Reliability-constrained unit commitment using stochastic mixed-integer programming

This paper proposes a stochastic mixed-integer programming (SMIP) model for the reliability-constrained unit commitment (RCUC) problem. The major objective of the paper is to examine both features of accuracy and efficiency of the proposed SMIP model of RCUC. The spinning reserve of generating units is considered as the only available reserve provision resource; however, the proposed formulation can be readily extended to comprise the other kind of reserve facilities. Expected load not served (ELNS) and loss of load probability (LOLP) are accommodated as the reliability constraints. Binding either or both reliability indices ensures the security of operation incorporating the stochastic nature of component outages. In this situation, the spinning reserve requirement is no longer considered explicitly. The Monte Carlo simulation method is used to generate scenarios for the proposed SMIP model. The scenario reduction method is also adopted to reduce computation burden of the proposed method. The IEEE reliability test system (RTS) is employed to numerically analyze the proposed model and the implementation issues are discussed. The simulations are conducted in the single- and multi-period bases and the performance of the model is investigated verses different reliability levels and various numbers of scenarios.