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Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China

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  • Xu, Qingyang
  • Sun, Feihu
  • Cai, Qiran
  • Liu, Li-Jing
  • Zhang, Kun
  • Liang, Qiao-Mei

Abstract

The development of renewable energy (RE) is a critical path to achieve global climate goals and energy conversion. The understanding of Demand-side response (DR) is crucial for the stability and efficiency of renewable energy system (RES). The DR strategies are performed by coordinating various energy sources and electricity demand optimally in the operation of high penetration of renewable generations across different seasons from 2015 to 2050 using Qinghai, China as an example. The results show the reduced peak demand by DR is various in different seasons, and the shifted peak demand will be 56.8 GWh-596.5 GWh in 2050. In general, DR could cause a significant reduction of the total costs by avoiding unnecessary installed capacity from ￥2.19 billion to ￥28.62 billion in 2050. In the short-term, the structure of high-proportion RES cannot rapidly adjust to a new form. However, in the long-term, hydropower will have a large share in RES due to the ability of improving the synergistic stability of the high-proportion RES. In addition, the adoption of DR demonstrates a great potential on reducing PV curtailment and wind curtailment.

Suggested Citation

  • Xu, Qingyang & Sun, Feihu & Cai, Qiran & Liu, Li-Jing & Zhang, Kun & Liang, Qiao-Mei, 2022. "Assessment of the influence of demand-side responses on high-proportion renewable energy system: An evidence of Qinghai, China," Renewable Energy, Elsevier, vol. 190(C), pages 945-958.
    • Handle: RePEc:eee:renene:v:190:y:2022:i:c:p:945-958
    DOI: 10.1016/j.renene.2022.03.028
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    References listed on IDEAS

    as
    1. Khan, Muhammad T. & Thopil, George Alex & Lalk, Jorg, 2016. "Review of proposals for practical power sector restructuring and reforms in a dynamic electricity supply industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 326-335.
    2. Antonio Frangioni & Claudio Gentile, 2006. "Solving Nonlinear Single-Unit Commitment Problems with Ramping Constraints," Operations Research, INFORMS, vol. 54(4), pages 767-775, August.
    3. Qadrdan, Meysam & Cheng, Meng & Wu, Jianzhong & Jenkins, Nick, 2017. "Benefits of demand-side response in combined gas and electricity networks," Applied Energy, Elsevier, vol. 192(C), pages 360-369.
    4. Jonathan T. Lee & Duncan S. Callaway, 2018. "The cost of reliability in decentralized solar power systems in sub-Saharan Africa," Nature Energy, Nature, vol. 3(11), pages 960-968, November.
    5. Liu, Zuming & Zhao, Yingru & Wang, Xiaonan, 2020. "Long-term economic planning of combined cooling heating and power systems considering energy storage and demand response," Applied Energy, Elsevier, vol. 279(C).
    6. Pang, Yuexia & He, Yongxiu & Jiao, Jie & Cai, Hua, 2020. "Power load demand response potential of secondary sectors in China: The case of western Inner Mongolia," Energy, Elsevier, vol. 192(C).
    7. Bradley, Peter & Leach, Matthew & Torriti, Jacopo, 2013. "A review of the costs and benefits of demand response for electricity in the UK," Energy Policy, Elsevier, vol. 52(C), pages 312-327.
    8. Azadeh, A. & Tarverdian, S., 2007. "Integration of genetic algorithm, computer simulation and design of experiments for forecasting electrical energy consumption," Energy Policy, Elsevier, vol. 35(10), pages 5229-5241, October.
    9. Padrón, S. & Medina, J.F. & Rodríguez, A., 2011. "Analysis of a pumped storage system to increase the penetration level of renewable energy in isolated power systems. Gran Canaria: A case study," Energy, Elsevier, vol. 36(12), pages 6753-6762.
    10. Gao, Jianwei & Ma, Zeyang & Guo, Fengjia, 2019. "The influence of demand response on wind-integrated power system considering participation of the demand side," Energy, Elsevier, vol. 178(C), pages 723-738.
    11. Mimica, Marko & Dominković, Dominik Franjo & Capuder, Tomislav & Krajačić, Goran, 2021. "On the value and potential of demand response in the smart island archipelago," Renewable Energy, Elsevier, vol. 176(C), pages 153-168.
    12. Neves, Diana & Pina, André & Silva, Carlos A., 2018. "Assessment of the potential use of demand response in DHW systems on isolated microgrids," Renewable Energy, Elsevier, vol. 115(C), pages 989-998.
    13. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    14. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    15. Montuori, Lina & Alcázar-Ortega, Manuel & Álvarez-Bel, Carlos & Domijan, Alex, 2014. "Integration of renewable energy in microgrids coordinated with demand response resources: Economic evaluation of a biomass gasification plant by Homer Simulator," Applied Energy, Elsevier, vol. 132(C), pages 15-22.
    Full references (including those not matched with items on IDEAS)

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