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首页> 外文会议>Recent advances in energy, environment and development >Lessons Learnt on Industrial Ecology as an Optimization Mechanism within the Multi-Dimensional Domain of Sustainable Development, Energy/Materials Saving and Environmental Preservation
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Lessons Learnt on Industrial Ecology as an Optimization Mechanism within the Multi-Dimensional Domain of Sustainable Development, Energy/Materials Saving and Environmental Preservation

机译：在可持续发展，能源/材料节约和环境保护的多维领域内，将工业生态学作为一种优化机制的经验教训

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Industrial Ecology Is a systemic/multidisciplinary discourse dedicated to the optimization of energy and material flows through an industrial domain, mapped as a network of processes that extract/modify natural resources, thus interconnected with the environment, where residues/wastes are also discharged. This optimization is examined in the present work by using energy/materials saving (E/M) and sustainable development (S) as main factors. In an attempt to investigate the relation between these factors, we set S as the dependent variable (output) and a composite index I, based on the weighted combination of E and M, as the independent variable (input). The optimal value lopt is found at the minimum value Smin of the objective function S(I), which consists of two conflict variables S1 and S2, based on the beneficial action of energy/materials saving and the flexibility decrease (due to sacrifice of degrees of freedom to obtain higher I-values, implying also higher compactness of the industrial processes network), respectively. Since the demand for energy/materials depends also on the level of S, which is changing in the time course, we should deal with an implicit function of the form f (S, E, M) = 0 rather than with an explicit function of the form S = f (E,M). Therefore, we can obtain an internal triangular relation between S, E, M, having a gravity center near the variable playing the most significant role. Nevertheless, we can reduce the generalized implicit function to its corresponding explicit form by setting the variable to be interconnected mostly with the strategic task as the depended one. Three case examples are presented to illustrate real situations, where S, E, M, correspond to a strategic target set a priori, respectively.
机译：工业生态学是一种系统/多学科的论述，致力于优化通过工业领域的能源和物质流，将其映射为提取/修改自然资源的过程网络，从而与环境互连，其中还排放了残留物/废物。通过使用能源/材料节约（E / M）和可持续发展（S）作为主要因素，对本次优化进行了研究。为了研究这些因素之间的关系，我们将S设为因变量（输出），并将基于E和M的加权组合的综合指数I设为自变量（输入）。最佳值lopt在目标函数S（I）的最小值Smin上找到，该函数由两个冲突变量S1和S2组成，这是基于节省能源/材料和降低灵活性（由于牺牲度而产生的）的作用获得更高的I值的自由，分别意味着工业过程网络的更高的紧凑性。由于对能源/材料的需求还取决于随时间变化的S的水平，因此我们应该处理形式为f（S，E，M）= 0的隐式函数，而不是形式为的显式函数。形式S = f（E，M）。因此，我们可以获得S，E，M之间的内部三角关系，其重心在变量附近起着最重要的作用。尽管如此，我们可以通过将变量设置为主要与战略任务相关来将其简化为相应的显式形式。给出三个案例以说明实际情况，其中S，E，M分别对应于先验设置的战略目标。

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