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An energy-constrained state priority list model using deferrable electrolyzers as a load management mechanism

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  • Wang, Dan
  • Zhou, Yue
  • Jia, Hongjie
  • Wang, Chengshan
  • Lu, Ning
  • Sui, Pang-Chieh
  • Fan, Menghua

Abstract

To reduce the consumption of fossil fuel and greenhouse gas (GHG) emissions, incentive-based policies are used to encourage end-users to utilize more clean energy. Hydrogen energy is an ideal clean energy that can be integrated into the next generation power grid. Deferrable electrolyzers (DEs), as a typical electricity-to-hydrogen conversion devices and capable of modulating power consumption, can convert excessive power to store electricity as hydrogen. Therefore it can be used as a method for load management. The main contribution of this paper is to propose an energy-constrained state priority list (ECSPL) model, for analyzing the charging response of aggregated loads consisting of DE units. The typical hysteresis control of DEs as a load management mechanism is first discussed. A characteristic parameter, i.e. the energy state of DE charging load, is used to group and prioritize the DE units. The proposed ECSPL model optimally determines the operating status of DE charging and standby process, and it maintains the user-desired DE charging trajectory considering customer-constraints. The proposed model maintains the diversity of operating status of DE charging and standby process to prevent unexpected synchronization phenomenon for operating status. To evaluate the performance of the proposed method, an estimated baseline of the aggregated DE charging loads is obtained based on natural hysteresis control. The ECSPL control method of DE units for intra-hour load balancing is then evaluated. The effects of different energy-constraints, deadbands of sampled end-use state comparison, error associated with the charging-trajectory measurements are modeled to evaluate the performance of controlled DE group. The ECSPL model is described and demonstrated by the modeling results of investigated DE units.

Suggested Citation

  • Wang, Dan & Zhou, Yue & Jia, Hongjie & Wang, Chengshan & Lu, Ning & Sui, Pang-Chieh & Fan, Menghua, 2016. "An energy-constrained state priority list model using deferrable electrolyzers as a load management mechanism," Applied Energy, Elsevier, vol. 167(C), pages 201-210.
    • Handle: RePEc:eee:appene:v:167:y:2016:i:c:p:201-210
    DOI: 10.1016/j.apenergy.2015.10.129
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    References listed on IDEAS

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    1. Troncoso, E. & Newborough, M., 2010. "Electrolysers as a load management mechanism for power systems with wind power and zero-carbon thermal power plant," Applied Energy, Elsevier, vol. 87(1), pages 1-15, January.
    2. Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2011. "Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market," Applied Energy, Elsevier, vol. 88(7), pages 2548-2558, July.
    3. Liu, Zhe & Wang, Dan & Jia, Hongjie & Djilali, Ned, 2014. "Power system operation risk analysis considering charging load self-management of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 136(C), pages 662-670.
    4. Wang, D. & Parkinson, S. & Miao, W. & Jia, H. & Crawford, C. & Djilali, N., 2012. "Online voltage security assessment considering comfort-constrained demand response control of distributed heat pump systems," Applied Energy, Elsevier, vol. 96(C), pages 104-114.
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    4. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Zhang, Zhen, 2018. "Coordination optimization of multiple thermostatically controlled load groups in distribution network with renewable energy," Applied Energy, Elsevier, vol. 231(C), pages 456-467.

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