Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/244026 
Erscheinungsjahr: 
2020
Quellenangabe: 
[Journal:] Energy Reports [ISSN:] 2352-4847 [Volume:] 6 [Publisher:] Elsevier [Place:] Amsterdam [Year:] 2020 [Pages:] 216-227
Verlag: 
Elsevier, Amsterdam
Zusammenfassung: 
Nowadays in India the renewable energy sources are continuum growing to accommodate the current demands of energy. Therefore, for an effective use of this energy, a careful and critical analysis is required. As per literature review, India was reported having a massive potential as superpower source in terms of wind energy In the present research, an effort has been carried out to explore various decision making approaches such as TOPSIS, VIKOR, and Fuzzy analysis, to subsequently rank various Indian states with respect to their wind energy potential. In this perspective, potentiality indices have been found on the justification of five significant factors that influence the effective use of wind energy and then a classification has been proposed. It was found that the wind power density is the most significant parameter while the technical expertise has been found as the least significant among identified parameters. The results presented here indicates that among all alternative states of India, Tamilnadu and Maharashtra have the maximum potential to tap the wind energy potential. This study will act as a guide for various government agencies to re-evaluate and re-formulate their energy policies as well as will help various investors (under the 'Make in India' campaign) orientated to do business here, to take a well informed decision. The present study also provides a way to make strong policies, in the area of high wind energy potential, in order to maximize the use of renewable source of energy which allows to tackle the societal need and poverty.
Schlagwörter: 
Wind energy potential
Fuzzy logic
Hybrid MADM
Policy decision-making
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by-nc-nd Logo
Dokumentart: 
Article
Erscheint in der Sammlung:

Datei(en):
Datei
Größe
891.77 kB





Publikationen in EconStor sind urheberrechtlich geschützt.