Yashwant Sawle

Dr. Yashwant Sawle

Madhav Institute of Technology & Science, Gwalior, India
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 February 2023 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
MTM. Thirunavukkarasu
M. Thirunavukkarasu
Yashwant SawleYashwant Sawle
Yashwant Sawle
HLHimadri Lala
Himadri Lala

1 January 2018 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
Yashwant SawleYashwant Sawle
Yashwant Sawle
SGS.C. Gupta
S.C. Gupta
ABAashish Kumar Bohre
Aashish Kumar Bohre

1 April 2018 in Renewable Energy
Verified
Journal Article
Closed access
Yashwant SawleYashwant Sawle
Yashwant Sawle
SGS.C. Gupta
S.C. Gupta
ABAashish Kumar Bohre
Aashish Kumar Bohre

7 June 2016 in Cogent Engineering
Verified
Journal Article
Open access
Yashwant SawleYashwant Sawle
Yashwant Sawle
SGS.C. Gupta
S.C. Gupta
ABAashish Kumar Bohre
Aashish Kumar Bohre

1 June 2017 in Energy Procedia
Verified
Journal Article
Open access
Yashwant SawleYashwant Sawle
Yashwant Sawle
SGS.C. Gupta
S.C. Gupta
ABAashish Kumar Bohre
Aashish Kumar Bohre

11 February 2021 in IEEE Access
Verified
Journal Article
Open access
Yashwant SawleYashwant Sawle
Yashwant Sawle
SJSiddharth Jain
Siddharth Jain
SBSanjana Babu
Sanjana Babu
ANAshwini Ramachandran Nair
Ashwini Ramachandran Nair
Baseem KhanBaseem Khan
Baseem Khan
Nowadays, microgrids with hybrid renewable energy sources are increasing, and it is a promising solution to electrify remote areas where distribution network expansion is not feasible or economical. This study aims to find an ideal hybrid system grounded on solar, wind, diesel, biomass, hydro, and battery. This study utilizes the hybrid optimization model for electric renewable (HOMER) software to size the important components, perform technical, financial evaluation, renewable factor, estimate the harmful emissions, and sensitivity analysis. For optimum system selection, the lowest cost of energy is used as the criteria. Four different configurations of renewable energy sources are analyzed and found PV-WT-MH-CT-BT-DG-BG is the most feasible hybrid system amongst all configurations. The proposed PV-WT-MH-CT-BT-DG-BG hybrid system is more economic as the lowest cost of energy 0.196$, low operating cost 36,184$, low net present cost 831,217$. Also, this hybrid system is more environmentally friendly as it has less emission and a high renewable factor of 81.2%.