FRRo - I+D+i - Artículos en Revistas

Permanent URI for this collectionhttp://48.217.138.120/handle/20.500.12272/1297

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Author: search.filters.author.Scenna, Nicolás JoséSubject: search.filters.subject.economic optimization

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    An optimization model for evaluating the economic impact of availability and maintenance notions during the synthesis and design of a power plant
    (Elsevier, 2017-01-27) Godoy, Ezequiel; Benz, Sonia Judith; Scenna, Nicolás José
    In this paper, we introduce an optimization strategy in order to comprehensively quantify the impact of availability and maintenance notions during the early stages of synthesis and design of a new natural gas combined cycle power plant. A detailed state-space approach is thoroughly discussed, where influence of maintenance funds on each component’s repair rate is directly assessed. In this context, analysis of the reliability characteristics of the system is centered at two designer-adopted parameters, which largely influence the obtained results: the number of components which may fail independently at the same time, and the number of simultaneous failure/repair events. Then, optimal solutions are evaluated as the availability-related parameters and the amount of resources assigned for maintenance actions are varied across a wide range of feasible values, which enable obtaining more accurate and detailed estimations of the expected economic performance for the project when compared with traditional economic evaluation approaches.
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    A NGCC power plant with a CO2 post-combustion capture option : optimal economics for different generation/capture goals
    (Elsevier, 2013-11-13) Mores, Patricia Liliana; Godoy, Ezequiel; Mussati, Sergio Fabián; Scenna, Nicolás José
    Fossil fuel power plants are one of the major sources of electricity generation, although invariably release greenhouse gases. Due to international treaties and countries regulations, CO2emissions reduction is increasingly becoming key in the generators’ economics. NGCC power plants constitute a widely used generation technology, from which CO2capture through a post-combustion and MEA absorption option constitutes a technological challenge due to the low concentration of pollutants in the flue gas and the high energy requirements of the sequestration process. In the present work, a rigorous optimization model is developed to address the design and operation of power plants coupled to capture systems. The equations-oriented modeling strategy here utilized can address greenfield designs in which design and operating variables are simultaneously optimized, in order to ensure that the system will be able to meet process requirements at minimum cost. Then, an analysis of the electricity cost, CO2avoidancecost, energy penalties, as well as the optimal values of decision variables is thoroughly pursued. Different economic tradeoffs are comprised at the optimal solutions for the joint project, as given by the different discrete and continuous decisions that the designer needs to weight in order to achieve the desired generation and capture goals, including the number of parallel capture trains, the inherent efficiency of each recovery unit, and the overall emissions reduction rate. In this context, the joint optimization of the NGCC power plant with the amine-based capture option results in a novel configuration where 731 MW are optimally generated for supplying both the external demand and the capture plant energy requirements, and achieving an overall CO2emissions reduction rate of 82.1% by means of a three capture trains arrangement, where 13.4% of the flue gas stream is bypassed and 94.8% of the CO2gets recovered at each unit. This new generation/capture project features optimal values of its economic performance indicators, with an avoidance cost of 81.7 US$ per tonne of CO2 captured, which can Ministerio de Educación y Deportes Universidad Tecnológica Nacional Facultad Regional Rosario Universidad Tecnológica Nacional – Facultad Regional Rosario Zeballos 1341, Rosario, Santa Fe, Argentina only be secured by simultaneously optimizing the design and operating variables of both systems on a start-of-the-art optimization algorithm.