Identifying effective operating rules for large hydro–solar–wind hybrid systems based on an implicit stochastic optimization framework

Yan Li, Bo Ming, Qiang Huang, Yimin Wang, Pan Liu and Pengcheng Guo

Energy, 2022, vol. 245, issue C

Abstract: Optimization of operational strategies of a hydro–solar–wind hybrid renewable energy system (HRES) could increase resource use efficiency without additional investment. However, because of the myopic nature of the short-term forecast information, the short-term optimal operation strategy of the large HRES cannot guarantee a satisfactory long-term system performance. Therefore, it is necessary to explore reasonable long-term operation strategies for the hydro–solar–wind HRES, especially the establishment of operating rules. In this study, we proposed a method to identify effective long-term operating rules for the large hydro–solar–wind HRES based on an implicit stochastic optimization framework. A large hydro–solar–wind HRES located in the upper Yellow River, China was selected as a case study. It was found that: (1) Operating rules taking reservoir storage or water level as the output variable and available energy as the input variable were most effective to guide the complementary operation of the hydro–solar–wind HRES; (2) Compared with a standard operating policy, the identified best operating rules could increase energy production and guaranteed rate of the HRES by 5.2% and 4%, respectively; and (3) Complementary management of hydro, solar and wind could increase the energy production of the hydropower system, when power transmission capacity was large enough.

Keywords: Hybrid energy system; Cascade hydropower plants; Renewable energy; Operating rules; Implicit stochastic optimization (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:245:y:2022:i:c:s0360544222001633

DOI: 10.1016/j.energy.2022.123260

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