Applying High Performance Computing to Transmission-Constrained Stochastic Unit Commitment for Renewable Energy Integration
- 6 August 2014
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Power Systems
- Vol. 30 (3) , 1109-1120
Abstract
We present a parallel implementation of Lagrangian relaxation for solving stochastic unit commitment subject to uncertainty in renewable power supply and generator and transmission line failures. We describe a scenario selection algorithm inspired by importance sampling in order to formulate the stochastic unit commitment problem and validate its performance by comparing it to a stochastic formulation with a very large number of scenarios, that we are able to solve through parallelization. We examine the impact of narrowing the duality gap on the performance of stochastic unit commitment and compare it to the impact of increasing the number of scenarios in the model. We report results on the running time of the model and discuss the applicability of the method in an operational setting.Keywords
All Related Versions
This publication has 41 references indexed in Scilit:
- A methodology to generate statistically dependent wind speed scenariosApplied Energy, 2010
- Unit Commitment for Systems With Significant Wind PenetrationIEEE Transactions on Power Systems, 2009
- Forecast of hourly average wind speed with ARMA models in Navarre (Spain)Solar Energy, 2005
- A Solution to the Stochastic Unit Commitment Problem Using Chance Constrained ProgrammingIEEE Transactions on Power Systems, 2004
- Scenario reduction in stochastic programmingMathematical Programming, 2003
- Duality Gaps in Stochastic Integer ProgrammingJournal of Global Optimization, 2000
- The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods SubcommitteeIEEE Transactions on Power Systems, 1999
- Monte Carlo (importance) sampling within a benders decomposition algorithm for stochastic linear programsAnnals of Operations Research, 1992
- Composite generation/transmission reliability evaluationProceedings of the IEEE, 1992
- Time Series Models to Simulate and Forecast Wind Speed and Wind PowerJournal of Climate and Applied Meteorology, 1984