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

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 lostof-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 temporaldependent 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.

Random Furrowing for a Stochastic Unit Commitment Solution

“…The Unit Commitment Problem (UCP) has thrown up several solution methods [4,5]. The authors have developed a random furrowing technique to generate a generic solution.…”

“…By themselves, they do not form power states. This shortcoming is addressed while considering a micro-level power system, which consists of a fewer number of units; each, assuming a relatively larger number of de-rated states [4]. Using an appropriate interval value ki (Column5), Pit is made to swing between Pmin i and Pmax i for the ith unit in the t th interval.…”

Adaptive distributed scheduling of the resources in smart grids with considering demand response

“…Some system lines can be opened and closed dynamically over time in real-world applications. Incorporating this feature into the UC problem makes it more difficult to solve (Yuan et al, 2021). In this regard, various algorithms have been proposed in the literature in which the UC problem is solved in different methods.…”