A Compact PV Panel Model for Cyber-Physical Systems in Smart Cities

One of the ambitious goals of the ‘‘Smart city’’ paradigm is to design zero-energy buildings. Buildings can be considered as connected cyber-physical systems that require the construction of sound methodologies inherited from the Electronic Design Automation (EDA) research. In particular, aiming at autonomous buildings, the effective design of renewable energy sources is a key aspect for which such methodologies have to be developed. In this work, we propose a modeling strategy for the early estimation of the performance of photovoltaic (PV) arrays. Although a plethora of PV panel models there exists, most of these models suffer from accuracy/complexity tradeoffs. On one hand, building fast models forces to ignore either the correlation between temperature and irradiance, or the topology of panels, thus yielding inaccurate estimations. On the other, more accurate models are time consuming and require costly measurements or circuit analysis, that cannot be extracted from the sole datasheet. This paper proposes a compact semi-empirical model, suitable for real time simulation and built solely from information derived from the PV panel datasheet. The model is built by empirically fitting an expression of the panel operating point as a function of both irradiance and temperature, and of the adopted PV system topology. The accuracy and effectiveness of the proposed model have been validated w.r.t. the production traces of the PV systems of a real world industrial building

Design of District-level Photovoltaic Installations for Optimal Power Production and Economic Benefit

PhotoVoltaic (PV) installations are a widespreadsource of renewable energy, and are quite common urbanbuildings’ roofs. To soften both the initial investment and therecurrent maintenance costs, the current market trends delegatethe construction of PV installations toEnergy Aggregators, i.e.,grouping of consumers and producers that act as a single entityto satisfy local energy demand and to sell the surplus energy tothe grid. In this perspective, PV installations can be designedwith a larger perspective, i.e.,at district level, to maximize powerproduction not of a single building but rather of a number ofblocks of a city. This implies new challenges, including efficientdata management (the covered area can be squared kilometerswide) and optimal PV installation (the number of PV modulescan be in the order of hundreds or even thousands). Thispaper proposes a framework to combine detailed geographic andirradiance information to determine anoptimal PV installationover a district, by maximizing both power production and economicconvenience. Our simulation results run on a real-world districtprove that the framework allows an advanced evaluation of costsand benefit, that can be used by Energy Aggregators to design anew PV installation, and demonstrate an improvement on powergeneration up to 20% w.r.t. standard installations

Frame Semantics for Social NLP in Italian:Analyzing Responsibility Framing in Femicide News Reports

We propose using a FrameNet-based ap- proach for analyzing how socially relevant events are framed in media discourses. Taking femicides as an example, we per- form a preliminary investigation on a large dataset of news reports and event data cov- ering recent femicides in Italy. First, we revisit the EVALITA 2011 shared task on Italian frame labeling, and test a recent multilingual frame semantic parser against this benchmark. Then, we experiment with specializing this model for Italian and perform a human evaluation to test our model’s real-world applicability. We show how FrameNet-based analyses can help to identify linguistic constructions that back- ground the agentivity and responsibility of femicide perpetrators in Italian news

Optimal Configuration and Placement of PV Systems in Building Roofs with Cost Analysis

Following the Smart Grid view, current energy generation systems based on fossil fuels will be replaced with renewable energy sources. Photovoltaic (PV) is currently consid- ered the most promising technology, due to decreasing costs of the devices and to the limited invasiveness in existing infrastructures, that make PV installations quite common urban buildings’ roofs. To maximise both power production and Return Of Investment (ROI) of PV installations, new techniques and methodologies should be applied to limit sources of inefficiencies, like shading and power losses due to an incorrect installation. In this paper, we propose a novel solution for an optimal configuration and placement of PV systems in buildings’ roofs. Given a number of alternative configurations and a roof of interest, it combines detailed geographic and irradiance information to determine the optimal PV installation, by maximizing both power production and ROI. Our simulation results on two real-world roofs demonstrate an improvement on power generation up to 23% w.r.t. standard compact installations. These results also highlight that a cost analysis, often ignored by standard installation strategies, is nonetheless necessary to guarantee optimal results in terms of PV production and revenue

Syntopic Cystoseira taxa support different molluscan assemblages in the Gulf of Naples (southern Tyrrhenian Sea)

Brown macroalgae belonging to the genus Cystoseira (Fucales: Sargassaceae) are canopy-forming organisms the recent decline of which at a basin and local scale has been widely documented, which urgently calls for research to fill knowledge gaps and support new and effective measures for protection. We, hereby, characterised the molluscan assemblages associated with three Cystoseira taxa (C. amentacea, C. compressa and C. crinita) from Ischia Island (Italy, Tyrrhenian Sea), and tested whether different congeneric taxa may syntopically support a different biota. In particular, these assemblages were compared among three Cystoseira species, between two times of sampling (June–July 2015 and June–July 2016), and among six sites in terms of multivariate structure (identity and relative abundances of constituting taxa combined, and presence–absence composition), as well as for synthetic measures of diversity, including the total richness of taxa, the exponential Shannon index, and the reciprocal Simpson index. In total, 24736 molluscan individuals were collected, overall belonging to 52 taxa. The majority of the identified species included micrograzers and filter feeders, which is in agreement with similar previous studies. The composition of associated molluscan assemblages, which was mainly represented by juvenile individuals, differed among the three Cystoseira species, suggesting that even congeneric taxa do not support an analogous benthic fauna. The present findings have shedded light on the molluscan biota associated with Cystoseira taxa in the Gulf of Naples and strengthened the importance of such habitat-forming macroalgae in structuring the local infralittoral invertebrate biodiversity and as a nursery for species-specific associated molluscs

A Microservices-based Framework for Smart Design and Optimization of PV Installations

The design of photovoltaic (PV) installations mostly relies on rule-of-thumb criteria and on gross estimates of the shading patterns, and the few optimized approaches are generally focused on the problem of identifying the most suitable surfaces (e.g., roofs) in a larger geographic area (e.g., city or district). This work proposes a framework to address the design and the optimization of PV installations through a set of microservices focusing on the different variables of the design: identification of the target surfaces, elaboration of weather data, modeling of the PV panel, and floorplanning of the panel on the surface. The microservices architecture ensures extensibility and generality, as the user may execute only a subset of the proposed services or provide novel algorithms to extend the existing ones. Additionally, the framework provides a set of built-in models that allow sensitivity to the distribution of shades and accurate modeling of the power production over time. We show the many benefits of the proposed framework on two different use cases