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

Abstract

Abstract 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.

Keywords

• Reliability
• Other topics in statistics
• Power system management, operation and economics
• Other topics in statistics
• Power engineering computing
• Reasoning and inference techniques