Multivariate KPI for energy management of cooling system in food industry

Within EU, the food industry is currently ranked among the energy-intensive sectors, mainly as a consequence of the cooling system shareover the total energy demand. As such, the definition of appropriate key performance indicators (KPI) for ammonia chillers can play a strategic role for the efficient monitoring of the energy performance of the cooling systems. The goal of this paper is to develop an appropriate management approach, to account for energy inefficiency of the single compressors, and to identify the specific variables driving the performance outliers. To this end, a new KPI is proposed which correlates the energy consumption and the different process variables. The construction of the new indicator was carried out by means of multivariate statistical analysis, in particular using Kernel Partial Least Square (KPLS).This method is able to evaluate the maximum correlation between dataset and energy consumption employing nonlinear regression techniques. The validity of the new KPI is discussed on a case study relevant to the cooling system of a frozen ready meals industry. The assessment of the proposed metric is one against Specific Energy Consumption (SEC) like indicator, typically used in the context of the Energy Management Systems

Carbon Dioxide (CO2) Sequestration and Air Temperature Amelioration Provided by Urban Parks in Rome

Abstract Urban landscapes are rapidly expanding globally and transforming the structure and function of urban areas, thereby influencing the quality of life. Cities account for more than 70% of the energy related to global greenhouse gases, which is expected to rise up to 76% by 2030. Taking into account that over 50% of the world's population lives in cities and more than two thirds are expected by 2050, the problem of mitigating the atmospheric CO 2 concentration is considerable. The urban areas covered by parks, gardens, tree-lined avenues, sport fields, and hedges are important sinks for carbon dioxide (CO 2 ) by storing carbon through photosynthesis to form plant biomass. Despite plant CO 2 sequestration is an important ecosystem service, the relationship between urban park vegetation and CO 2 emission reduction is not completely clarified. In this context, the main objective of our research was to evaluate the role of urban park vegetation in improving air quality in Rome in terms of CO 2 concentration and air temperature. In particular, we analyzed the relationship among the different vegetation types, size and position of an historical urban park in Rome. Moreover, since the presence of buildings within urban parks determines CO 2 emissions closely related to their purpose of use, it is important to evaluate their impact in order to set instruments for their retrofit, considering the necessity of a compromise among the energy audit, the use of renewable energy systems and preservation of cultural heritage

Computational Structural Biology of S-nitrosylation of Cancer Targets

Nitric oxide (NO) plays an essential role in redox signaling in normal and pathological cellular conditions. In particular, it is well known to react in vivo with cysteines by the so-called S-nitrosylation reaction. S-nitrosylation is a selective and reversible post-translational modification that exerts a myriad of different effects, such as the modulation of protein conformation, activity, stability, and biological interaction networks. We have appreciated, over the last years, the role of S-nitrosylation in normal and disease conditions. In this context, structural and computational studies can help to dissect the complex and multifaceted role of this redox post-translational modification. In this review article, we summarized the current state-of-the-art on the mechanism of S-nitrosylation, along with the structural and computational studies that have helped to unveil its effects and biological roles. We also discussed the need to move new steps forward especially in the direction of employing computational structural biology to address the molecular and atomistic details of S-nitrosylation. Indeed, this redox modification has been so far an underappreciated redox post-translational modification by the computational biochemistry community. In our review, we primarily focus on S-nitrosylated proteins that are attractive cancer targets due to the emerging relevance of this redox modification in a cancer setting

Sensitive methods for estimating the anchoring strength of nematic liquid crystals on Langmuir-Blodgett monolayers of fatty acids

