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Long‐term generation scheduling for renewable‐dominant systems concerning limited energy supporting capability of hydrogeneration.

Authors :
Lin, Yisha
Qiao, Ying
Lu, Zongxiang
Source :
IET Generation, Transmission & Distribution (Wiley-Blackwell); Jan2022, Vol. 16 Issue 1, p57-70, 14p
Publication Year :
2022

Abstract

Renewable‐dominant mixtures with hydrogeneration and variable renewable energies (VREs) have been the focus for decarbonization of power systems. Hydrogeneration with large reservoir becomes the main regulating source. The long‐term generation scheduling (LTGS) on monthly reservoir regulation for the approaching year becomes more significant because reserving adequate water storage is related to intramonth balance, considering that hydrogeneration has to supplement deficit energy of VRE generation. However, conventional LTGS method that is based on monthly averages overestimates the hydrogeneration's intramonth energy supporting capability, whereas rolling short‐term generation scheduling method cannot account the long‐term effect of reservoir regulation decisions. This paper proposes a new LTGS method accounting intramonth imbalance risk that the energy deficit of VRE generation exceeds the maximum supporting energy of hydrogeneration. Since intramonth imbalance risk is coupled with LTGS in an uncertain and implicit way, intramonth extreme scenarios are introduced based on distribution quantiles of natural inflow of reservoirs and VRE generation, and the probabilistic intramonth imbalance risk constraints can be transformed as the hydrogeneration must supplement energy deficit of VRE generation during the extreme scenarios. A case study is conducted on a Wind‐PV‐Hydro energy base of southwestern China. The proposed method is found able to improve the feasibility and reliability of LTGS compared to other LTGS methods. Moreover, the high calculation efficiency of conventional LTGS method is inherited. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17518687
Volume :
16
Issue :
1
Database :
Complementary Index
Journal :
IET Generation, Transmission & Distribution (Wiley-Blackwell)
Publication Type :
Academic Journal
Accession number :
153936596
Full Text :
https://doi.org/10.1049/gtd2.12276