Non-anticipative risk-averse analysis with effective scenarios applied to long-term hydrothermal scheduling
From MaRDI portal
Publication:2695694
DOI10.1007/s40314-023-02258-1OpenAlexW4360609116MaRDI QIDQ2695694
Karla Cristiane Arsie, Elizabeth W. Karas, Gislaine A. Periçaro, Clóvis C. Gonzaga
Publication date: 31 March 2023
Published in: Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40314-023-02258-1
stochastic programmingnonlinear optimizationhydrothermal power systemsnon-anticipative scenario analysis
Large-scale problems in mathematical programming (90C06) Applications of mathematical programming (90C90) Stochastic programming (90C15)
Cites Work
- Unnamed Item
- The value of rolling-horizon policies for risk-averse hydro-thermal planning
- Comparing stochastic optimization methods to solve the medium-term operation planning problem
- Scenario optimization
- Multi-stage stochastic optimization applied to energy planning
- Scenario reduction for stochastic programs with conditional value-at-risk
- Identifying effective scenarios in distributionally robust stochastic programs with total variation distance
- Risk-averse feasible policies for large-scale multistage stochastic linear programs
- Global convergence of a general filter algorithm based on an efficiency condition of the step
- Optimal non-anticipative scenarios for nonlinear hydro-thermal power systems
- Optimal scenario tree reduction for stochastic streamflows in power generation planning problems
- Scenarios and Policy Aggregation in Optimization Under Uncertainty
- Contemporaneous bivariate time series