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The applicability of BFA and LCCA to analyze reliability of power system
Nugraha H.a, Arifianto Y.a, Sinisuka N.I.a
a School of Electrical Engineering and Informatics, Institut Teknologi 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]Bacteria Foraging Algorithm (BFA) has been widely implemented in power engineering. This algorithm is emulated from Escherichia coli bacteria’s ability in finding nutrients in the human body. The intelligent search of bacteria is used to find the position that produces the maximum fitness value. The positions of each bacterium describe the status of the generation system and the resulting fitness value is its probability. The generation system states were visited included a failure state (status which causes load curtailment or loss of load). When the high probability failure states are obtained, the reliability indices can be calculated such as Loss of Load Probability (LOLP), Loss of Load Expectation (LOLE) and Expected Energy Not Supplied (EENS). The success of BFA measured from its ability to find the dominant failure state because the more we found it, the reliability index is expected to be closer to the actual values. In order to determine the lowest long-term cost of ownership with low risk of power generation investment, it is required to do next evaluation ‘is the new investment or improvement needed or not?’ based on reliability indices of power system and Equivalent Availability Factor (EAF) and Equivalent Force Outage Rate (EFOR) of power generation. The new approach or model is proposed as a tool to make decision for new investment, improvement or not doing anything. The new model is included Life Cycle Cost Analysis (LCCA), Reliability & Maintainability (R&M) calculation and BFA. To simulate the model, calculation of BFA of Muarakarang-Gandul 1 Power System (islanding system which part of Jawa-Bali-Madura grid in Indonesia) and calculation of LCCA of Lontar Coal Fired Steam Power Plant 3×315 MW (CFSPP) was applied. The results tell us that calculation of BFA and LCCA were applicable to analyze reliability of power system to get optimum cost, risk and performance. At the scenario 2, even additional investment is decided but it got the lowest long-term cost of ownership with low risk. More deeply researches in this field are still interesting. © 2014 IEEE.[/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]Bacteria foraging algorithms,Bacteria foraging optimization algorithms,Escherichia coli bacteria,Expected energy not supplied,Life-cycle cost analysis,Loss of load probabilities (LOLP),Power generation investments,Power System[/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]Bacteria Foraging Optimization Algorithm (BFA),Life Cycle Cost Analysis (LCCA),Power System[/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/RAMS.2014.6798474[/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]