Enhancement in reliability-constrained unit commitment considering state-transition-process and uncertain resources

The high penetration of uncertain resources challenges the security of power system operation. By taking the impact of rescheduling under contingencies into consideration, reliability-constrained unit commitment (RCUC) is developed to address this challenge. Although several efforts have been made in modelling reliability constraints, the existing methods can only manage oversimplified low-order temporal-independent contingencies without considering wide-range contingencies or their state-transition-process issue. To quantify the impact of rescheduling on the normal-state scheduling process denoted by UC problem, this paper builds up a Bayesian inference method for encoding reliability constraints in wide-range temporal-dependent contingencies. Three predictors, for example, expected-generator-rescheduling-power, expected-energy-not-serviced and lost-of-load-probability, are selected to describe the possible corrective behaviours in rescheduling process and quantified by using Bayesian inference method. Then, these predictors are reformatted as a set of linearized constraints to be incorporated into UC. The proposed RCUC comprehensively considers the effect of rescheduling in wide-range temporal-dependent contingencies. Therefore, it can reveal the influence of generator rescheduling in wide-range contingencies and keep better reliability performance than those methods reported in previous RCUC studies. The modified IEEE 30-bus test system and IEEE 118-bus test system are used to show the proposed model's effectiveness.