@inproceedings{rom-can-17-aa-unitcom,
  author = {David Fernando {Romero-Quete} and Claudio A. Canizares},
  title = {Affine Arithmetic Formulation of the Unit Commitment Problem Under Uncertainty},
  booktitle = {Proc. Bulk Power Systems Dynamics and Control Symposium (IREP 2017)},
  location = {Espinho, Portugal},
  year = 2017,
  month = aug,
  comment = {Application to power allocation and generator on/off schedule},
  abstract = {This paper proposes a method based on affine arithmetic (AA) to solve the unit commitment (UC) problem, considering load and renewable energy (RE) uncertainties. The main idea is to formulate an AA-based constrained multi-objective problem that not only provides a robust commitment solution, but also provides confidence intervals for active powers and operating costs, as well as dispatch solutions for all possible load and RE generation realizations for the predetermined uncertainty bounds. Moreover, the AA-based UC (AAUC) approach allows to explore solutions where the impact of the re-dispatch cost in the total operation cost can be reduced by adjusting the objective function weight values. The proposed approach can be used to better estimate day-ahead energy prices and explore more costefficient solutions under uncertainty, as well as for real-time dispatching. The AAUC approach is tested and compared against stochastic optimization UC (SOUC), interval optimization UC (IOUC), and Monte Carlo simulation (MCS) approaches, on a sixbus system and a modified IEEE 118-bus system. The simulations results show that the proposed approach provides more accurate confidence intervals for active power and operating costs than IOUC, using MCS results as the benchmark, and has a better computational performance than SOUC}
}