Large-scale Security Constrained Unit Commitment Optimization Method Based on Multiple Strategy Combination of Model Dimension Reduction

The efficient operation of electricity spot market needs the support of high-performance clearing algorithm. Security-constrained unit commitment (SCUC) is one of the most important programs executed to plan a secure and economical hourly generation schedule. With the expanding of the scale of power grid, more and more generator variables and security constraints have been added in SCUC model. The size and the complexity of large-scale SCUC are often beyond reasonable computing time and resources. This paper introduces an efficient fast SCUC based on model dimension reduction for large-scale and long-term power systems. Model dimension reduction strategy used in the proposed approach include neighboring time interval combine, inactive generator state variables identification and inactive security constraints identification. A reasonable multiple strategy combination of model dimension reduction is explored. Then the number of unit variables, security constraints and time intervals can be reduced so as to lower the goal of solving dimensions. A modified IEEE RTS system, and a large system with 805 thermal units are analyzed. The results show that the proposed optimization method can greatly reduce the optimization time while retaining a high precision required by engineering calculation.