scholarly journals Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact

2015 ◽  
Vol 88 ◽  
pp. 335-346 ◽  
Author(s):  
Joan Carreras ◽  
Dieter Boer ◽  
Gonzalo Guillén-Gosálbez ◽  
Luisa F. Cabeza ◽  
Marc Medrano ◽  
...  
2018 ◽  
Vol 70 ◽  
pp. 01012
Author(s):  
Dominika Matuszewska ◽  
Marta Kuta ◽  
Jan Górski

This paper details the development of a systematic methodology to integrated life cycle assessment (LCA) with thermo-economic models and to thereby identify the optimal exploitation schemes of geothermal resources. Overall geothermal systems consist of a superstructure of geothermal exploitable resources, a superstructure of conversion technology and multiple demand profiles for Swiss city. In this paper, an enhanced geothermal system has been chosen as exploitable resources. The energy conversion technology used in modelling is an organic Rankine cycle, which can be used to supply heat and electricity. In the Swiss case four demand profiles periods are considered: summer, interseason, winter and extreme winter, the city Nyon serving for the example case study. The multi-objective optimization system, that uses an evolutionary algorithm, is employed to determine the optimal scheme for some of the prepared models, with exergy efficiency and environmental impact as objectives.


Author(s):  
Christian Buschbeck ◽  
Larissa Bitterich ◽  
Christian Hauenstein ◽  
Stefan Pauliuk

Regional food supply, organic farming, and changing food consumption are three major strategies to reduce the environmental impacts of the agricultural sector. In the German Federal State of Baden-Württemberg (population: 11 million), multiple policy and economic incentives drive the uptake of these three strategies, but quantitative assessments of their overall impact abatement potential are lacking. Here, the question of how much food can be produced regionally while keeping environmental impacts within political targets is tackled by comparing a scenario of maximum productivity to an optimal solution obtained with a multi-objective optimization (MO) approach. The investigation covers almost the entirety of productive land in the state, two production practices (organic or conventional), four environmental impact categories, and three demand scenarios (base, vegetarian, and vegan). We present an area-based indicator to quantify the self-sufficiency of regional food supply, as well as the database required for its calculation. Environmental impacts are determined using life cycle assessment. Governmental goals for reducing environmental impacts from agriculture are used by the MO to determine and later rate the different Pareto-efficient solutions, resulting in an optimal solution for regional food supply under environmental constraints. In the scenario of maximal output, self-sufficiency of food supply ranged between 61% and 66% (depending on the diet), and most political targets could not be met. On the other hand, the optimal solution showed a higher share of organic production (ca. 40%–80% com¬pared to 0%) and lower self-sufficiency values (between 40% and 50%) but performs substantially better in meeting political targets for environmental impact reduction. At the county level, self-sufficiency varies between 2% for densely populated urban districts and 80% for rural counties. These results help policy-makers benchmark and refine their goalsetting regarding regional self-sufficiency and environmental impact reduction, thus ensuring effective policymaking for sustainable community development.


2016 ◽  
Vol 130 ◽  
pp. 506-518 ◽  
Author(s):  
Joan Carreras ◽  
Carlos Pozo ◽  
Dieter Boer ◽  
Gonzalo Guillén-Gosálbez ◽  
Jose A. Caballero ◽  
...  

2011 ◽  
Vol 121-126 ◽  
pp. 2223-2227 ◽  
Author(s):  
Chun Sheng Zhu ◽  
Qi Zhang ◽  
Fan Tun Su ◽  
Hong Liang Ran

By weighing reliability, maintainability, availability and life-cycle cost of equipment which are influenced by testability,the testability indexes of system level BIT are determined on the basis of maximum system reliability & maintainability and minimum the life-circle cost. The influence mathematical models of system reliability, maintainability, availability and life-circle cost are established. According to these mathematical models, the multi-objective optimization model of system-level BIT testability indexes is established. The multi-objective optimization model is solved using Non-dominated Sorting Genetic Algorithm II, and the validity of the multi-objective optimization model is proved through an example.


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