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[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]© 2020 IEEE.In the near future, Indonesian electric power systems will be strongly influenced by the penetration of Distributed Generation (DG) along with increasing electricity demand. This growth may cause capacity congestion, which is traditionally responded with new infrastructure investment by the utility. Alternatively, investment of DG has the potential to defer traditional investment. It also comes with some technical benefits. In distribution network planning, the suitable of investment decision must fulfil the economic (funding risk) and reliability (operational risk) criteria. Planning engineers have to deal with uncertainty of demand increase, financial risk, and ways to determine the timing, location, size and types of investment. This paper introduces DG (both non-renewable and renewable) benefits as an option to defer traditional investment using Real Option Analysis in radial distribution network. This combines two economical approach: Return per Risk Index (RRI) and Real Option Value (ROV). The uncertain conditions are simulated with Monte Carlo. Furthermore, the optimal power flow gives an assessment of the best investment option using DIgSILENT. It is found that RRI and ROV of gas internal combustion engine (ICE) power plant investment is higher (least risky investment) compared to Battery Energy Storage System (BESS) and traditional investment, respectively. This paper has shown that Real Option Analysis may provide flexibility options (pictured in decision tree and decision area) for utility in order to make decision on future investment, including the deferral of traditional investment while obtaining technical benefits as DG penetration impact as well.[/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]Battery energy storage systems,Distribution network planning,Electricity demands,Infrastructure investment,Investment decisions,Power plant investment,Radial distribution networks,Real option analysis[/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]Deferral investment decision,Distributed generation,Monte carlo,Optimal power flow,Real option analysis,Return per risk[/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][/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/10.1109/ICT-PEP50916.2020.9249846[/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]