Sensitivity analysis of line current variation model for representing the forecasting error of renewable generation under dynamic line ratings — considering a variation in meteorological conditions

For a high penetration of intermittent renewable energy sources, they may cause transmission-line congestion problems in power systems. In particular, among the current forecasting methodologies for renewable generation, an extremely large (but rare) forecasting error in the renewable generation inevitably occurs. In a previous paper, the authors developed a line current variation model to represent the forecasting error in the renewable output under the conventional worst-case meteorological conditions. In this paper, the method for evaluating the dynamic line ratings (DLRs) using the line current variation model is extended to conditions with the real-time meteorological parameters. Therefore, the applicability of the shape parameter γ in this model to various meteorological conditions is investigated. After it is investigated that the same value of γ can be applied to various meteorological conditions, the line current variation model is applied to actually measured meteorological data, resulting in a larger benefit due to the real-time DLRs from a power system operational viewpoint.