IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i6p1503-d151500.html
   My bibliography  Save this article

An Optimization Method for Local Consumption of Photovoltaic Power in a Facility Agriculture Micro Energy Network

Author

Listed:
  • Yuzhu Wang

    (College of Information and Electrical Engineering China Agricultural University, Beijing 100083, China)

  • Huanna Niu

    (College of Information and Electrical Engineering China Agricultural University, Beijing 100083, China)

  • Lu Yang

    (College of Information and Electrical Engineering China Agricultural University, Beijing 100083, China)

  • Weizhou Wang

    (State Grid Gansu Electric Power Research Institute, Lanzhou 730000, China)

  • Fuchao Liu

    (State Grid Gansu Electric Power Research Institute, Lanzhou 730000, China)

Abstract

In order to solve the problem of optimal dispatching of photovoltaic power for local consumption to the greatest degree in a photovoltaic greenhouse, this paper proposes a multiform energy optimal dispatching model and a solution algorithm. First, an input-output power model is established for energy storages which are reservoir, biogas digester, and block wall with phase-change thermal storage. Based on it, multiform energy storages play a bridging role of energy transfer in optimal energy dispatching. Subsequently, an optimal energy dispatching model is proposed with the objective of minimizing the sum of the squares of the difference between the loads and the photovoltaic generation in dispatching periods. Control variables are working state quantities of the time-shiftable loads and input-output state quantities of energy storages in dispatching periods. Finally, a genetic algorithm with matrix binary coding is used to solve the energy optimal dispatching model. Simulation results of a practical photovoltaic greenhouse facility agricultural micro energy network system in three typical weather conditions showed that the method could fully utilize the energy transfer function of the multiform energy storage and the time-shiftable characteristics of the agricultural load to achieve the maximum effect of increasing the local consumption of the photovoltaic power.

Suggested Citation

  • Yuzhu Wang & Huanna Niu & Lu Yang & Weizhou Wang & Fuchao Liu, 2018. "An Optimization Method for Local Consumption of Photovoltaic Power in a Facility Agriculture Micro Energy Network," Energies, MDPI, vol. 11(6), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1503-:d:151500
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/6/1503/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/6/1503/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peacock, A.D. & Newborough, M., 2006. "Impact of micro-combined heat-and-power systems on energy flows in the UK electricity supply industry," Energy, Elsevier, vol. 31(12), pages 1804-1818.
    2. Cho, Heejin & Smith, Amanda D. & Mago, Pedro, 2014. "Combined cooling, heating and power: A review of performance improvement and optimization," Applied Energy, Elsevier, vol. 136(C), pages 168-185.
    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. Ji, Zhengsen & Li, Wanying & Niu, Dongxiao, 2024. "Optimal investment decision of agrivoltaic coupling energy storage project based on distributed linguistic trust and hybrid evaluation method," Applied Energy, Elsevier, vol. 353(PA).
    2. Xiayun Duan & Yifeng Ding & Huanna Niu & Yuzhu Wang, 2019. "Analysis of the Day-ahead Deviation Plan and Research on the Real-time Scheduling of Photovoltaic Greenhouses Based on Exergy Theory," Energies, MDPI, vol. 12(20), pages 1-21, October.
    3. Yan Ren & Linmao Ren & Kai Zhang & Dong Liu & Xianhe Yao & Huawei Li, 2022. "Research on the Operational Strategy of the Hybrid Wind/PV/Small-Hydropower/Facility-Agriculture System Based on a Microgrid," Energies, MDPI, vol. 15(7), pages 1-15, March.
    4. Xin Zhang & Jianhua Yang & Weizhou Wang & Man Zhang & Tianjun Jing, 2018. "Integrated Optimal Dispatch of a Rural Micro-Energy-Grid with Multi-Energy Stream Based on Model Predictive Control," Energies, MDPI, vol. 11(12), pages 1-23, December.

