Published April 1, 2022 | Version v1
Journal article

Cascade hydropower station risk operation under the condition of inflow uncertainty

  • 1. State Key Laboratory of Eco-hydraulics in Northwest Arid Region of China (Xi'an University of Technology), Xi'an, 710048 (China)

Description

Highlights: • The Gibbs sampling model based on copula function is presented to simulate runoff. • The scenario tree method is employed to describe the uncertainty of inflow. • The Mean-variance is introduced to build the reservoir risk operation model. • The trade-off between hydropower generation, ecology and their risks of cascade hydropower stations is analyzed. Runoff is an important basis for the operation of hydropower. However, due to inflow uncertainty, the ideal practical operation process usually doesn't match with the plan, which exacerbates the power generation and ecological risks. Therefore, the purpose of this paper is to investigate the relationship between hydropower generation, ecology and their risks under the uncertainty of inflow. Gibbs sampling based on the copula function is presented to simulate the runoff. The scenario tree method is employed to describe the inflow uncertainty. The power generation risk operation model is developed based on the Mean-variance method. In addition, the expected minimum ecological risk model and its comparison model are proposed to analyze the relationship between power generation and ecological risk. The proposed methods are applied to a case study of the Lancang River cascade hydropower station. The results show that (1) The power generation risk of risk operation model decreased by 86.41% at the 90% scenario reduction level, compared with deterministic model. (2) There is an obvious competitive relationship between ecology and power generation, in the case of a 1% loss of expected power generation, the expected ecological risk can be reduced by 6.14%.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.energy.2021.122666

Additional details

Identifiers

DOI
10.1016/j.energy.2021.122666;
PII
S0360544221029157;

Publishing Information

Journal Title
Energy (Oxford)
Journal Volume
244
Journal Issue
Part A
Journal Page Range
vp.
ISSN
0360-5442
CODEN
ENEYDS

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54006531
Subject category
S13: HYDRO ENERGY; S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
ECOLOGY; HYDROELECTRIC POWER; POWER GENERATION; RIVERS; RUNOFF; SAMPLING
Descriptors DEC
ELECTRIC POWER; ENERGY SOURCES; ENVIRONMENTAL TRANSPORT; MASS TRANSFER; POWER; RENEWABLE ENERGY SOURCES; SURFACE WATERS

Optional Information

Copyright
Copyright (c) 2021 Elsevier Ltd. All rights reserved.