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reports - Deliverable

Enhancing System Resilience through Active and Passive Measures: Modeling, Cost-Benefit Analysis, and Methodology for Identifying the Optimal Mix, Considering the Effects of Climate Change

reports - Deliverable

Enhancing System Resilience through Active and Passive Measures: Modeling, Cost-Benefit Analysis, and Methodology for Identifying the Optimal Mix, Considering the Effects of Climate Change

The report describes methodologies for evaluating resilience indicators in long-term analyses and for identifying the optimal set of resilience improvement measures through a cost-benefit analysis over different time horizons, also considering the effects of climate change. Additionally, it presents the current status of the software implementation of the RELIEF 2.0 tool for system resilience management.

The report describes developments in methodologies and tools for assessing and controlling the resilience of the electrical system.

First, it presents aspects of the long-term resilience indicator calculation methodology developed by RSE in collaboration with the national transmission system operator, Terna. The focus is on calculating annual probabilities of contingencies based on line fault return times. The proposed methodology allows for evaluating the probability of N-k contingencies on real networks using data on return times (probability distributions) of weather events.

In line with the first year’s activities, the report describes the application of a network loss minimization method for optimal reconfiguration of distribution networks during severe contingencies.

It then introduces a cost-benefit analysis (CBA) methodology for evaluating active and passive measures to support the resilience of the electrical system, consistent with approaches adopted by TSOs for planning interventions.

To evaluate the application of mitigation solutions for improving resilience, a methodology is proposed to optimize the portfolio of active and passive measures over different time horizons. The approach is formulated as a global optimization problem based on scenarios defined by uncertainties in load and renewable generation patterns and threat intensity. The objective function is the total net benefit for the network, while constraints include maximum acceptable costs for the operator. Given the multi-year horizon of the optimization, the effects of climate change (CC) on the probabilities of extreme events are considered, using a GEV (Generalized Extreme Value) distribution model and a GLM (Generalized Linear Model) to describe the temporal evolution of the related parameters.

Application to a simple test network demonstrates the proposed methodology’s ability to identify optimal mixes of measures depending on factors such as the extent of climate change and unit costs of individual measures. The current status of the SW implementation of the RELIEF platform for resilience assessment and control is also described, with integration into GIS environments, focusing on data structure, communication with external databases, and code modularization.

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