Decision Support Systems (DSS) are complex technological tools, which enable an accurate and complete scenario awareness, by integrating data from both “external” (physical) situation and current behaviour and state of functioning of the technological systems. The aim is to produce a scenario analysis and to guess identify educated the most efficient strategies to cope with possible crises. In the domain of Critical Infrastructures (CI) Protection, DSS can be used to support strategy elaboration from CI operators, to improve emergency managers capabilities, to improve quality and efficiency of preparedness actions. For these reasons, the EU project CIPRNet, among others, has realised a new DSS designed to help operators to deal with the complex task of managing multi-sectorial CI crises, due to natural events, where many different CI might be involved, either directly or via cascading effects produced by (inter-)dependency mechanisms. This DSS, called CIPCast, is able to produce a real-time operational risk forecast of CI in a given area; other than usable in a real-time mode, CIPCast could also be used as scenario builder, by using event simulators enabling the simulation of synthetic events whose impacts on CI could be emulated. A major improvement of CIPCast is its capability of measuring societal consequences related to the unavailability of primary services such as those delivered by CI.

The electrical distribution network (EDN) is a critical infrastructure that plays a primary role in a person’s life. Its resilience is a primary property to be achieved in order to withstand all types of perturbations affecting their functions, thus guaranteeing service continuity in adverse conditions. Resilience arises from a combination of a number of properties and actions related to both intrinsic system technologies and management skills. This work proposes a model enabling the estimation of the EDN operational resilience. The proposed model accounts for most of the parameters influencing the resilience of the network, such as network topology, technological properties of its active elements, the SCADA systems, automation procedures and management efficiency. Results confirm that the model can appropriately handle a real network with a large dimension and provide valuable insights to electrical operators.

A procedure for a simplified evaluation of bridges is proposed based on census and visual inspections. The structural–foundational, seismic, landslide, and hydraulic risks are considered, the hazard, vulnerability, and exposure factors of which are quantified with an index that can assume integer values from 1 to 5. Polynomial functions are then defined combining these indices, calculating an index for each risk and finally a multi-risk index of attention. The procedure follows a mathematical approach, less influenced by subjective choices, leading to a more gradual and efficient classification that managers can directly utilize. Specific needs and requirements result in specific configuration and calibration of the mathematical model coefficients. In this study, the authors calibrated coefficients to obtain results that were compliant with the Italian guidelines for existing bridges. The procedure, tested on a set of 86 bridges, does not replace an accurate evaluation, which is necessary in some cases and represents a higher level of knowledge, nor does it claim to provide a definitive result. It provides a more efficient classification, useful for establishing a rational decision-making process to prioritize any subsequent retrofit interventions.

This paper presents an overall concept developed by ENEA (the Italian National Agency for New Technologies, Energy and Sustainable Economic Development) in the Italian framework of renewable energy communities (RECs). The proposed work is driven by the idea that RECs are part of a long-term vision aimed at achieving the broader concept of smart communities (SCs) through smart energy communities (SECs). SECs are, therefore, the evolution of RECs toward SCs, where ICT (information and communications technology) and digitalization play a pivotal role in fostering and boosting the energy transition and addressing societal challenge goals by 2050. In this scenario, the proposed approach is based on three dimensions, as follows: digital tools, use cases, and the observatory. Digital tools can be utilized at different stages of the creation of RECs, ranging from the design and engagement phase to evaluation, analysis, and the token economy. The second dimension refers to some selected different business cases that are used to test and demonstrate the proposed tools and provide support to specific RECs in the different phases of their creation. Lastly, the EC observatory was created by ENEA to provide necessary support to the market and stakeholders on different aspects, such as data management, economics, legal issues, communication, and regional governance.

Electrical distribution networks deliver a fundamental service to citizens. However, they are still highly vulnerable to natural hazards as well as to cyberattacks; therefore, additional commitment and investments are needed to foster their resilience. Toward that, this paper presents and proposes the use of a complex simulation model, called reconfiguration simulator (RecSIM), enabling to evaluate the effectiveness of resilience enhancement strategies for electric distribution networks and the required resources to implement them. The focus is, in particular, on one specific attribute of resilience, namely, the readiness, i.e., the promptness and efficiency to recover the service functionality after a crisis event by managing and deploying the available resources rapidly and effectively. RecSIM allows estimating how and to what extent technological, topological, and management issues might improve electrical distribution networks’ functionality after the occurrence of accidental faults, accounting for interdependency issues and reconfiguration possibilities. The viability of implementing RecSIM on a real and large urban network is showcased in the paper with reference to the study case of the electrical distribution network (EDN) of Rome city.