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Selecting tools for renewable energy analysis in developing countries: An expanded review
Indra Al Irsyad M.a,b, Halog A.B.a, Nepal R., Koesrindartoto D.P.d
a School of Earth and Environmental Science, University of Queensland, Brisbane, Australia
b Ministry of Energy and Mineral Resources, Jakarta, Indonesia
c Massey Business School, Massey University, Palmerston North, New Zealand
d School of Business and Management, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2017 al Irsyad, Halog, Nepal and Koesrindartoto.Renewable energy planners in developing countries should be cautious in using analytical tools formulated in developed countries. Traditional energy consumption, economic and demography transitions, high-income inequality, and informal economy are some characteristics of developing countries that may contradict the assumptions of mainstream, widely used analytical tools. In this study, we synthesize the debate in previous review studies on energy models for developing countries and then extend the scope of the previous studies by highlighting emerging methods of system thinking, life cycle thinking, and decision support analysis. We then discuss how these tools have been used for renewable energy analysis in developing countries and found out that not all studies are aware of the emerging critical issues in developing countries. We offer here a guidance to select the most appropriate analytical tool, mainly when dealing with energy modeling and analysis for developing countries. We also suggest potential future improvements to the analytical tool for renewable energy modeling and analysis in the developing countries.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Bottom up approach,Decision supports,Life cycle thinking,Low-carbon transitions,System thinkings,Top down approaches[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Bottom-up approach,Decision support analysis,Developing countries,Life cycle thinking,Low carbon transition,System thinking,Top-down approach[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The authors acknowledge the funding support from the Indonesia Endowment Fund for Education (LPDP), Ministry of Finance-the Republic of Indonesia (Grant no: 20141122092191); and the research grant from the School of Earth and Environmental Sciences at the University of Queensland.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.3389/fenrg.2017.00034[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]