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Optimizing Unit Commitment Schemes for Variable RES Power Plant Integration in Microgrid Systems
Rendroyoko I.a, Sinisuka N.I.a, Koesrindartoto D.P.a
a Institute Technology of Bandung, School of Electrical and Informatics Engineering, 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]© 2019 IEEE.With the development of technology, renewable energy sources (RES) have been developed on islands and electricity systems in isolated areas, including RES which have intermittent characteristics. Those variable renewable energy power plants are operated by integration into existing power systems. The rapid increase of variable RES power plants integration into electricity network has given effect on the development of unit commitment (UC) schemes which aimed to ensure the operation of electric power systems stability, resilience, and with minimum operating cost can be maintained. To achieve these goals, it is necessary to develop optimization methods to be applied to the UC scheme for the island’s electricity system.This paper discusses the most suitable optimization methods for the inclusion of renewable energy power generation using a unit commitment scheme in the microgrid electricity system. The methods here are a hybrid technique which combines enhanced priority list method for accurate generation unit scheduling and genetic algorithm (GA) technique for an optimum search for the lowest operational cost. The capacity of generating units to operate per capability segment is also taken into account in operating scheduling and affects the number of iterations in the operation of genetic algorithm techniques. This method has been simulated on the Timor electricity system, which is a growing power system and has an intermittent RES power plant. Implementation in other locations with other variable RES could provide better results. This method is an enrichment of hybrid techniques developed in previous studies. This enrichment is carried out on the calculation by segmenting the ability of generating units.[/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]Optimization method,Power system stability,System integration,Unit-commitment,Variable renewable energies[/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]genetic algorithm,low operating cost,optimization method,power system stability,system integration,unit commitment,variable renewable energy sources[/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/ICHVEPS47643.2019.9011115[/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]