1994): 237–252. [4] U. Zessler, and U. Shamir. "Optimal operation of water distribution systems." Journal of Water Resources Planning and Management 115, no. 6 (1989): 735–752. [5] M.F.K. Pasha, and K. Lansey. "Optimal pump scheduling by linear programming." In Proceedings of World Environmental and Water Resources Congress. Kanzas city. (2009): 395–404. [6] A. Savic, D. Walters, A. Godfrey, and M. Schwab. "Multiobjective genetic algorithms for pump scheduling in water supply." In Evolutionary Computing, AISB. (1997): 1–10. [7] G.C. Dandy. A.R. Simpson. and L.J. Murphy. "An improved genetic algorithm for pipe network optimization." Water Resources Research 32, no. 2 (1996): 449–458. [8] V. Kelner, and O. Léonard. "Optimal pump scheduling for water supply using genetic algorithms." In 5th International Conference on Evolutionary Computing for Industrial Applications (EUROGEN’03). 2003. [9] C. Biscos, M. Mulholland, M.V. Le Lann, C.A. Buckley, and C.J. Brouckaert. "Optimal operation of water distribution networks by predictive control using MINLP." Water Sa 29, no. 4 (2003): 393–404. [10] M. Van Dijk, S.J. van Vuuren, and J.E. Zyl. "Optimising water distribution systems using a weighted penalty in a genetic algorithm." Water Sa 34, no. 5 (2008): 537–548. [11] M. Lopez-Ibanez, T. Devi Prasad, and B. Paechter. "Ant colony optimization for optimal control of pumps in water distribution networks." Journal of Water Resources, Planning and Management, ASCE 134, no. 5 (2008): 337–346. [12] V. Nitivattananon, E.C. Sadowski, and R.G. Quimpo. "Optimization of water supply system operation." Journal of Water Resources, Planning and Management, ASCE 122, no. 5 (1996): 374–384. [13] S. Pezeshk, and O.J. Helweg. "Adaptive search optimization in reducing pump operating costs." Journal of Water Resources, Planning and Management, ASCE 122, no. 1 (1996): 57–63. [14] M. Zarei, et al. "Optimizing the performance of water supply networks using genetic algorithm." Irrigation and Development Engineering, no. 1 (2006). (in Persian) [15] R. Yusefi, et al. "Optimization of urban water distribution system using harmonic search algorithm." Water Resources Engineering, no. 3 (2020). (in Persian) [16] M.M. Shahbazi, et al. "Optimization of urban water distribution system using genetic algorithm." Scientific-Research Journal of Urban-Spatial Civil Engineering, no. 2 (2014). (in Persian) [17] S. Parvaze, R. Kumar, J.N. Khan, N. Al-Ansari, S. Parvaze, D.K. Vishwakarma, and A. Kuriqi. "Optimization of water distribution systems using genetic algorithms: A review." Archives of Computational Methods in Engineering 30, no. 7 (2023): 4209-4244. [18] S.J. Musavi, et al. "Optimization of water distribution system using ant algorithm." Bimonthly Water and Wastewater Journal, no. 23 (2016). (in Persian) [19] S. Hajiha, et al. "Optimization of water distribution in water supply network using magnetic particle flow algorithm." Journal of Water and Sewage, no. 34 (2018). (in Persian) [20] H. Moeinfar, and J. Yazdi. "Optimization of energy consumption in water distribution networks using variable speed pumps." Iranian Hydraulic Association Journal of Hydraulics 18, no. 3 (2023): 45-61. (in Persian) [21] S. Daulat, M.M. Rokstad, A. Klein-Paste, J. Langeveld, and F. Tscheikner-Gratl. "Challenges of integrated multi-infrastructure asset management: a review of pavement, sewer, and water distribution networks." Structure and Infrastructure Engineering 20, no. 4 (2024): 546-565. [22] T. Yu, X. Chen, W. Yan, Z. Xu, and M. Ye. "Leak detection in water distribution systems by classifying vibration signals." Mechanical Systems and Signal Processing, 185 (2023): 109810. [23] A.M. Farouk, R.A. Rahman, and N.S. Romali. "Economic analysis of rehabilitation approaches for water distribution networks: Comparative study between Egypt and Malaysia." Journal of Engineering, Design and Technology 21, no. 1 (2023): 130-149. | ||
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