Abstract
The term “energy efficiency” covers a wide scope and it is affected by a lack of clarity. To overcome this issue, quantitative measures should be defined and evaluated for each unit of product or process considered. These quantitative indicators are necessary to support and evaluate energy efficiency improvements in industry, by allowing to (i) monitor the energy performance, and (ii) perform benchmarking analyses with best available techniques or similar processes. The specific energy consumption (SEC), i.e., the amount of energy consumed per unit of product/output, is the most commonly used index. Because of the uncertain demand faced by companies, production processes run at a rate that can vary within a certain range, to which correspond a different utilization of plants. Energy efficiency investments can be categorized in accordance to how they affect the SEC: i.e., the first group of investments has the same effects for each production rate (e.g., replacement of dated electric motors with new technologies), while the other has different effects for different ranges of production rate (e.g., installation of an inverter). The present work proposes a novel decision model for supporting the evaluation of the more suitable energy efficiency investment in an industrial context where the demand is uncertain. A numerical example based on a case study from the aluminum industry is then proposed in order to highlight the relevance of the problem discussed and to evaluate the behavior of the models in different scenarios characterized by different load factors. From the results, it evinced that the return of the investment strongly depends on the range of production rate and, thus, on the demand variability.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)
Cited by
2 articles.
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