مقاله انگلیسی رایگان در مورد استفاده از متد تصمیم‌ گیری ترکیبی در انتخاب تکنولوژی های انرژی‌ تجدیدپذیر – الزویر ۲۰۲۲

مقاله انگلیسی رایگان در مورد استفاده از متد تصمیم‌ گیری ترکیبی در انتخاب تکنولوژی های انرژی‌ تجدیدپذیر – الزویر ۲۰۲۲

 

مشخصات مقاله
ترجمه عنوان مقاله انتخاب فناوری‌ های انرژی‌های تجدیدپذیر با استفاده از روش تصمیم‌ گیری چند معیاره ترکیبی ذهنی و عینی
عنوان انگلیسی مقاله The selection of renewable energy technologies using a hybrid subjective and objective multiple criteria decision making method
انتشار مقاله سال ۲۰۲۲
تعداد صفحات مقاله انگلیسی ۱۸ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – Master Journal List – JCR
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
۹٫۶۰۲ در سال ۲۰۲۰
شاخص H_index ۲۲۵ در سال ۲۰۲۲
شاخص SJR ۲٫۰۷۰ در سال ۲۰۲۰
شناسه ISSN ۰۹۵۷-۴۱۷۴
شاخص Quartile (چارک) Q1 در سال ۲۰۲۰
فرضیه ندارد
مدل مفهومی دارد
پرسشنامه ندارد
متغیر ندارد
رفرنس دارد
رشته های مرتبط مهندسی کامپیوتر – مهندسی انرژی – مهندسی معدن – مدیریت
گرایش های مرتبط مهندسی نرم افزار – هوش مصنوعی – فناوری انرژی – انرژی های تجدیدپذیر
نوع ارائه مقاله
ژورنال
مجله  سیستم های خبره با برنامه های کاربردی – Expert Systems with Applications
دانشگاه Department of Earth Science and Engineering, Imperial College London, UK
کلمات کلیدی فناوری های انرژی های تجدیدپذیر – تصمیم گیری چند معیاره (MCDM) – عدم قطعیت – صنعت معدن
کلمات کلیدی انگلیسی Renewable energy technologies – Multiple criteria decision making (MCDM) – Uncertainty – Mining industry
شناسه دیجیتال – doi
https://doi.org/10.1016/j.eswa.2022.117839
کد محصول e16769
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
Abstract
۱٫ Introduction
۲٫ Literature review
۳٫ Research framework
۴٫ MCDM methodology
۵٫ Application of the method developed to the selection of renewable energy technologies in the mining industry
۶٫ Conclusions
CRediT authorship contribution statement
Declaration of Competing Interest
Acknowledgement
References

بخشی از متن مقاله:

Abstract

     The use of renewable energy technologies is a key factor for sustainable development but their selection from several alternatives is a difficult task that relies on the careful assessment of relevant criteria. While Multiple Criteria Decision Making (MCDM) methods have been used successfully in various renewable energy technology selection problems, the decision process becomes more challenging when preferential judgements are made on the basis of non-homogenous and imprecise input data, and when there is uncertainty due to disparities among decision makers. This paper presents a hybrid MCDM method capable of overcoming these problems by taking into account quantitative and qualitative data under a probabilistic environment in the context of group decision making. In this method, qualitative data is fuzzified and used along with quantitative data to develop a hybrid model. A coefficient factor allows decision makers to vary the weight of each quantitative model so that the resultant criteria weights and overall alternatives’ scores consider both subjective considerations and objective information. An example is presented to showcase the usability of the method developed for ranking and evaluating renewable energy technologies in the mining industry. In addition, the impact of different coefficient factors on the final results was assessed by means of sensitivity analysis. The results indicate that the method developed is able to minimise the loss of valuable objective information, caused by the subjective bias of qualitative weights during the evaluations, by adjusting the coefficient factors of the hybrid model during the calculations.

Introduction

     Energy-generating technologies that depend on non-renewable fossil fuels result in significant environmental challenges, such as increasing greenhouse gas (GHG) emissions, which lead to climate change (Disli et al., 2016, Li et al., 2020). In response to these challenges, it is important to better exploit renewable energy technologies (e.g. wind and solar), which are low-cost, clean and sustainable (Cunden et al., 2020, Dincer, 2000).

     The selection of renewable energy technologies is a complex and multidisciplinary problem that mainly refers to the performance of the technologies concerning multiple criteria such as environmental, social, technical and economic (Wu et al., 2018). In order to evaluate holistically and select the technologies that have a higher performance appropriately, decision makers need to have methodological tools that incorporate both quantitative and qualitative analyses of the multiple criteria. Decision makers should, therefore, make use of the best tools available to evaluate the performance criteria of renewable energy technologies. Choosing the best renewable energy technology to use among various alternatives considering conflicting criteria is thus considered a Multiple Criteria Decision Making (MCDM) problem (Büyüközkan & Güleryüz, 2017).

Conclusions

     A hybrid MCDM method was proposed and was applied to the selection of renewable energy technologies in the mining industry, which faces an increase in energy demand as high grade ores are depleted and the demand for metals and minerals, including those required for renewable energy technologies, increases. The large scale of mining operations makes it very important to consider renewable energy options in order to contribute to the sustainability of the operations.

     Three renewable technology alternatives, namely onshore wind, concentrated solar power, and solar photovoltaic, were assessed taking into account both subjective considerations and objective information with respect to five sustainability criteria. The selected criteria were potential total power generation, GHG emissions, area requirement, levelised energy cost, and prospective jobs creation. An objective weight was obtained using data compiled from the literature, whereas a subjective weight was obtained from the judgements and preferences of four experts. The proposed method was then employed to compute the criteria weights and the alternatives’ scores.

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