Update on coronavirus disease 2019 (COVID-19)

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Fire risk in MTBF evaluation for UPS system

The reliability improvement of no-break redundant electrical systems is the first aim of the proposed strategy. The failure of some UPS (Uninterruptible Power Supply) system may lead to the fire occurrence. The most used electrical configurations are presented and discussed in the paper. The innovation of the proposed method consists of taking into account the fire risk to improve the accuracy of wiring configuration and component’s failure rate. Thorough research on MTBF (Mean Time Between Failure) data has been performed for each wiring component and UPS. The fire risk is taken into account introducing an equivalent fire block in the Reliability Block Diagram scheme; it has an MTBF value calculated form yearly statistics of UPS fire events. The reliability of the most used UPS electrical configurations is evaluated by means of the RBD method. Different electrical systems have been investigated and compared based on MTBF. The importance of fire compartmentation between two or more UPS’ connected in parallel is proved here

QGIS-Based Tools to Evaluate Air Flow Rate by Natural Ventilation in Buildings at Urban Scale

Urban-scale evaluations of aerodynamic and morphological parameters allow correction of the wind speed within the urban boundary layer, as the wind profile is strongly influenced by the presence of roughness elements. This can have important implications for defining urban strategies for the reduction of buildings energy consumption and the improvement of air quality and liveability of outdoor spaces. Among the current models for assessing the air flow rate by natural ventilation in buildings at urban scale, this study aims to define a GIS-based methodology, using existing databases and an open source QGIS plug- in. From a digital surface elevation dataset, and considering prevalent wind directions, the displacement height (zd) was determined. The wind speed was corrected, applying the logarithmic or turbulent laws of wind profile, respectively, above and below zd. This method could determine the spatial distribution of wind speed, considering each building façade characteristics and its surroundings. Resulting wind pressure on windward and leeward façades drives the air flow rate inside the buildings. Further developments of this work will improve the air flow modelling in buildings with other tools for applications at urban scale

Statistical Data Analysis for Energy Communities

The objectives of the European Energy transition entail an increasing use of electricity especially for residential sector. Member states are invited to promote energy policies that involve stakeholders directly. Energy Communities (EC) are intended as local institutions that could drive this change, creating local-scaled energy entities that cooperate to exchange energy. The purpose of this study is to investigate the energy consumption identifying a linear regression model to forecast electric energy demand at municipal scale, for residential end users. This work analyses electric consumption of 1,201 municipalities in Piedmont (north-west of Italy) evaluating the main energy-related variables. Information are obtained by online databases and georeferenced with GIS tool. The identified model evidences that the most influential variables are the population, the number of members per family, the education level, and the income. Regarding building features, the dwelling area and the number of occupied dwellings, the age of buildings and their maintenance condition. The statistical GIS-based methodology proposed in this study is replicable and can be applied to other contexts. A forecasting model to predict the amount of energy demand can support preliminary decision-making process defining the scale of ECs and their optimal configuration for balancing energy demand and local production

Indicators and Representation Tools to Measure the Technical-Economic Feasibility of a Renewable Energy Community. The Case Study of Villar Pellice (Italy)

Energy Communities (EC) are intended as legal entities that can ensure environmental, economic, and social benefits for energy exchanges between its members. The Italian legislation has recently introduced incentives to Renewable Energy Communities (REC). This work analyses the case study of the REC in Villar Pellice (Turin) and defines a methodology to assess its technical-economic feasibility. The hourly energy consumption and the local renewable energy production are assessed through a place-based methodology, considering different category of end users (municipalities, residential dwelling, companies), and obtaining data from available online database. The REC energy performance is assessed through the self-consumption and the self-sufficiency indexes. Besides, cost-optimal analysis evaluates its economic feasibility, considering investment costs and economic incentives. Several interventions are hypothesized to compare possible REC scenarios (e.g., photovoltaic panels and storage systems installation, energy efficiency measures for public lighting, and different configurations of end users). Results show that REC allows to aggregate stakeholders, ensuring economic advantages and environmental benefits. The methodology applied in this work can support the design phase of the RECs. Its flexibility makes it adaptable to different territorial and regulatory contexts, in evaluating the optimal REC configuration to maximize revenues from the incentive and reach the highest level of energy independence

Evaluation of ventilation loads in buildings energy modelling at urban scale

Generally, the models for evaluating the energy performance of buildings have a ventilation thermal load that depends on the type of building and its occupancy rate. The models apply a constant rate of air changes and therefore the ventilation load depends on this value and on the temperature gradient between internal and external environments. In this work, a single zone air flow model is presented to modify monthly the air changes according to the climatic data, the air permeability, shape and orientation of the building and the urban morphology. The results of this work, show how the air change rates vary with the building floor and with the wind direction and velocity. For both case studies, the air changes per hours vary monthly with minimum values in wintertime and with monthly differences of 41%. Of course, if the building is not well exposed and there is no wind, the air infiltrations are not sufficient to ensure good air quality conditions and it will be necessary to open the windows. In these first two case-studies, a very simple single zone evaluation of air flow rate by natural ventilation improved the existing energy performance placebased model. The results of this work encourage the application of this model at district-urban scale, taking into account the characteristics of each single building and its surroundings

Urban-Scale Energy Models: the relationship between cooling energy demand and urban form

To enhance the quality of life in cities, it is necessary to improve the energy performance of buildings together with a sustainable urban planning especially in high-density contexts. Previous works investigated the building shape, the urban morphology, and the local climate conditions to optimize the energy performance for space heating of buildings. The aim of this study is to validate a GIS-based engineering model to simulate the hourly energy demand for space cooling in residential buildings at neighborhood scale and to assess the relationship between the urban form and the energy performance in terms of cooling energy demand. A place-based methodology was applied to six neighborhoods in the city of Turin (Italy), identified as homogeneous zones with different building characteristics and urban contexts. The hourly cooling demand of residential buildings was studied starting from the energy balance at building scale, and then was applied at block of buildings scale with the support of GIS. This model was validated with a comparison of the results using CitySim tool and ISO 52016 assessment. In order to investigate the relationship between cooling energy demand and urban form, the GIS-based engineering model was applied to five typical blocks of buildings with different construction periods. The results show how cooling energy demand varies according to building characteristics and urban morphology in a continental-temperate climate. By this analysis, it is possible to identify the optimal block of building shape in Turin ensuring lower energy consumptions during the cooling season with different types of buildings