IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v205y2020ics0360544220311336.html
   My bibliography  Save this article

Adaptive time division power dispatch based on numerical characteristics of net loads

Author

Listed:
  • Hu, Shu-bo
  • Gao, Zheng-nan
  • He, Hai
  • Cao, Wen-ping
  • Zhao, Yu-ting
  • Zhou, Wei
  • Gu, Hong
  • Sun, Hui

Abstract

Energy sustainable development is of strategic importance across the world. This is especially the case in China as it is the world’s largest energy consumer. However, renewable energies such as wind and solar energy are characterized with high intermittence and fluctuation. As the penetration of renewable power in the energy system increases, it is getting more challenging in power dispatch. In this paper, an adaptive time division power dispatch strategy based on numerical characteristics of net loads is proposed. In this strategy, a dispatch time division method is introduced in detail to divide the dispatching time according to the numerical characteristics of net loads. The sample entropy theory is utilized to calculate the complexity of the net loads, depending on which a specific thermal generating mode is provided. The experiment simulation is developed on an actual provincial power system in the northeast of China. The test results have confirmed that in the adaptive time division power dispatch strategy, the ramping power of thermal generators are decreased, the continuous and steady operation time of thermal generators are improved. As a result, this new strategy, can lead to improved energy efficiency of power systems as well as significant environmental benefits.

Suggested Citation

  • Hu, Shu-bo & Gao, Zheng-nan & He, Hai & Cao, Wen-ping & Zhao, Yu-ting & Zhou, Wei & Gu, Hong & Sun, Hui, 2020. "Adaptive time division power dispatch based on numerical characteristics of net loads," Energy, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:energy:v:205:y:2020:i:c:s0360544220311336
    DOI: 10.1016/j.energy.2020.118026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220311336
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.118026?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. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    2. de Boer, Harmen Sytze & Grond, Lukas & Moll, Henk & Benders, René, 2014. "The application of power-to-gas, pumped hydro storage and compressed air energy storage in an electricity system at different wind power penetration levels," Energy, Elsevier, vol. 72(C), pages 360-370.
    3. Zhao, Pan & Wang, Jiangfeng & Dai, Yiping, 2015. "Capacity allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level," Renewable Energy, Elsevier, vol. 75(C), pages 541-549.
    4. Shubo Hu & Hui Sun & Feixiang Peng & Wei Zhou & Wenping Cao & Anlong Su & Xiaodong Chen & Mingze Sun, 2018. "Optimization Strategy for Economic Power Dispatch Utilizing Retired EV Batteries as Flexible Loads," Energies, MDPI, vol. 11(7), pages 1-21, June.
    5. Zhang, Ningning & Lin, Aijing & Ma, Hui & Shang, Pengjian & Yang, Pengbo, 2018. "Weighted multivariate composite multiscale sample entropy analysis for the complexity of nonlinear times series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 595-607.
    6. Shaker, Hamid & Zareipour, Hamidreza & Wood, David, 2016. "Impacts of large-scale wind and solar power integration on California׳s net electrical load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 761-774.
    7. Zhao, Pan & Wang, Mingkun & Wang, Jiangfeng & Dai, Yiping, 2015. "A preliminary dynamic behaviors analysis of a hybrid energy storage system based on adiabatic compressed air energy storage and flywheel energy storage system for wind power application," Energy, Elsevier, vol. 84(C), pages 825-839.
    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. Wang, Yuwei & Yang, Yuanjuan & Fei, Haoran & Song, Minghao & Jia, Mengyao, 2022. "Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    2. Jin, Xiaoyu & Liu, Benxi & Liao, Shengli & Cheng, Chuntian & Yan, Zhiyu, 2022. "A Wasserstein metric-based distributionally robust optimization approach for reliable-economic equilibrium operation of hydro-wind-solar energy systems," Renewable Energy, Elsevier, vol. 196(C), pages 204-219.
    3. Xu, Fang Yuan & Tang, Rui Xin & Xu, Si Bin & Fan, Yi Liang & Zhou, Ya & Zhang, Hao Tian, 2021. "Neural network-based photovoltaic generation capacity prediction system with benefit-oriented modification," Energy, Elsevier, vol. 223(C).
    4. Shubo Hu & Zhengnan Gao & Jing Wu & Yangyang Ge & Jiajue Li & Lianyong Zhang & Jinsong Liu & Hui Sun, 2022. "Time-Interval-Varying Optimal Power Dispatch Strategy Based on Net Load Time-Series Characteristics," Energies, MDPI, vol. 15(4), pages 1-23, February.
    5. Wang, Yajun & Wang, Jidong & Cao, Man & Kong, Xiangyu & Abderrahim, Bouchedjira & Yuan, Long & Vartosh, Aris, 2023. "Dynamic emission dispatch considering the probabilistic model with multiple smart energy system players based on a developed fuzzy theory-based harmony search algorithm," Energy, Elsevier, vol. 269(C).

