A Rigorous MINLP Model for the Optimal Synthesis and Operation of Utility Plants

Bruno, Joan Carles; Fernández, Francisco; Castells, Francesc; Grossmann, Ignacio E.

doi:10.1205/026387698524901

Cited by 143 publications

(71 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For a fixed superstructure, Colmenares and Seider (1989) [25] solve an NLP for the integrated design of a utility plant and a chemical plant. The model of Papoulias and Grossmann (1983) [24] is refined by Bruno et al (1998) [26] who provide a MINLP formulation that considers nonlinear characteristics such as steam properties, efficiencies, and gas enthalpies in combustion turbines. Iyer and Grossmann (1998) [27] use a linear multi-period design and operation formulation to account for variable operating conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices

Mitra

Sun

Grossmann

2013

Energy

226

106

View full text Add to dashboard Cite

Combined heat and power (CHP) plants are widely used in industrial applications. In the aftermath of the recession, many of the associated production processes are under-utilized, which challenges the competitiveness of chemical companies. However, under-utilization can be a chance for tighter interaction with the power grid, which is in transition to the so-called smart grid, if the CHP plant can dynamically react to time-sensitive electricity prices.In this paper, we describe a generalized mode model on a component basis that addresses the operational optimization of industrial CHP plants. The mode formulation tracks the state of each plant component in a detailed manner and can account for different operating modes, e.g. fuel-switching for boilers and supplementary firing for gas turbines, and transitional behavior. Transitional behavior such as warm and cold start-ups, shutdowns and pre-computed start-up trajectories is modeled with modes as well. The feasible region of operation for each component is described based on input-output relationships that are thermodynamically sound, such as the Willans line for steam turbines. Furthermore, we emphasize the use of mathematically efficient logic constraints that allow solving the large-scale models fast.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices

Mitra

Sun

Grossmann

2013

Energy

226

106

View full text Add to dashboard Cite

show abstract

“…Bruno et al [72] proposed a superstructure optimization formulated as a MINLP based on the previous work by Papoulias & Grossmann [62]. Manninen & Zhu [73] decomposed the problem into a Master problem that specifies major structural features on a design and flowsheet level, in which an exergy analysis identifies relevant modification options.…”

Section: Case Studymentioning

confidence: 99%

“…In this work we use a superstructure inspired by the previous work of Bruno et al [72]. Figure 2 shows the superstructure, which includes:…”

Section: Case Studymentioning

confidence: 99%

Integration of different models in the design of chemical processes: Application to the design of a power plant

2014

View full text Add to dashboard Cite

With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the 'best available model'. However, in practice, these models are usually little more than a black box with a rigid input-output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular -equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.

show abstract

“…For example, the molar enthalpy of a pure ideal gas stream i is calculated with the following equation: 14) where y = T /1000, h ref is associated with the reference value calculating the enthalpy and a i , b i , c i , and d i are constants depending on the substance being considered. All gas streams in the process are treated as mixtures of ideal gases.…”

Section: Working Fluid Propertiesmentioning

confidence: 99%

Optimization of the Design and Partial-Load Operation of Power Plants Using Mixed-Integer Nonlinear Programming

Jüdes

Vigerske

Tsatsaronis

2009

Optimization in the Energy Industry

View full text Add to dashboard Cite

Summary. This paper focuses on the optimization of the design and operation of combined heat and power plants (cogeneration plants). Due to the complexity of such an optimization task, conventional optimization methods consider only one operation point that is usually the full-load case. However, the frequent changes in demand lead to operation in several partial-load conditions. To guarantee a technically feasible and economically sound operation, we present a mathematical programming formulation of a model that considers the partial-load operation already in the design phase of the plant. This leads to a nonconvex mixed-integer nonlinear program (MINLP) due to discrete decisions in the design phase and discrete variables and nonlinear equations describing the thermodynamic status and behavior of the plant. The model is solved using an extended Branch and Cut algorithm that is implemented in the solver LaGO. We describe conventional optimization approaches and show that without consideration of different operation points, a flexible operation of the plant may be impossible. Further, we address the problem associated with the uncertain cost functions for plant components.Keywords. cogeneration plant, partial load performance, design optimization, cost minimization, nonconvex mixed-integer nonlinear programming, branch and cut IntroductionIn deregulated energy markets the optimization of the design and operation of energy conversion plants becomes increasingly important. To reduce the product cost during the entire operation time of a plant, both selection of an optimal plant structure and selection of optimal operating parameters in different load situations are necessary. Several design optimization methods were developed and applied to energy conversion systems in the past, e.g.,

show abstract

A Rigorous MINLP Model for the Optimal Synthesis and Operation of Utility Plants

Cited by 143 publications

References 13 publications

Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices

Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices

Integration of different models in the design of chemical processes: Application to the design of a power plant

Optimization of the Design and Partial-Load Operation of Power Plants Using Mixed-Integer Nonlinear Programming

Contact Info

Product

Resources

About