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Optimal capacity allocation of multiple solar trackers and storage capacity for utility-scale photovoltaic plants considering output characteristics and complementary demand

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  • Hua, Zhengcao
  • Ma, Chao
  • Lian, Jijian
  • Pang, Xiulan
  • Yang, Weichao

Abstract

The most striking features of solar energy are its intermittency and instability resulting from environmental influence. Combination of different solar trackers can be a feasible option to stabilize output fluctuations. The main aim of this study was to analyze the optimal capacity allocation of multiple solar trackers and storage capacity. In this regard, a multi-objective optimization model considering fluctuations and the net present value was developed. A desert area in the west of China was considered as the case study. Results indicate that: (1) horizontal-axis trackers and its bifacial modules have complementarity with other kinds of solar trackers; (2) fluctuations of the photovoltaic plant with optimal capacity allocation can be significantly reduced; (3) optimal capacity allocation is sensitive to the feed-in tariff and the adjustment value of automatic generation control; (4) energy storage is crucial to improving the stability of the photovoltaic system while its capacity is constrained by the cost. The novel capacity allocation method does not only improve the stability and benefit of the utility-scale grid-connected photovoltaic plant but also provides a valuable reference for the optimal utilization of other renewable energy resources worldwide.

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  • Hua, Zhengcao & Ma, Chao & Lian, Jijian & Pang, Xiulan & Yang, Weichao, 2019. "Optimal capacity allocation of multiple solar trackers and storage capacity for utility-scale photovoltaic plants considering output characteristics and complementary demand," Applied Energy, Elsevier, vol. 238(C), pages 721-733.
    • Handle: RePEc:eee:appene:v:238:y:2019:i:c:p:721-733
    DOI: 10.1016/j.apenergy.2019.01.099
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    8. Li, Yan & Ming, Bo & Huang, Qiang & Wang, Yimin & Liu, Pan & Guo, Pengcheng, 2022. "Identifying effective operating rules for large hydro–solar–wind hybrid systems based on an implicit stochastic optimization framework," Energy, Elsevier, vol. 245(C).

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