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Optimal Allocation of Photovoltaic in the Hybrid Power System using Knapsack Dynamic Programming

Surya A.S.a,b, Awater P.c, Marbun M.P.a, Hariyanto N.b

a PT PLN (Persero), Jakarta, Indonesia
b School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Indonesia
c Siemens AG, Erlangen, Germany

[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]© 2019 IEEE.Indonesia, which is represented by PLN as stated- owned electric utility company, commits to increase the share of renewable energy mix up to 23% in 2025. One way to reach this goal is the commitment to solar power generation. However, generation from photovoltaic has intermittency that dependent on sun irradiation, so the stability of power system might be affected in certain cases. The stability problem can be anticipated by using a hybrid power system with the composition of photovoltaic, battery, and diesel. Optimal power flow and N-1 contingency simulation is conducted to determine and compare locations and the capacity of hybrid power system. Furthermore the composition of hybrid power system is evaluated by an frequency stability simulation and the LCOE is calculated. The appropriate hybrid power system is selected by applying a knapsack dynamic programming approach. The result of the calculation is the optimal location of the hybrid power system with photovoltaic capacity as planned. This method is applied to Sumbawa power system as a case study.[/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]Hybrid power systems,Optimal allocation,Optimal power flows,Power system stability,Renewable energies,Smart grid,Stability of power system,Stability simulation[/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]cost,dynamic programming,hybrid power system,power system stability,smart grids[/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/ISGT-Asia.2019.8881331[/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]