Stochastic Optimization Models for Risk-Based Reservoir Management*

Ermoliev, Y., Ermolieva, T., Kahil, T. ORCID: https://orcid.org/0000-0002-7812-5271, Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769, Gorbachuk, V., & Knopov, P. (2019). Stochastic Optimization Models for Risk-Based Reservoir Management*. Cybernetics and Systems Analysis 55 (1) 55-64. 10.1007/s10559-019-00112-z.

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Abstract

The paper provides an overview of publications on reservoir management and formulates a novel stochastic dynamic optimization model for water balance management in the area affected. The proposed stochastic optimization approach allows multiple key performance indicators such as agriculture and energy production, wetland water and flood protection, biodiversity preservation, and reservoir storage. The two-stage feature of the proposed model induces safety constraints on water supply known as chance conditions in stochastic optimization: safety constraints in nuclear energy, stability constraints in insurance business, or constraints on the Conditional Value-at-Risk (CVaR) in finance. The original nonlinear, nonconvex and often discontinuous model can be reduced to linear programming problems.

Item Type:	Article
Uncontrolled Keywords:	stochastic optimization; risk; water resource management; two-stage problem; extreme events
Research Programs:	Ecosystems Services and Management (ESM) Water (WAT)
Depositing User:	Luke Kirwan
Date Deposited:	27 Feb 2019 08:51
Last Modified:	02 Feb 2022 14:13
URI:	https://pure.iiasa.ac.at/15769

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