Search

During the design of the carbon capture and hydrogen storage process, a static CO 2 hydrogenation poly-generation process for methanol and formic acid synthesis was developed, thereby reducing recycling flow and feedstock losses in the single methanol synthesis process and increasing product diversity. Additionally, a novel flexible poly-generation process was proposed as the product prices fluctuated with the market environment throughout the plant's life cycle. For the static poly-generation process, a mixed integer nonlinear programming model was established, followed by the Mesh Adaptive Direct Search algorithm to determine the optimal parameter design. For flexible processes, with the unscented transform tool, a two-stage optimization strategy is proposed for obtaining optimal design and operating parameters that are computationally tractable. With an input CO 2 flow rate of 200 kmol/h, the results show (1) the static process with an optimal Return On Investment of 13.05%, a fixed investment cost of $ 34.14 × 106, and an annual net profit of 4.46 × 106 $/year; and (2) the flexible process, in which the flexibility indices of the methanol and formic acid production units are 1.088 and 1.194, respectively, resulting the fixed investment cost increase to $ 39.19 × 106, an increase of 14.79%. Accordingly, the annual net profit increased by 8.97% to 4.86 × 106 $/year, while the Return On Investment decreased by 4.67%–12.44%. For investment decision-makers, the flexible poly-generation process can achieve higher profits and reduce potential market risks when they have adequate financing. • A static CO 2 hydrogenation process for MeOH and FA poly-generation process is established. • A MINLP model is developed to obtain the optimal parameter design for the static process. • Conversion continuous variables into scenario variables by unscented transform tool. • The optimal flexible poly-generation process design is obtained by the two-stage optimization strategy. [ABSTRACT FROM AUTHOR]

The lightning performance of transmission lines is a criterion of utmost importance to be evaluated in transmission system reliability. In order to accurately estimate the expected number of shutdowns, it is imperative to account for the stochastic nature of the lightning phenomenon. In this sense, the most widely used technique to estimate these shutdowns is the Monte Carlo method (MCM). Although the MCM is a trustful method, it has a huge drawback in terms of computational burden. Therefore, this paper proposes the use of an alternative statistical technique, the Unscented Transform method (UTM). This method achieves an approximate non-linear mapping by employing a set of points (associated with input statistical data), which are deterministically selected and weighted. The set of these points and weights is then used to estimate the lightning overvoltage across insulator strings, which represents a significant reduction in the number of samples evaluated in the process in relation to the application from MCM. In this paper, the MCM and UTM methods are applied and compared in the lightning overvoltage evaluation, which is carried out with the help of the Alternative Transient Program (ATP). From the studies conducted, it was found that the application of UTM in place of MCM allowed for significant computational gains while maintaining satisfactory levels of accuracy in the estimation of indicators. • Unscented Transform applied to transmission line lightning performance estimation. • Monte Carlo applied to transmission line lightning performance estimation. • Accelerating the assessment process of transmission line lightning performance. • Monte Carlo and Unscented Transform performance in lightning-related study. [ABSTRACT FROM AUTHOR]