IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v160y2015icp521-531.html
   My bibliography  Save this article

Energy-water optimization model incorporating rooftop water harvesting for lawn irrigation

Author

Listed:
  • Wanjiru, Evan M.
  • Xia, Xiaohua

Abstract

The management of energy and water is increasingly gaining attention among domestic end-users. In developing countries, potable water supply is unreliable leading to alternative strategies such as rooftop water harvesting (RWH), storage and pumping. Since urban garden irrigation is the highest outdoor water consumer, optimal scheduling is important to conserve energy and water over conventional lawn irrigation methods. A model to optimally control the lawn irrigation was developed with the simulation results showing 17.4% potential water savings when using water directly from municipal sources. With RWH of a 1-h event with 1-mm rainfall from a 120-m2 roof, the model can potentially save 23.4% of water and 73.8% in energy costs per day. Such savings are important in reducing the demand for existing water and energy sources as well as greenhouse emissions. Further, this paper looks into two strategies to maximize the pump’s life through minimizing the maintenance cost.

Suggested Citation

  • Wanjiru, Evan M. & Xia, Xiaohua, 2015. "Energy-water optimization model incorporating rooftop water harvesting for lawn irrigation," Applied Energy, Elsevier, vol. 160(C), pages 521-531.
    • Handle: RePEc:eee:appene:v:160:y:2015:i:c:p:521-531
    DOI: 10.1016/j.apenergy.2015.09.083
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915011927
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.09.083?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Plappally, A.K. & Lienhard V, J.H., 2012. "Energy requirements for water production, treatment, end use, reclamation, and disposal," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4818-4848.
    2. Davis, S.L. & Dukes, M.D., 2010. "Irrigation scheduling performance by evapotranspiration-based controllers," Agricultural Water Management, Elsevier, vol. 98(1), pages 19-28, December.
    3. McCready, M.S. & Dukes, M.D., 2011. "Landscape irrigation scheduling efficiency and adequacy by various control technologies," Agricultural Water Management, Elsevier, vol. 98(4), pages 697-704, February.
    4. Reca, Juan & García-Manzano, Alfonso & Martínez, Juan, 2015. "Optimal pumping scheduling model considering reservoir evaporation," Agricultural Water Management, Elsevier, vol. 148(C), pages 250-257.
    5. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    6. Hafeez, Mohsin & Bundschuh, Jochen & Mushtaq, Shahbaz, 2014. "Exploring synergies and tradeoffs: Energy, water, and economic implications of water reuse in rice-based irrigation systems," Applied Energy, Elsevier, vol. 114(C), pages 889-900.
    7. Numbi, B.P. & Xia, X., 2015. "Systems optimization model for energy management of a parallel HPGR crushing process," Applied Energy, Elsevier, vol. 149(C), pages 133-147.
    8. Blonquist, J.M. Jr. & Jones, S.B. & Robinson, D.A., 2006. "Precise irrigation scheduling for turfgrass using a subsurface electromagnetic soil moisture sensor," Agricultural Water Management, Elsevier, vol. 84(1-2), pages 153-165, July.
    9. Dubreuil, Aurelie & Assoumou, Edi & Bouckaert, Stephanie & Selosse, Sandrine & Maı¨zi, Nadia, 2013. "Water modeling in an energy optimization framework – The water-scarce middle east context," Applied Energy, Elsevier, vol. 101(C), pages 268-279.
    10. van Staden, Adam Jacobus & Zhang, Jiangfeng & Xia, Xiaohua, 2011. "A model predictive control strategy for load shifting in a water pumping scheme with maximum demand charges," Applied Energy, Elsevier, vol. 88(12), pages 4785-4794.
    11. Chatterjee, Arnab & Zhang, Lijun & Xia, Xiaohua, 2015. "Optimization of mine ventilation fan speeds according to ventilation on demand and time of use tariff," Applied Energy, Elsevier, vol. 146(C), pages 65-73.
