A disjunctive programming model for superstructure optimization of power and desalting plants

Disjunctive multiperiod optimization methods for design and planning of chemical process systems

In this paper, we address a new optimal plate design problem in steel production, in which slab selection is jointly considered. On the basis of the underlying features, the problem is formulated as a mixed integer nonlinear programming (MINLP) model with generalized disjunctive programming (GDP) constraints. A logic-based outer approximation (L-OA) algorithm is proposed to solve the problem. Specifically, a two-stage heuristic method is designed to initialise the L-OA algorithm. Numerical results are presented to demonstrate that the proposed L-OA algorithm and the heuristic method are effective and computationally efficient.

The basic approach with the design of power plants is to first carry out a thermodynamic cycle analysis and then to vary certain cycle parameters such as the overall pressure ratio in order to determine the optimum or design point condition. One would then proceed to design the different components to match the process conditions. However, since component design has an impact on overall system performance, one cannot optimize the design of the components in isolation from the rest of the system. This calls for an iterative procedure where one has to move several times between the process and component levels to obtain an optimized integrated solution. Another problem faced by plant designers is that Computational Fluid Dynamics (CFD) codes that are increasingly used for detailed component design are slow and not well suited for optimization studies. They are not suited at all for the analysis of complete power plants. Furthermore, the main task of plant designers is not to do design point analyses but to analyze off-design performance, to do uncertainty analyses, to optimize the design and to characterize the dynamic behavior of the system for the purpose of controller design. An approach that has been used with great success for the design of the power conversion system of the Pebble Bed Modular Reactor (PBMR) is the systems CFD approach. The PBMR is a new High Temperature Gas-cooled Reactor (HTR) that is being developed in South Africa. The PBMR utilizes a direct closed recuperated Brayton cycle. Other cycles are also being investigated including various combined cycles. Systems CFD codes are based on the network approach and allow one to model the performance of large complex systems in an integrated fashion. Different levels of component models are provided for ranging from lumped models for components such as pumps to 1D, 2D or even 3D CFD models for components such as complex diffusers, heat exchangers and the pebble bed reactor. In this paper the systems CFD approach will be discussed including the most important component models. Various examples of the application of the systems CFD approach in the design of the PBMR plant will be given.

Optimal synthesis and design of Heat Recovery Steam Generation (HRSG) via mathematical programming

Exploration of optimal operating conditions for a natural gas combined-cycle power plant integrated with post-combustion CO2 capture using 2-amino-2-methyl-1-propanol/piperazine considering the propagation effect

ABSTRACTLeaching is a hydrometallurgical activity widely used in mineral processing, both for metallic and non-metallic ores, and in soil remediation. The dissolution of valuable species by heap leaching is strongly dependent on the design and operating variables, so the study of the influence of these variables on recovery and their optimization for the best performance are attractive tasks for the development of the mining industry. In this work, a methodology is developed that enables the planning and design of leaching systems. This methodology uses a proposed superstructure and a mathematical model to analyze the system behavior and determine the optimal design and operating conditions. The model was generated with a Mixed Integer Nonlinear Programming (MINLP) approach and solved by different solvers under GAMS® software (General Algebraic Modelling System). The Spatial Branch-and-Bound (SBB) solver obtained the global optimum in the shortest times. Based on a case of study for copper leaching, it is demonstrated that the procedure allows achieving optimal design and operational conditions.

The Medway Project is a 660 MW combined cycle power plant which employs two of the world’s largest advanced technology MS9001FA combustion turbine generators and an advanced design reheat steam turbine generator in a power plant system designed for high reliability and efficiency. This paper discusses the power plant system optimization and design, including thermodynamic cycle selection, equipment arrangement, and system operation. The design of the MS9031FA combustion turbine generator and the steam turbine generator, including tailoring for the specific application conditions, is discussed.

The Medway Project is a 660 MW combined cycle power plant, which employs two of the world’s largest advanced technology MS9001FA combustion turbine generators and an advanced design reheat steam turbine generator in a power plant system designed for high reliability and efficiency. This paper discusses the power plant system optimization and design, including thermodynamic cycle selection, equipment arrangement, and system operation. The design of the MS9001FA combustion turbine generator and the steam turbine generator, including tailoring for the specific application conditions, is discussed.

Thermoeconomic optimization of combined cycle power plants

This paper deals with the simultaneous optimization of the operating conditions and sizes of each one of the process units of a natural gas combined cycle coupled to a postcombustion CO2 capture system. Precisely, from the mathematical models previously developed by the authors for each stand-alone process, a new optimization nonlinear programming (NLP) model is proposed in order to optimize the whole process but with the main characteristic that several feasible alternatives to integrate both processes are simultaneously embedded. Therefore, as a result of the model, the best integration schema, optimal operating conditions, and size of each process unit are obtained at the same time. No integer variables are needed to model discrete decisions in both processes. The maximization of the overall thermal efficiency is considered as an objective function. However, the proposed NLP model can be easily extended into a mixed-integer nonlinear programming (MINLP) model if it is necessary for cost minimization. T...

Energy Hub is known as a new solution to reduce energy costs of the consumers using multiple energies. Therefore, this paper introduces a structure model of Energy Hub in residential areas where energy demands include electrical, heat and cold because of major changes of environmental temperature in different periods of the year. The mathematical models optimizing energy cost of Energy Hubs are presented with an objective function and constraints. Theof Energy Hub is valuated by comparing with a traditional energy supply structure. The calculation program is performed by General Algebraic Modeling System (GAMS). The efficiency and capability of the proposed model are illustrated by numerical results.

Integrated design and construction of a micro-central tower power plant

Performance analysis of two combined cycle power plants with different steam injection system design

With adjustment of energy structure and enhancement of environmental protection standard, gas-steam combined cycle power plants will be erupt gradually, especially with the project of gas being moved from WEST to EAST and liquefied natural gas (LNG)being imported, many more 350MW-class combined cycle power plants will be constructed in China. This paper begins wi discussing on how to choose gas turbine and optimize matching relationship between gas turbine and steam turbine, followed by analyzing application situations and characteristics of heat recovery of steam generators (Hrsg) with supplementary firing equipmen and without, giving several layout programs of steam turbine cycle system, analyzing the chosen method for steam cycle system. analyzing and comparing shafts of combined cycle power plant, analyzing effect on gas turbine performance caused by ambient temperature, providing therefore references to optimize design of large combined cycle power plants.

We describe four approaches to solving nonconvex global optimization problems by convex nonlinear programming methods. It is assumed that the problem becomes convex when selected variables are fixed. The selected variables must be discrete, or else discretized if they are continuous. We first survey some existing methods: disjunctive programming with convex relaxations, logic-based outer approximation, and logic-based Benders decomposition. We then introduce a branch-and-bound method with convex quasi-relaxations (BBCQ) that can be effective when the discrete variables take a large number of real values. The BBCQ method generalizes work of Bollapragada, Ghattas and Hooker on structural design problems. It applies when the constraint functions are concave in the discrete variables and have a weak homogeneity property in the continuous variables.