An efficient interior-point algorithm with new non-monotone line search filter method for nonlinear constrained programming

Xu²,

et al. 2020

Ind. Eng. Chem. Res.

Self Cite

The number of stages is a basic structural parameter for the heat-integrated air separation column (HIASC) to improve its energy-saving potential. This paper, therefore, aims at the optimization of the number of stages of the HIASC regarding energy conservation and economic feasibility. A basic optimization problem is carried out showing the existence of an optimal number of stages regarding energy consumption with a fixed heat-transfer capacity. It is shown by the results that the energy use is reduced with an increased number of stages in a certain range, and a smaller heat-transfer capacity should be selected in the meantime. The heat-transfer capacity is taken as a variable in further optimization to exploit the energy-saving potential and evaluate its economic feasibility based on total annual costs. Results show that the HIASC can reduce energy consumption by 43.6% or the total annual costs by 18.7% compared with a conventional column.

Section: Optimizationmentioning

confidence: 99%

Optimization of Number of Stages for Energy Conservation and Economic Feasibility of the Heat-Integrated Air Separation Column

Xu²,

et al. 2020

Ind. Eng. Chem. Res.

Self Cite

Asia-Pacific J Chem Eng

“…Considering the large number of equations, the advanced solving method, such as Broyden-Fletcher-Goldfarb-Shanno SQP method [40] and interior point method, [41] should be employed. But the optimizer of gPROMS, named as SRQPD solver, employs SQP method for the solution of the nonlinear programming problem.…”

Section: Optimization Of Economic Benefitsmentioning

confidence: 99%

Trade‐off between energy consumption and ethylene recovery rate for quasi‐plant wide operation optimization of the ethylene column with bottom circulatory system in ethylene complex

Huang

Zhao

Luo

2017

Reducing energy consumption and increasing ethylene recovery rate can effectively optimize the operation of ethylene columns. This paper discusses the trade-off between energy consumption and recovery rate in different scenes. For normal condition, the influences of energy consumption and recovery rate on economic benefits are represented as energy consumption of separation and energy consumption of circulation, while the unseparated ethylene is recycled by the bottom circulatory system. The operation optimization, whose objective is economic benefits, is achieved at the lowest total energy consumption, the sum of energy consumption of separation and circulation. For abnormal condition caused by furnace decoking, the objectives of operation optimization are economic benefits and operability. Operability, affected with remarkable production fluctuation, is quantified by variation of gas and liquid loads. Moreover, the Pareto curve of the multiobjective optimization problem was obtained with total energy consumption and variation of gas/liquid loads as objectives, and the inflection point achieves the equilibrium of economic benefits and operability. Therefore, the balance of recovery rate and energy consumption is crucial to improve economic benefits. Furthermore, moderately operating recovery rate and energy consumption is suitable to maximize economic benefits and operability simultaneously for production fluctuation.

Annals of Computer Science and Information Systems

“…Moreover, it has a capability to solve problems with equality, as well as inequality constraints. An efficient primaldual interior-point algorithm using a new non-monotone line search filter method was presented in [20]. The designed nonmonotone line search technique has been introduced to lead to relaxed step acceptance conditions and improved convergence performance.…”

Section: Introductionmentioning

confidence: 99%

A general optimization-based approach for thermal processes modeling

Drąg

Styczein

2017

Abstract-In the article a new optimization approach for thermal processes modeling has been presented. In the designed method, the considered process is monitored by a measurement system with a thermal camera. Then, a spatio-temporal dynamics is discretized and transformed into a large-scale optimization problem with differential-algebraic constraints. To preserve the process dynamics in the assumed range, variability constraints have been imposed. Finally, a new interior-point optimization algorithm has been designed to solve the optimization problem with the variability constraints. The applicability of the new approach has been investigated experimentally.