    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. Li, Wenjia & Hao, Yong & Wang, Hongsheng & Liu, Hao & Sui, Jun, 2017. "Efficient and low-carbon heat and power cogeneration with photovoltaics and thermochemical storage," Applied Energy, Elsevier, vol. 206(C), pages 1523-1531.
    2. Zhao, Qin & Zhang, Houcheng & Hu, Ziyang & Hou, Shujin, 2021. "Performance evaluation of a new hybrid system consisting of a photovoltaic module and an absorption heat transformer for electricity production and heat upgrading," Energy, Elsevier, vol. 216(C).
    3. Nolan, Sheila & Neu, Olivier & O’Malley, Mark, 2017. "Capacity value estimation of a load-shifting resource using a coupled building and power system model," Applied Energy, Elsevier, vol. 192(C), pages 71-82.
    4. Chang, Huawei & Wan, Zhongmin & Zheng, Yao & Chen, Xi & Shu, Shuiming & Tu, Zhengkai & Chan, Siew Hwa & Chen, Rui & Wang, Xiaodong, 2017. "Energy- and exergy-based working fluid selection and performance analysis of a high-temperature PEMFC-based micro combined cooling heating and power system," Applied Energy, Elsevier, vol. 204(C), pages 446-458.
    5. Dong, Hye-Won & Jeong, Jae-Weon, 2020. "Energy benefits of organic Rankine cycle in a liquid desiccant and evaporative cooling-assisted air conditioning system," Renewable Energy, Elsevier, vol. 147(P1), pages 2358-2373.
    6. Díaz, Guzmán & Planas, Estefanía & Andreu, Jon & Kortabarria, Iñigo, 2015. "Joint cost of energy under an optimal economic policy of hybrid power systems subject to uncertainty," Energy, Elsevier, vol. 88(C), pages 837-848.
    7. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Nor, Khalil M.D. & Khoshnoudi, Masoumeh, 2016. "Using fuzzy multiple criteria decision making approaches for evaluating energy saving technologies and solutions in five star hotels: A new hierarchical framework," Energy, Elsevier, vol. 117(P1), pages 131-148.
    8. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    9. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    10. Zhang, Na & Wang, Zefeng & Lior, Noam & Han, Wei, 2018. "Advancement of distributed energy methods by a novel high efficiency solar-assisted combined cooling, heating and power system," Applied Energy, Elsevier, vol. 219(C), pages 179-186.
    11. Su, Bosheng & Han, Wei & Jin, Hongguang, 2017. "Proposal and assessment of a novel integrated CCHP system with biogas steam reforming using solar energy," Applied Energy, Elsevier, vol. 206(C), pages 1-11.
    12. Vaclav Novotny & David J. Szucs & Jan Špale & Hung-Yin Tsai & Michal Kolovratnik, 2021. "Absorption Power and Cooling Combined Cycle with an Aqueous Salt Solution as a Working Fluid and a Technically Feasible Configuration," Energies, MDPI, vol. 14(12), pages 1-26, June.
    13. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
    14. Chen, Xi & Wang, Chengfu & Wu, Qiuwei & Dong, Xiaoming & Yang, Ming & He, Suoying & Liang, Jun, 2020. "Optimal operation of integrated energy system considering dynamic heat-gas characteristics and uncertain wind power," Energy, Elsevier, vol. 198(C).
    15. Fan Li & Jingxi Su & Bo Sun, 2023. "An Optimal Scheduling Method for an Integrated Energy System Based on an Improved k-Means Clustering Algorithm," Energies, MDPI, vol. 16(9), pages 1-22, April.
    16. Zhang, Jingxin & Hu, Qiang & Qu, Yiyuan & Dai, Yanjun & He, Yiliang & Wang, Chi-Hwa & Tong, Yen Wah, 2020. "Integrating food waste sorting system with anaerobic digestion and gasification for hydrogen and methane co-production," Applied Energy, Elsevier, vol. 257(C).
    17. Fong, K.F. & Lee, C.K., 2019. "Performance investigation of a SOFC-primed micro-combined hybrid cooling and power system in hot and humid regions," Energy, Elsevier, vol. 189(C).
    18. Lombardi, K. & Ugursal, V.I. & Beausoleil-Morrison, I., 2010. "Proposed improvements to a model for characterizing the electrical and thermal energy performance of Stirling engine micro-cogeneration devices based upon experimental observations," Applied Energy, Elsevier, vol. 87(10), pages 3271-3282, October.
    19. Shariat Torbaghan, Shahab & Madani, Mehdi & Sels, Peter & Virag, Ana & Le Cadre, Hélène & Kessels, Kris & Mou, Yuting, 2021. "Designing day-ahead multi-carrier markets for flexibility: Models and clearing algorithms," Applied Energy, Elsevier, vol. 285(C).
    20. Bataineh, Khaled, 2024. "Hybrid fuel-assisted solar-powered stirling engine for combined cooling, heating, and power systems: A review," Energy, Elsevier, vol. 300(C).

    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:gam:jeners:v:11:y:2018:i:6:p:1503-:d:151500. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.