A New Standalone Tool for DC-Equivalent Network Generation and GIC Calculation in Power Grids With Multiple Voltage Levels

Space Weather phenomena pose a major socio-economic threat due, in part, to the vulnerability of power network transformers to geomagnetically induced currents (GIC). In 1985, Lehtinen and Pirjola (LP) provided a method to calculate GICs in a single-voltage-level network. The need to account for low...

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Detalles Bibliográficos
Autores: Marsal, Santiago, Torta, Joan Miquel, Canillas-Pérez, Victoria, Curto, Juan José
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universitat Ramon Llull (URL)
Repositorio:DAU Arxiu Digital de la Universitat Ramon Llull
OAI Identifier:oai:dau.url.edu:20.500.14342/5483
Acceso en línea:http://hdl.handle.net/20.500.14342/5483
https://doi. org/10.1029/2021SW002984
Access Level:acceso abierto
Palabra clave:Geomagnetically Induced Currents
Descripción
Sumario:Space Weather phenomena pose a major socio-economic threat due, in part, to the vulnerability of power network transformers to geomagnetically induced currents (GIC). In 1985, Lehtinen and Pirjola (LP) provided a method to calculate GICs in a single-voltage-level network. The need to account for lower voltages has caused the proliferation of GIC risk assessments applied to power grids with multiple voltages. We hereby present a tool to systematically generate the direct currents (DC)-equivalent of a multiple-voltage-level network. The LP and Nodal Admittance Matrix methods are the most popular schemes to compute the GIC from the resulting equivalent network by solving the circuit laws for the earthing current or the voltage at each node, respectively. A new scheme is presented here that solves the circuit laws for the current flowing between the bus nodes and the neutral point which, unlike LP, requires no (infinite-resistance) earth connections for the buses. The number of equations/unknowns of the resulting GIC matrix equation is reduced compared to the traditionalmethods, thus optimizing the computational cost -an advantage that becomes important for large networks-, while keeping a good condition of the design matrix associated with the inversion. Examples are shown for different test cases and a standalone computationally efficient code is provided.