    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. Saboori, Hedayat & Hemmati, Reza & Jirdehi, Mehdi Ahmadi, 2015. "Reliability improvement in radial electrical distribution network by optimal planning of energy storage systems," Energy, Elsevier, vol. 93(P2), pages 2299-2312.
    2. Fichter, Tobias & Soria, Rafael & Szklo, Alexandre & Schaeffer, Roberto & Lucena, Andre F.P., 2017. "Assessing the potential role of concentrated solar power (CSP) for the northeast power system of Brazil using a detailed power system model," Energy, Elsevier, vol. 121(C), pages 695-715.
    3. Guo, Cong & Xu, Yujie & Zhang, Xinjing & Guo, Huan & Zhou, Xuezhi & Liu, Chang & Qin, Wei & Li, Wen & Dou, Binlin & Chen, Haisheng, 2017. "Performance analysis of compressed air energy storage systems considering dynamic characteristics of compressed air storage," Energy, Elsevier, vol. 135(C), pages 876-888.
    4. Hasan, Nor Shahida & Hassan, Mohammad Yusri & Abdullah, Hayati & Rahman, Hasimah Abdul & Omar, Wan Zaidi Wan & Rosmin, Norzanah, 2016. "Improving power grid performance using parallel connected Compressed Air Energy Storage and wind turbine system," Renewable Energy, Elsevier, vol. 96(PA), pages 498-508.
    5. Abdul Ghani Olabi & Tabbi Wilberforce & Mohammad Ali Abdelkareem & Mohamad Ramadan, 2021. "Critical Review of Flywheel Energy Storage System," Energies, MDPI, vol. 14(8), pages 1-33, April.
    6. Xin Sui & Shengyang Lu & Hai He & Yuting Zhao & Shubo Hu & Ziqian Liu & Hong Gu & Hui Sun, 2020. "Wind-Thermal-Nuclear-Storage Combined Time Division Power Dispatch Based on Numerical Characteristics of Net Load," Energies, MDPI, vol. 13(2), pages 1-24, January.
    7. Tong, Zheming & Cheng, Zhewu & Tong, Shuiguang, 2021. "A review on the development of compressed air energy storage in China: Technical and economic challenges to commercialization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    8. Yang, Yiqing & Chen, Peihao & Liu, Qiang, 2021. "A wave energy harvester based on coaxial mechanical motion rectifier and variable inertia flywheel," Applied Energy, Elsevier, vol. 302(C).
    9. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.
    10. Theo, Wai Lip & Lim, Jeng Shiun & Wan Alwi, Sharifah Rafidah & Mohammad Rozali, Nor Erniza & Ho, Wai Shin & Abdul-Manan, Zainuddin, 2016. "An MILP model for cost-optimal planning of an on-grid hybrid power system for an eco-industrial park," Energy, Elsevier, vol. 116(P2), pages 1423-1441.
    11. Jidai Wang & Kunpeng Lu & Lan Ma & Jihong Wang & Mark Dooner & Shihong Miao & Jian Li & Dan Wang, 2017. "Overview of Compressed Air Energy Storage and Technology Development," Energies, MDPI, vol. 10(7), pages 1-22, July.
    12. Soria, Rafael & Lucena, André F.P. & Tomaschek, Jan & Fichter, Tobias & Haasz, Thomas & Szklo, Alexandre & Schaeffer, Roberto & Rochedo, Pedro & Fahl, Ulrich & Kern, Jürgen, 2016. "Modelling concentrated solar power (CSP) in the Brazilian energy system: A soft-linked model coupling approach," Energy, Elsevier, vol. 116(P1), pages 265-280.
    13. Zhao, Pan & Wang, Peizi & Xu, Wenpan & Zhang, Shiqiang & Wang, Jiangfeng & Dai, Yiping, 2021. "The survey of the combined heat and compressed air energy storage (CH-CAES) system with dual power levels turbomachinery configuration for wind power peak shaving based spectral analysis," Energy, Elsevier, vol. 215(PB).
    14. Zhang, Yi & Xu, Yujie & Guo, Huan & Zhang, Xinjing & Guo, Cong & Chen, Haisheng, 2018. "A hybrid energy storage system with optimized operating strategy for mitigating wind power fluctuations," Renewable Energy, Elsevier, vol. 125(C), pages 121-132.
    15. Shubo Hu & Feixiang Peng & Zhengnan Gao & Changqiang Ding & Hui Sun & Wei Zhou, 2019. "Sample Entropy Based Net Load Tracing Dispatch of New Energy Power System," Energies, MDPI, vol. 12(1), pages 1-23, January.
    16. Koh, Siong Lee & Lim, Yun Seng, 2016. "Methodology for assessing viability of energy storage system for buildings," Energy, Elsevier, vol. 101(C), pages 519-531.
    17. Ruixiong Li & Huanran Wang & Erren Yao & Shuyu Zhang, 2016. "Thermo-Economic Comparison and Parametric Optimizations among Two Compressed Air Energy Storage System Based on Kalina Cycle and ORC," Energies, MDPI, vol. 10(1), pages 1-19, December.
    18. Sciacovelli, Adriano & Li, Yongliang & Chen, Haisheng & Wu, Yuting & Wang, Jihong & Garvey, Seamus & Ding, Yulong, 2017. "Dynamic simulation of Adiabatic Compressed Air Energy Storage (A-CAES) plant with integrated thermal storage – Link between components performance and plant performance," Applied Energy, Elsevier, vol. 185(P1), pages 16-28.
    19. Guo, Huan & Xu, Yujie & Zhu, Yilin & Chen, Haisheng & Lin, Xipeng, 2022. "Unsteady characteristics of compressed air energy storage systems with thermal storage from thermodynamic perspective," Energy, Elsevier, vol. 244(PB).
    20. Li, Peng & Hu, Qingya & Han, Zhonghe & Wang, Changxin & Wang, Runxia & Han, Xu & Wang, Yongzhen, 2022. "Thermodynamic analysis and multi-objective optimization of a trigenerative system based on compressed air energy storage under different working media and heating storage media," Energy, Elsevier, vol. 239(PD).

    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:energy:v:205:y:2020:i:c:s0360544220311336. 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.journals.elsevier.com/energy .

    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.