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

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.

Chemical characterization of emissions from a municipal solid waste treatment plant

Gaseous emissions are an important problem in municipal solid waste (MSW) treatment plants. The sources points of emissions considered in the present work are: fresh compost, mature compost, landfill leaks and leachate ponds. Hydrogen sulphide, ammonia and volatile organic compounds (VOCs) were analysed in the emissions from these sources. Hydrogen sulphide and ammonia were important contributors to the total emission volume. Landfill leaks are significant source points of emissions of H2S; the average concentration of H2S in biogas from the landfill leaks is around 1700 ppmv. The fresh composting site was also an important contributor of H2S to the total emission volume; its concentration varied between 3.2 and 1.7 ppmv and a decrease with time was observed. The mature composting site showed a reduction of H2S concentration (<0.1 ppmv). Leachate pond showed a low concentration of H2S (in order of ppbv). Regarding NH3, composting sites and landfill leaks are notable source points of emissions (composting sites varied around 30–600 ppmv; biogas from landfill leaks varied from 160 to 640 ppmv). Regarding VOCs, the main compounds were: limonene, p-cymene, pinene, cyclohexane, reaching concentrations around 0.2–4.3 ppmv. H2S/NH3, limonene/p-cymene, limonene/cyclohexane ratios can be useful for analysing and identifying the emission sources.

Presence of Siloxanes in the Biogas of a Wastewater Treatment Plant Separation in Condensates and Influence of the Dose of Iron Chloride on its Elimination

The siloxanes present in the biogas produced during anaerobic digestion damage the mechanism of cogeneration equipment and, consequently, negatively affect the energy valorization process. For this reason, the detection and elimination of these silicon-derived chemical compounds are a priority in the management of cogeneration facilities. In this regard, the objectives of this paper are, firstly, to characterize the siloxanes in the biogas and, secondly, to qualitatively evaluate the influence of the dose of iron chloride on its elimination. The research was performed at the Rincón de León Wastewater Treatment Plant (Alicante, Spain). The outflow biogas of the digesters and of the pressurized gasometers was sampled and analyzed. The results obtained made it possible to demonstrate, firstly, the absence of linear siloxanes and that, of the cyclic siloxanes, the predominant type was decamethylcyclopentasiloxane, and, secondly, that the addition of iron chloride in the digesters significantly reduces the siloxane content in the biogas. Additionally, it was demonstrated that the process of compression of the biogas, with the elimination of condensates, also produces significant reductions in the concentration of siloxanes in the biogas.

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.