Adaptation of the ascendency theory to industrial systems

作者: Monica Carvalho , Luis M. Serra

DOI: 10.1007/S40430-019-2051-X

关键词: ExergyProcess engineeringThermoeconomicsElectric power systemEnergy transformationEfficient energy useThermal efficiencyRankine cycleAscendencyComputer science

摘要: Growth and development of ecosystems are subject to restrictions. Besides exergy, other properties, such as ascendency, have been described goal functions that can inform about the health synthesize information energy matter flows in relation an ideal theoretical state. Ascendency is index quantifies both growth degree organization ecosystem, which several subsystems interact with mass flows. quantified terms exchanges among different constituting ecosystem. Its value increases when activity ecosystem (amount increase) evolves a higher complexity its structure (level integration subsystems). Exergy provides quality therefore very appropriate for evaluating thermodynamic efficiency conversion processes. Growing concerns stimulated techniques analysis, design, diagnosis complex systems based on second law thermodynamics. In this context, set methodologies called thermoeconomics was created, aimed at cost allocation (economic, thermodynamic, or environmental) optimization thermal concepts system operation, often use exergy. Thermoeconomic analysis interaction components how resources distributed throughout internal system. Herein formulation ascendency adapted industrial using exergy quantity interest, employing productive obtained from thermoeconomic describe production process then applied simple power Rankine cycle study connection between (thermodynamic) “growth” “development” Four configurations interconnection levels equipment were studied, maintaining final product (net power) entire constant, comparison purposes. Moreover, turbine efficiencies also analyzed, fixed constant net produced, obtain comparable results. It verified case steam plants cycle, increase complexity, total plant well potential improvement. When cases same level (same structure), compared, configuration highest presents better optimization.

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