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Optimal Placement of Energy Storage with Synthetic Inertia Control on a Grid with High Penetration of Renewables using Mean-Variance Mapping Optimization
Israjuddina,b,c, Hariyanto N.b, Chao-Yuan L.c, Chih-Wen L.c
a PT PLN (Persero), Jakarta, Indonesia
b Bandung Institute of Technology, School of Electrical Engineering and Informatics, Bandung, Indonesia
c National Taiwan University, Department of Electrical Engineering, Taipei, Taiwan
[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.Modern power systems have evolved, from classical type of synchronous generation to more distributed non-synchronous generation with power electronic-based, some country is dealing with high penetration of renewable energy sources (RESs) such as photovoltaic and wind turbines. However, this new generation model does not have natural inertia and damping properties, which is a classic feature of synchronous machines. The lack of system inertia in such power system has mainly two implications on system frequency stability, namely: higher frequency deviations (nadirs/zeniths); and larger ROCOF, which results in possible tripping of grid components. Many researchers have shown how to use inverters and energy storages with synthetic inertia control algorithms; by then, it will be recognized as synchronous generators by power grids, maintain and improve frequency stability. This paper aims to show the process of identifying the optimal placement of energy storage with SIC in order to improve frequency stability in a high RESs penetration power system using Mean-Variance Mapping Optimization (MVMO) algorithm.[/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]Damping property,Grid components,Higher frequencies,Mapping optimization,MVMO,Optimal placements,Renewable energy source,Synchronous machine[/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]energy storage,frequency stability,MVMO,renewable energy sources,synthetic inertia control[/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/APPEEC45492.2019.8994698[/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]