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A novel hierarchical contribution factor based model for distribution use-of-system charges

Author

Listed:
  • Sharma, A.
  • Bhakar, R.
  • Tiwari, H.P.
  • Li, R.
  • Li, F.

Abstract

Due to the limited visibility at low voltage (LV) networks, existing Distribution Use-of-System (DUoS) charging methodologies assume that all the network users use the network in proportion to their peak flows. This naive supposition fails to reflect the contribution of network users to network peak flows, which actually is the driver for network reinforcement. This can send an inadvertent signal to customers, leading to aggravated network pressure. This paper for the first time, brings the new dimension into the design of DUoS charging methodology by considering the true contribution of customer class’s load on network peak flows. It proposes a novel Hierarchical Contribution Factor based Model (HCM), recognizing the contributions of differing customer classes to the network reinforcement of upstream asset. Such contribution will be further propagated to network assets at higher voltage level, forming a Hierarchical CF model and reflecting the true individual class contribution to the whole-system reinforcement. Benefit of the proposed model on investment deferral is assessed by determining annuitized present value (PV) of future investments, and consequences are assessed on a 22-bus practical Indian reference network. The approach helps customers as a class to reduce their network usage charges by minimizing their energy usage contribution during distribution network peaks, eventually reducing distribution network investment and energy transfer costs.

Suggested Citation

  • Sharma, A. & Bhakar, R. & Tiwari, H.P. & Li, R. & Li, F., 2017. "A novel hierarchical contribution factor based model for distribution use-of-system charges," Applied Energy, Elsevier, vol. 208(C), pages 996-1006.
  • Handle: RePEc:eee:appene:v:208:y:2017:i:c:p:996-1006
    DOI: 10.1016/j.apenergy.2017.09.050
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    1. Thellufsen, Jakob Zinck & Lund, Henrik, 2016. "Roles of local and national energy systems in the integration of renewable energy," Applied Energy, Elsevier, vol. 183(C), pages 419-429.
    2. Gaiser, Kyle & Stroeve, Pieter, 2014. "The impact of scheduling appliances and rate structure on bill savings for net-zero energy communities: Application to West Village," Applied Energy, Elsevier, vol. 113(C), pages 1586-1595.
    3. Shahmohammadi, M. Sadegh & Mohd. Yusuff, Rosnah & Keyhanian, Sina & Shakouri G., Hamed, 2015. "A decision support system for evaluating effects of Feed-in Tariff mechanism: Dynamic modeling of Malaysia’s electricity generation mix," Applied Energy, Elsevier, vol. 146(C), pages 217-229.
    4. Serra, Pablo J., 1997. "Energy pricing under uncertain supply," Energy Economics, Elsevier, vol. 19(2), pages 209-223, May.
    5. Brusco, Giovanni & Burgio, Alessandro & Menniti, Daniele & Pinnarelli, Anna & Sorrentino, Nicola, 2016. "The economic viability of a feed-in tariff scheme that solely rewards self-consumption to promote the use of integrated photovoltaic battery systems," Applied Energy, Elsevier, vol. 183(C), pages 1075-1085.
    6. Tan, Sieting & Yang, Jin & Yan, Jinyue & Lee, Chewtin & Hashim, Haslenda & Chen, Bin, 2017. "A holistic low carbon city indicator framework for sustainable development," Applied Energy, Elsevier, vol. 185(P2), pages 1919-1930.
    7. Wang, Mingshen & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qi, Yan, 2017. "Active power regulation for large-scale wind farms through an efficient power plant model of electric vehicles," Applied Energy, Elsevier, vol. 185(P2), pages 1673-1683.
    8. Qadrdan, Meysam & Chaudry, Modassar & Jenkins, Nick & Baruah, Pranab & Eyre, Nick, 2015. "Impact of transition to a low carbon power system on the GB gas network," Applied Energy, Elsevier, vol. 151(C), pages 1-12.
    9. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    10. Herrando, María & Markides, Christos N. & Hellgardt, Klaus, 2014. "A UK-based assessment of hybrid PV and solar-thermal systems for domestic heating and power: System performance," Applied Energy, Elsevier, vol. 122(C), pages 288-309.
    11. Teng, Fei & Aunedi, Marko & Strbac, Goran, 2016. "Benefits of flexibility from smart electrified transportation and heating in the future UK electricity system," Applied Energy, Elsevier, vol. 167(C), pages 420-431.
    12. Drysdale, Brian & Wu, Jianzhong & Jenkins, Nick, 2015. "Flexible demand in the GB domestic electricity sector in 2030," Applied Energy, Elsevier, vol. 139(C), pages 281-290.
    Full references (including those not matched with items on IDEAS)

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