A decomposition approach to the two-stage stochastic unit commitment problem
From MaRDI portal
Publication:2442096
DOI10.1007/s10479-012-1092-7zbMath1284.90114OpenAlexW2082279688WikidataQ57734123 ScholiaQ57734123MaRDI QIDQ2442096
Panos M. Pardalos, Jianhui Wang, Qipeng Phil Zheng, Yongpei Guan
Publication date: 31 March 2014
Published in: Annals of Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10479-012-1092-7
energyBenders decompositionstochastic mixed integer programmingmixed integer subproblemtwo-stage stochastic unit commitment
Applications of mathematical programming (90C90) Mixed integer programming (90C11) Stochastic programming (90C15)
Related Items
Short-term balancing of supply and demand in an electricity system: forecasting and scheduling, Decomposition algorithm for large-scale two-stage unit-commitment, Towards a sustainable power grid: stochastic hierarchical planning for high renewable integration, An extended formulation for two-stage stochastic unit commitment with reserves, Extreme Ray Feasibility Cuts for Unit Commitment with Uncertainty, Integrated Stochastic Optimal Self-Scheduling for Two-Settlement Electricity Markets, A data mining transmission switching heuristic for post-contingency AC power flow violation reduction in real-world, large-scale systems, A Nested Cross Decomposition Algorithm for Power System Capacity Expansion with Multiscale Uncertainties, Large-scale unit commitment under uncertainty: an updated literature survey, Contingency-constrained unit commitment with post-contingency corrective recourse, A stabilised scenario decomposition algorithm applied to stochastic unit commitment problems, Solution sensitivity-based scenario reduction for stochastic unit commitment, An accelerated L-shaped method for solving two-stage stochastic programs in disaster management, Multistage Stochastic Power Generation Scheduling Co-Optimizing Energy and Ancillary Services, Large-scale unit commitment under uncertainty, Operations research in optimal power flow: a guide to recent and emerging methodologies and applications
Cites Work
- Unnamed Item
- Unnamed Item
- A modification of Benders' decomposition algorithm for discrete subproblems: An approach for stochastic programs with integer recourse
- Stochastic and risk management models and solution algorithm for natural gas transmission network expansion and LNG terminal location planning
- The integer \(L\)-shaped method for stochastic integer programs with complete recourse
- Large-scale mixed integer programming: Benders-type heuristics
- Partitioning procedures for solving mixed-variables programming problems
- L-shaped decomposition of two-stage stochastic programs with integer recourse
- A hierarchy of relaxations and convex hull characterizations for mixed- integer zero-one programming problems
- Unit commitment in power generation -- a basic model and some extensions
- A lift-and-project cutting plane algorithm for mixed 0-1 programs
- Decomposition with branch-and-cut approaches for two-stage stochastic mixed-integer programming
- Unit commitment in electricity pool markets
- On solving discrete two-stage stochastic programs having mixed-integer first- and second-stage variables
- Generalized Benders decomposition
- The \(C^3\) theorem and a \(D^2\) algorithm for large scale stochastic mixed-integer programming: set convexification
- Accelerating Benders Decomposition by Local Branching
- Disjunctive Decomposition for Two-Stage Stochastic Mixed-Binary Programs with Random Recourse
- A Stochastic Programming Approach to Power Portfolio Optimization
- Accelerating Benders method using covering cut bundle generation
- Accelerating Benders Decomposition: Algorithmic Enhancement and Model Selection Criteria
- The value function of an integer program
- A Modified Benders' Partitioning Algorithm for Mixed Integer Programming
- Disjunctive Programming
- Introduction to Stochastic Programming
- Inexact Cuts in Benders Decomposition
- Cutting Planes for Multistage Stochastic Integer Programs
- L-Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming