Dynamic Thermal Rating (DTR) monitors the temperatures of conductors, or uses weather and load forecasting to estimate their future trend, in order to calculate the actual capacity of a transmission line. By fully exploiting the real performances of conductors corresponding to the current weather conditions, DTR provides Transmission System Operators (TSOs) with additional dispatching flexibility and helps decision-making in case of grid congestions, especially in terms of the amount and timing of required re-dispatching procedures. For this reason, DTR is increasingly used for security assessment and for the reliable operation of power systems. Recently the scientific literature is showing growing interest in applying probabilistic methods to weather-based DTR procedures, in order to account for the stochastic nature of meteorological parameters. In fact, it is evident that the weak point of predicting the ampacity of a transmission line for the next hours is the accuracy of weather forecasting. This paper suggests that the impact of weather uncertainty on the Dynamic Thermal Rating of a transmission line can be assessed through a Monte Carlo technique, used to generate weather scenarios whose Probability Distribution Functions (PDFs) have been carefully pre-tuned, for each meteorological parameter, according to the actual weather forecasting errors made in the proximity of the line. The weather scenarios so obtained are then processed by a thermo-mechanical model of the transmission line, in order to evaluate the impact of weather uncertainty on the confidence interval of thermal and mechanical outputs (conductor's temperature, tensions, sags). This approach is widely discussed and compared to the conventional method of simply modeling weather quantities with predefined Gaussian PDFs. Afterwards, it is applied to test the robustness of a deterministic DTR procedure developed in the last years by the authors. The DTR procedure under test combines the CIGRE thermal model of conductors and a complex multi-span mechanical model of a transmission line; in fact, it takes into account the mechanical interaction between spans, due to the possible rotation of strings of insulators, as well as that the temperature of conductors can vary span by span, for different weather conditions. Several case studies are discussed, based on weather measures collected near the same overhead lines on which the Italian TSO is obtaining significant benefits from the above-mentioned DTR procedure, especially in terms of increased amount of dispatchable wind energy.

The possible impact of weather uncertainty on the Dynamic Thermal Rating of transmission power lines: A Monte Carlo error-based approach

Poli, Davide
Primo
;
Pelacchi, Paolo;Lutzemberger, Giovanni;
2019-01-01

Abstract

Dynamic Thermal Rating (DTR) monitors the temperatures of conductors, or uses weather and load forecasting to estimate their future trend, in order to calculate the actual capacity of a transmission line. By fully exploiting the real performances of conductors corresponding to the current weather conditions, DTR provides Transmission System Operators (TSOs) with additional dispatching flexibility and helps decision-making in case of grid congestions, especially in terms of the amount and timing of required re-dispatching procedures. For this reason, DTR is increasingly used for security assessment and for the reliable operation of power systems. Recently the scientific literature is showing growing interest in applying probabilistic methods to weather-based DTR procedures, in order to account for the stochastic nature of meteorological parameters. In fact, it is evident that the weak point of predicting the ampacity of a transmission line for the next hours is the accuracy of weather forecasting. This paper suggests that the impact of weather uncertainty on the Dynamic Thermal Rating of a transmission line can be assessed through a Monte Carlo technique, used to generate weather scenarios whose Probability Distribution Functions (PDFs) have been carefully pre-tuned, for each meteorological parameter, according to the actual weather forecasting errors made in the proximity of the line. The weather scenarios so obtained are then processed by a thermo-mechanical model of the transmission line, in order to evaluate the impact of weather uncertainty on the confidence interval of thermal and mechanical outputs (conductor's temperature, tensions, sags). This approach is widely discussed and compared to the conventional method of simply modeling weather quantities with predefined Gaussian PDFs. Afterwards, it is applied to test the robustness of a deterministic DTR procedure developed in the last years by the authors. The DTR procedure under test combines the CIGRE thermal model of conductors and a complex multi-span mechanical model of a transmission line; in fact, it takes into account the mechanical interaction between spans, due to the possible rotation of strings of insulators, as well as that the temperature of conductors can vary span by span, for different weather conditions. Several case studies are discussed, based on weather measures collected near the same overhead lines on which the Italian TSO is obtaining significant benefits from the above-mentioned DTR procedure, especially in terms of increased amount of dispatchable wind energy.
2019
Poli, Davide; Pelacchi, Paolo; Lutzemberger, Giovanni; Baffa Scirocco, Temistocle; Bassi, Fabio; Bruno, Gianluca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/962450
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