Optimization of a network of compressors in parallel: Operational and maintenance planning – The air separation plant case

A general mathematical framework for the optimization of compressors operations in air separation plants that considers operating constraints for compressors, several types of maintenance policies and managerial aspects is presented. The proposed approach can be used in a rolling horizon scheme. The operating status, the power consumption, the startup and the shutdown costs for compressors, the compressor-to-header assignments as well as the outlet mass flow rates for compressed air and distillation products are optimized under full demand satisfaction. The power consumption in the compressors is expressed by regression functions that have been derived using technical and historical data. Several case studies of an industrial air separation plant are solved. The results demonstrate that the simultaneous optimization of maintenance and operational tasks of the compressors favor the generation of better solutions in terms of total costs

Analysis of steady state Cryogenic Air Separation unit of Rourkela Steel Plant and simulation of Fixed Bed Adsorption Separation of Air

Atmospheric dry air contains approximately 78% nitrogen, 21% oxygen, and 1% argon plus low concentrations of noble gases like carbon dioxide, hydrocarbons and other impurities. An air separation unit divides atmospheric air into the three pure gaseous components (nitrogen, oxygen and argon). Further separation may be performed on some plants to produce other gases such as krypton, neon and xenon. Other gas components of atmospheric air, such as carbon dioxide, water vapour and hydrocarbons must be removed to ensure safety, product quality and efficient plant operation. Nitrogen, oxygen and argon are used by industry in large quantities and hence termed industrial gases. The current work aim is to simulate the cryogenic air separation unit including adsorber and cryogenic distillation. Simulation of absorber is carried out using ADSIM of Aspen Tech to remove carbon dioxide (CO2) and water vapour (H2O). The breakthrough curves of carbon dioxide (CO2) and water vapour on 5A molecular sieve and activated alumina respectively are found at different Reynolds number. The study helps to find out schedule time adsorber/desorber unit. ASPEN Plus simulator is used to simulate cryogenic air separation into nitrogen, oxygen and argon. The steady-state simulation results (purity) are compared to Rourkela steel plant real data

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

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.BMBF, 03SFK3X1, Verbundvorhaben SynErgie: Synchronisierte und energieadaptive Produktionstechnik zur flexiblen Ausrichtung von Industrieprozessen auf eine fluktuierende Energieversorgung. X1_Linde: Erforschung und Demonstration von Industrieprozessen und Produktionssystemen im Hinblick auf energetische Nachfrageflexibilitä

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

Techno-economic study of output-flexible light water nuclear reactor systems with cryogenic energy storage

This study explores whether a nuclear power plant can be combined with a cryogenic energy storage plant to allow the resultant facility to provide variable power to the grid. The study expands on previous literature by performing novel market-led system optimisation to best design the output profile of the plant to improve economic performance in the UK electricity grid. There are three key conclusions that emerge from this study. The current UK electricity market favours plant designs with rapid discharge rate. Provided that the capital cost expectations of the NuScale SMR are realised, strike prices of £55/MWh are sufficient to ensure a return on investment. However, the case for storage remains weak and only becomes viable in extreme spot market conditions

Efficient Nonlinear Optimization with Rigorous Models for Large Scale Industrial Chemical Processes

Large scale nonlinear programming (NLP) has proven to be an effective framework for obtaining profit gains through optimal process design and operations in chemical engineering. While the classical SQP and Interior Point methods have been successfully applied to solve many optimization problems, the focus of both academia and industry on larger and more complicated problems requires further development of numerical algorithms which can provide improved computational efficiency. The primary purpose of this dissertation is to develop effective problem formulations and an advanced numerical algorithms for efficient solution of these challenging problems. As problem sizes increase, there is a need for tailored algorithms that can exploit problem specific structure. Furthermore, computer chip manufacturers are no longer focusing on increased clock-speeds, but rather on hyperthreading and multi-core architectures. Therefore, to see continued performance improvement, we must focus on algorithms that can exploit emerging parallel computing architectures. In this dissertation, we develop an advanced parallel solution strategy for nonlinear programming problems with block-angular structure. The effectiveness of this and modern off-the-shelf tools are demonstrated on a wide range of problem classes. Here, we treat optimal design, optimal operation, dynamic optimization, and parameter estimation. Two case studies (air separation units and heat-integrated columns) are investigated to deal with design under uncertainty with rigorous models. For optimal operation, this dissertation takes cryogenic air separation units as a primary case study and focuses on formulations for handling uncertain product demands, contractual constraints on customer satisfaction levels, and variable power pricing. Multiperiod formulations provide operating plans that consider inventory to meet customer demands and improve profits. In the area of dynamic optimization, optimal reference trajectories are determined for load changes in an air separation process. A multiscenario programming formulation is again used, this time with large-scale discretized dynamic models. Finally, to emphasize a different decomposition approach, we address a problem with significant spatial complexity. Unknown water demands within a large scale city-wide distribution network are estimated. This problem provides a different decomposition mechanism than the multiscenario or multiperiod problems; nevertheless, our parallel approach provides effective speedup

NASA SBIR abstracts of 1991 phase 1 projects

The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

Modeling and optimization of process systems for unconventional technologies and feedstocks

In the present era, the petrochemical/chemical process industries must adapt to unconventional feedstocks and energy sources, in order to keep pace with increased competition, regulatory pressure, and changing markets. However, developing processes compatible with these changes requires deviating from traditional and accepted process design and operation paradigms. This dissertation addresses fundamental challenges related to this transition from three angles: incorporation of custom (and detailed) models into process design, integration of variable operation with process design, and optimization of transient process operations. The first part of the dissertation introduces a framework for modeling, simulation, and optimization of process flowsheets incorporating highly detailed physical models of important and complex process units, termed “multi-resolution flowsheets”. The framework relies on pseudo-transient continuation as a numerical method and allows for the robust optimization of large-scale process models. Several case studies demonstrate the method, including process flowsheets featuring both intensified (e.g., dividing-wall distillation column, multistream heat exchanger) and unconventional (e.g., quenched reactor, packed column for carbon capture) process units. Furthermore, these results reveal significant benefits of considering the added level of detail at the design stage. Finally, an avenue is presented to accelerate the convergence of the pseudo-transient method, which is especially important for the large-scale models considered. In the second part of the dissertation, the focus shifts to process design optimization for variable operation, or optimization under uncertainty. Here, I present a method for process design that considers the effect of uncertain physical parameters (assumed to follow continuous probability distributions), using a formulation that exploits the semi-infinite nature of dynamic optimization. I compare the method to traditional “scenario-based” approaches using both theoretical analyses and multiple case studies. In addition to demonstrating the effectiveness of the proposed method, these case studies also emphasize the importance of considering several practically relevant uncertainties during process design. The final part of the dissertation examines explicit consideration of process dynamics for operational optimization. First, I examine periodic (dynamically intensified) processes, which operate at a cyclic steady state. I present a pseudo-transient method for robust optimization of fully discretized dynamic process models, and I present an approach for implementing cyclic conditions based on their fundamental relation to material/energy recycle loops. Lastly, I propose a framework for optimal production scheduling in fast changing market situations. Towards this end, I show how data-driven dynamic models can represent the behavior of a set of scheduling-relevant (physical or latent) variables. A method is also given for executing scheduling calculations using these models, and the framework is demonstrated by considering the demand response operation of both simulated and real-world air separation units.Chemical Engineerin