    12. Zhang, Shirong & Xia, Xiaohua, 2010. "Optimal control of operation efficiency of belt conveyor systems," Applied Energy, Elsevier, vol. 87(6), pages 1929-1937, June.
    13. Zhuan, Xiangtao & Xia, Xiaohua, 2013. "Optimal operation scheduling of a pumping station with multiple pumps," Applied Energy, Elsevier, vol. 104(C), pages 250-257.
    14. Davis, S.L. & Dukes, M.D. & Miller, G.L., 2009. "Landscape irrigation by evapotranspiration-based irrigation controllers under dry conditions in Southwest Florida," Agricultural Water Management, Elsevier, vol. 96(12), pages 1828-1836, December.
    15. Numbi, B.P. & Zhang, J. & Xia, X., 2014. "Optimal energy management for a jaw crushing process in deep mines," Energy, Elsevier, vol. 68(C), pages 337-348.
    16. Chiu, Yie-Ru & Liaw, Chao-Hsien & Chen, Liang-Ching, 2009. "Optimizing rainwater harvesting systems as an innovative approach to saving energy in hilly communities," Renewable Energy, Elsevier, vol. 34(3), pages 492-498.
    17. Zhang, Lijun & Xia, Xiaohua & Zhang, Jiangfeng, 2014. "Improving energy efficiency of cyclone circuits in coal beneficiation plants by pump-storage systems," Applied Energy, Elsevier, vol. 119(C), pages 306-313.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xiaodong & Vesselinov, Velimir V., 2016. "Energy-water nexus: Balancing the tradeoffs between two-level decision makers," Applied Energy, Elsevier, vol. 183(C), pages 77-87.
    2. Wanjiru, Evan M. & Zhang, Lijun & Xia, Xiaohua, 2016. "Model predictive control strategy of energy-water management in urban households," Applied Energy, Elsevier, vol. 179(C), pages 821-831.
    3. Wanjiru, Evan M. & Sichilalu, Sam M. & Xia, Xiaohua, 2017. "Model predictive control of heat pump water heater-instantaneous shower powered with integrated renewable-grid energy systems," Applied Energy, Elsevier, vol. 204(C), pages 1333-1346.
    4. Mei, Jun & Xia, Xiaohua, 2017. "Energy-efficient predictive control of indoor thermal comfort and air quality in a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 195(C), pages 439-452.
    5. Charles Kagiri & Lijun Zhang & Xiaohua Xia, 2019. "A Hierarchical Optimisation of a Compressed Natural Gas Station for Energy and Fuelling Efficiency under a Demand Response Program," Energies, MDPI, vol. 12(11), pages 1-24, June.
    6. Wanjiru, Evan M. & Sichilalu, Sam M. & Xia, Xiaohua, 2017. "Optimal control of heat pump water heater-instantaneous shower using integrated renewable-grid energy systems," Applied Energy, Elsevier, vol. 201(C), pages 332-342.
    7. Arun Shankar, Vishnu Kalaiselvan & Umashankar, Subramaniam & Paramasivam, Shanmugam & Hanigovszki, Norbert, 2016. "A comprehensive review on energy efficiency enhancement initiatives in centrifugal pumping system," Applied Energy, Elsevier, vol. 181(C), pages 495-513.
    8. Kagiri, Charles & Wanjiru, Evan M. & Zhang, Lijun & Xia, Xiaohua, 2018. "Optimized response to electricity time-of-use tariff of a compressed natural gas fuelling station," Applied Energy, Elsevier, vol. 222(C), pages 244-256.
    9. Sui, Quan & Wei, Fanrong & Zhang, Rui & Lin, Xiangning & Tong, Ning & Wang, Zhixun & Li, Zhengtian, 2019. "Optimal use of electric energy oriented water-electricity combined supply system for the building-integrated-photovoltaics community," Applied Energy, Elsevier, vol. 247(C), pages 549-558.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kagiri, Charles & Wanjiru, Evan M. & Zhang, Lijun & Xia, Xiaohua, 2018. "Optimized response to electricity time-of-use tariff of a compressed natural gas fuelling station," Applied Energy, Elsevier, vol. 222(C), pages 244-256.
    2. Zhang, Lijun & Chennells, Michael & Xia, Xiaohua, 2018. "A power dispatch model for a ferrochrome plant heat recovery cogeneration system," Applied Energy, Elsevier, vol. 227(C), pages 180-189.
    3. Muller, C.J. & Craig, I.K., 2016. "Energy reduction for a dual circuit cooling water system using advanced regulatory control," Applied Energy, Elsevier, vol. 171(C), pages 287-295.
