Optimal scheduling of multiple sets of air separation units with frequent load-change operation

Zhou, Danyan; Zhou, Kai; Zhu, Lingyu; Zhao, Jun; Xu, Zuhua; Shao, Zili; Chen, Xi

doi:10.1016/j.seppur.2016.08.009

Cited by 49 publications

(24 citation statements)

References 21 publications

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“…Mode-based models have been applied in some of the most recent works on DSM planning and scheduling (Shrouf et al, 2014;Zhang et al, 2015aZhang et al, , 2016aZhou et al, 2017). In the most recent development, Zhang et al (2016e) have further generalized the model such that it can be used to represent continuous process networks.…”

Section: Prevalent Modeling Conceptsmentioning

confidence: 99%

“…The proposed model has been adopted by Zhang et al (2016a) to simultaneously optimize the long-term electricity procurement strategy for multiple air separation plants. A similar approach is taken by Zhou et al (2017) who also consider the interactions between multiple air separation units. Although Zhou et al (2017) consider demand rather then electricity price changes, the proposed model can be easily extended to be applied in a classical DSM setting.…”

Section: Across Multiple Space Scalesmentioning

confidence: 99%

“…A similar approach is taken by Zhou et al (2017) who also consider the interactions between multiple air separation units. Although Zhou et al (2017) consider demand rather then electricity price changes, the proposed model can be easily extended to be applied in a classical DSM setting.…”

Section: Across Multiple Space Scalesmentioning

confidence: 99%

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Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives

Zhang

Grossmann

2016

Chemical Engineering Research and Design

127

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The active management of electricity demand, also referred to as demand side management (DSM), has been recognized as an effective approach to increase power grid performance and consumer benefits. Being large electricity consumers, the power-intensive process industries play a key role in DSM. In particular, enterprise-wide optimization (EWO) for industrial DSM has emerged as a major area of interest for both researchers and practitioners. In this work, we introduce the reader to the fundamentals of power system economics, provide a definition of DSM that reflects more strongly the consumer's perspective, and present a comprehensive review of existing works on EWO for industrial DSM. The review is organized into four parts, which correspond to the four main challenges that we identify as: (1) accurate modeling of operational flexibility, (2) integration of production and energy management, (3) decision-making across multiple time and space scales, and (4) optimization under uncertainty. Finally, we highlight research gaps and future opportunities in this area.

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Section: Prevalent Modeling Conceptsmentioning

confidence: 99%

Section: Across Multiple Space Scalesmentioning

confidence: 99%

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Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives

Zhang

Grossmann

2016

Chemical Engineering Research and Design

127

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“…Xu et al proposed a two-layer framework automatic load change system integrated with nonlinear steady-state optimization and nonlinear model predictive control (MPC) for the nonlinearity, strong coupling and frequent load change of air separation systems (Xu et al, 2011). Zhou et al developed an optimal scheduling method under separate-mode strategy for the multiple sets of air separation units and the requirements of frequent load-change operation (Zhou et al, 2017). Fu and Liu studied the nonlinear behaviors of heat integrated air separation columns and carried out a novel nonlinear wave model predictive control scheme for them (Fu & Liu, 2015.…”

Section: Introductionmentioning

confidence: 99%

Automatic load change coordinated control of air separation units

Zou

Liu

Huang

et al. 2019

Control Engineering Practice

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“…The same topic was addressed in Zhang et al (2016c) whereby the combination of mode-based modeling approach and CRS models is used to model a network of continuous power-intensive processes. A similar approach was applied by Zhou et al (2017) to examine the optimal scheduling of a real-world production network.…”

Section: Introductionmentioning

confidence: 99%

A Discrete-time Scheduling Model for Continuous Power-intensive Processes Considering Fatigue of Equipment

Obermeier

Windmeier

Esche

et al. 2018

Computer Aided Chemical Engineering

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In the light of the growing renewable energy generation, matching of electricity supply and demand has become increasingly challenging. By participating in demand side management programs, industry can contribute to counter this challenge. However, the frequent adjustment of operation conditions according to volatile electricity prices leads to additional dynamic loads for the equipment. In this work, a mixed-integer linear programming based discrete-time model is proposed for scheduling of a single air separation unit, explicitly considering fatigue of equipment occurring during transient operation. Besides constraints for describing the feasible region and the process dynamics, this model includes constraints for considering mechanical fatigue of some key equipment. The resulting model is applied to investigate the impact of mechanical constraints on the potentials of demand side management.

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Optimal scheduling of multiple sets of air separation units with frequent load-change operation

Cited by 49 publications

References 21 publications

Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives

Enterprise-wide optimization for industrial demand side management: Fundamentals, advances, and perspectives

Automatic load change coordinated control of air separation units

A Discrete-time Scheduling Model for Continuous Power-intensive Processes Considering Fatigue of Equipment

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