Adverse weather events can impact failure rates of grid components, leading to a degradation of power system conditions both in terms of reliability and security. This paper investigates how Optimal Network Reconfiguration (ONR) techniques can be adopted to mitigate the effects of most common adverse weather events (AWEs), such as heat waves, floodings and high speed wind gusts. The proposed ONR formulation is based on the integration of full AC network equations and operating constraints through Mixed-Integer Second Order Cone Programming techniques. The formulation is also based on the assessment of how failure and repair rates change over AWE conditions. A full description of possible approaches to update reliability parameters in relation to weather conditions is also given. Numerical tests are performed on a realistic-sized (1014-buses) distribution network model. The results have demonstrated the feasibility and scalability of the approach, making the ONR a suitable tool for enhancing grid reliability and security during AWEs. The adoption of the ONR during extreme events has led to feasible optimal configurations that improved system reliability and losses.
Mitigating the Impact of Adverse Weather Events Via MISOCP-Optimal Network Reconfiguration / Velini, A., Cometa, R., Lorusso, F., La Scala, M., Bruno, S.. - In: IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS. - ISSN 0093-9994. - Earl:(2026), pp. 1-12. [10.1109/TIA.2026.3705703]
Mitigating the Impact of Adverse Weather Events Via MISOCP-Optimal Network Reconfiguration
Velini, Angelo;Cometa, Roberto;Lorusso, Francesco;La Scala, Massimo;Bruno, Sergio
2026
Abstract
Adverse weather events can impact failure rates of grid components, leading to a degradation of power system conditions both in terms of reliability and security. This paper investigates how Optimal Network Reconfiguration (ONR) techniques can be adopted to mitigate the effects of most common adverse weather events (AWEs), such as heat waves, floodings and high speed wind gusts. The proposed ONR formulation is based on the integration of full AC network equations and operating constraints through Mixed-Integer Second Order Cone Programming techniques. The formulation is also based on the assessment of how failure and repair rates change over AWE conditions. A full description of possible approaches to update reliability parameters in relation to weather conditions is also given. Numerical tests are performed on a realistic-sized (1014-buses) distribution network model. The results have demonstrated the feasibility and scalability of the approach, making the ONR a suitable tool for enhancing grid reliability and security during AWEs. The adoption of the ONR during extreme events has led to feasible optimal configurations that improved system reliability and losses.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