    4. Numbi, B.P. & Xia, X., 2015. "Systems optimization model for energy management of a parallel HPGR crushing process," Applied Energy, Elsevier, vol. 149(C), pages 133-147.
    5. Numbi, B.P. & Xia, X., 2016. "Optimal energy control of a crushing process based on vertical shaft impactor," Applied Energy, Elsevier, vol. 162(C), pages 1653-1661.
    6. Wanjiru, Evan M. & Zhang, Lijun & Xia, Xiaohua, 2016. "Model predictive control strategy of energy-water management in urban households," Applied Energy, Elsevier, vol. 179(C), pages 821-831.
    7. Numbi, B.P. & Malinga, S.J., 2017. "Optimal energy cost and economic analysis of a residential grid-interactive solar PV system- case of eThekwini municipality in South Africa," Applied Energy, Elsevier, vol. 186(P1), pages 28-45.
    8. Wanjiru, Evan M. & Sichilalu, Sam M. & Xia, Xiaohua, 2017. "Model predictive control of heat pump water heater-instantaneous shower powered with integrated renewable-grid energy systems," Applied Energy, Elsevier, vol. 204(C), pages 1333-1346.
    9. Snyder, R.L. & Pedras, C. & Montazar, A. & Henry, J.M. & Ackley, D., 2015. "Advances in ET-based landscape irrigation management," Agricultural Water Management, Elsevier, vol. 147(C), pages 187-197.
    10. Vieira, Abel S. & Beal, Cara D. & Ghisi, Enedir & Stewart, Rodney A., 2014. "Energy intensity of rainwater harvesting systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 225-242.
    11. Numbi, B.P. & Zhang, J. & Xia, X., 2014. "Optimal energy management for a jaw crushing process in deep mines," Energy, Elsevier, vol. 68(C), pages 337-348.
    12. Marjan Aziz & Madeeha Khan & Naveeda Anjum & Muhammad Sultan & Redmond R. Shamshiri & Sobhy M. Ibrahim & Siva K. Balasundram & Muhammad Aleem, 2022. "Scientific Irrigation Scheduling for Sustainable Production in Olive Groves," Agriculture, MDPI, vol. 12(4), pages 1-14, April.
    13. Filipe, Jorge & Bessa, Ricardo J. & Reis, Marisa & Alves, Rita & Póvoa, Pedro, 2019. "Data-driven predictive energy optimization in a wastewater pumping station," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    14. Du Plessis, Gideon Edgar & Liebenberg, Leon & Mathews, Edward Henry, 2013. "The use of variable speed drives for cost-effective energy savings in South African mine cooling systems," Applied Energy, Elsevier, vol. 111(C), pages 16-27.
    15. Witold Kawalec & Robert Król & Natalia Suchorab, 2020. "Regenerative Belt Conveyor versus Haul Truck-Based Transport: Polish Open-Pit Mines Facing Sustainable Development Challenges," Sustainability, MDPI, vol. 12(21), pages 1-15, November.
    16. Fang, Delin & Chen, Bin, 2017. "Linkage analysis for the water–energy nexus of city," Applied Energy, Elsevier, vol. 189(C), pages 770-779.
    17. Shang, Yizi & Hei, Pengfei & Lu, Shibao & Shang, Ling & Li, Xiaofei & Wei, Yongping & Jia, Dongdong & Jiang, Dong & Ye, Yuntao & Gong, Jiaguo & Lei, Xiaohui & Hao, Mengmeng & Qiu, Yaqin & Liu, Jiahong, 2018. "China’s energy-water nexus: Assessing water conservation synergies of the total coal consumption cap strategy until 2050," Applied Energy, Elsevier, vol. 210(C), pages 643-660.
    18. Sara Komenda & Martha C. Monroe, 2023. "Clues in the Data: The Role of Education in Adopting Technology That Enhances Sustainable Lifestyle Choices," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    19. Gu, Alun & Teng, Fei & Lv, Zhiqiang, 2016. "Exploring the nexus between water saving and energy conservation: Insights from industry sector during the 12th Five-Year Plan period in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 28-38.
    20. Smith, Kate & Liu, Shuming & Liu, Ying & Guo, Shengjie, 2018. "Can China reduce energy for water? A review of energy for urban water supply and wastewater treatment and suggestions for change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 41-58.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:160:y:2015:i:c:p:521-531. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.