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ROI-based study on impact factors of distributed PV projects by LSSVM-PSO

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  • Dong, Rentao
  • Xu, Jiuping
  • Lin, Bo

Abstract

A recent upsurge of investment in photovoltaic (PV) industry in China has made outstanding contributions to the adjustment of energy structure. In order to further promote the investment and construction of PV projects, the state has published many fiscal subsidy policies. In addition to unified national subsidy standard, local standards have been developed according to local fiscal revenue. They either have greatly improved return on investment (ROI) or have no significant effect as a result of too many impact factors. This paper utilizes multi dimensional big dates of distributed PV projects to obtain the weight of factors influencing the ROI from the calculation equation of ROI, which is fitted with innovative big data mining method of LSSVM-PSO. Results show that construction cost, sunshine duration, retail electricity tariff and subsidy have the greatest impacts. This study provides decision makers with quantitative basis for more comprehensive understanding on economic aspect of the distributed PV projects.

Suggested Citation

  • Dong, Rentao & Xu, Jiuping & Lin, Bo, 2017. "ROI-based study on impact factors of distributed PV projects by LSSVM-PSO," Energy, Elsevier, vol. 124(C), pages 336-349.
  • Handle: RePEc:eee:energy:v:124:y:2017:i:c:p:336-349
    DOI: 10.1016/j.energy.2017.02.056
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    2. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Chen, Kaifeng & Sun, Xiaokun, 2018. "An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China," Energy, Elsevier, vol. 143(C), pages 295-309.
    3. Huang, Yuqing & Lan, Hai & Hong, Ying-Yi & Wen, Shuli & Yin, He, 2019. "Optimal generation scheduling for a deep-water semi-submersible drilling platform with uncertain renewable power generation and loads," Energy, Elsevier, vol. 181(C), pages 897-907.
    4. Lu, Qing & Yu, Hao & Zhao, Kangli & Leng, Yajun & Hou, Jianchao & Xie, Pinjie, 2019. "Residential demand response considering distributed PV consumption: A model based on China's PV policy," Energy, Elsevier, vol. 172(C), pages 443-456.
    5. Xing Zhang, 2018. "Short-Term Load Forecasting for Electric Bus Charging Stations Based on Fuzzy Clustering and Least Squares Support Vector Machine Optimized by Wolf Pack Algorithm," Energies, MDPI, vol. 11(6), pages 1-18, June.
    6. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).

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