The anchoring of the nematic liquid crystal N-(p-methoxybenzylidene)-p-butylaniline (MBBA) on Langmuir-Blodgett monolayers of fatty acids (COOHC$_{n}$H$_{2n+1}$) was studied as a function of the length of the fatty acid alkyl chains, $n$ ($n = 15, 17, 19, 21$). The monolayers were deposited onto ITO-coated glass plates which were used to assemble sandwich cells of various thickness that were filled with MBBA in the nematic phase. The mechanism of relaxation from the flow-induced quasi-planar to the surface-induced homeotropic alignment was studied for the four decreases linearly with increasing the length of the alkyl chains $n$ which suggests that the Langmuir-Blodgett film plays a role in the phenomenon. This fact was confirmed by a sensitive estimation of the anchoring strength of MBBA on the fatty acid monolayers after anchoring breaking which takes place at the transition between two electric-field--induced turbulent states, denoted as DSM1 and DSM2. It was found that the threshold electric field for the anchoring breaking, which can be considered as a measure of the anchoring strength, also decreases linearly as $n$ increases. Both methods thus possess a high sensitivity in resolving small differences in anchoring strength. In cells coated with mixed Langmuir-Blodgett monolayers of two fatty acids ($n=15$ and $n=17$) a maximum of the relaxation speed was observed when the two acids were present in equal amount. This observation homeotropic cells by changing the ratio between the components of the surfactant film.Comment: LaTeX article, 20 pages, 15 figures, 17 EPS files. 1 figure added, references moved. Submitted to Phys. Rev.

Maria Nallino (1908-1974) and the Birth of Arabic and Islamic studies at Ca’ Foscari

This essay, based on bibliographic and archival material, focuses on the academic figure Maria Nallino, a scholar whose voluminous body of work ranges from classicism to modernity with equal fluency and expertise. Daughter of the famous Orientalist Carlo Alfonso Nallino (1872-1938), whose work she gathered and actively promoted, her arrival at Ca’ Foscari (1962) inaugurated Arabic and Islamic studies in Venice

A mixed-integer linear programming approach for the optimization of residential PV-battery energy storage system

Europe´s electricity sector is facing a major historical turning point shifting away from fossil fuels towards more sustainable energy sources and moving from vertically integrated public monopolies into competitive private companies in unbundled and liberalized markets. In this scenario consumers are expected to play a fundamental role in realising the full potential of the European energy market; the EU energy strategy, with new policy and regulatory initiatives, in fact, recognizes consumers and communities as a key driver of this process, encouraging them to take full ownership of the energy transition and empowering them to actively participate in the electricity market by generating, consuming and selling electricity back to the grid and interacting with other energy market participants. Citizens are in fact no longer restricted to the role of passive end-use consumers, but they are asked to be energy producers, or ‘prosumers’, representing an important contribution to global sustainability and helping to decarbonize the electricity sector. Furthermore, as well as allowing to increase the amount of renewable energy generation, they have the potential to reduce the energy supply-demand gap and electricity system losses and to provide opportunities for demand-side management and for an active grid support increasing grid reliability flexibility, and resiliency. To this end, distributed energy storage systems at the residential level have been identified as a priority technology to open up new possibilities for local flexibility solutions and participation in demand response, leading the energy transition towards new energy configurations, such as self-generation and self-consumption schemes and peer-to-peer selling of the self produced energy. Combining solar power generators and battery storage is one of the most common ways of reaching self-sufficiency in residential buildings by increasing the grid independence of individual households. Due to their cost and growth perspective, battery storage coupled to photovoltaic (PV) generation systems have reached a good level of competitiveness and market penetration in many European countries and they will increase as more such systems become available. In this thesis a battery energy storage systems (BESS) coupled with grid-connected rooftop-mounted residential photovoltaic generation is analyzed. The multi apartment building is located in Civitavecchia (Rome), central Italy, with ten households living in rent at a subsidized price and it is covered by the energy retrofit intervention and building renovation plan set by “Civitavecchia SMART-A.T.E.R.” project aiming to convert the old buildings in new Near Zero Energy Buildings (NZEBs) and to create energy communities. The aim of this thesis is to optimize the sizing and the operation of the battery energy storage system so as to maximize the households’ self-consumption and minimize their electricity bill, whilst ensuring the correct charge-discharge cycles scheduling strategy in order to assure better performance and a longer lifetime of the batteries. To this end, a multi-objective mixed-integer linear programming (MILP) formulation is proposed and it is solved by CPLEX. The battery sizing and operational parameters, in terms of number of batteries and charging/discharging operation mode, are included in the optimization problem and a penalty coefficient is imposed to limit the number of batteries needed. Collected and estimated data of potential photovoltaic production and households’ demand profiles are used to optimize the battery storage system using hourly dataset for different seasons

Un progetto per una scuola di lingue orientali a Venezia nel Settecento

Donated by Klaus KreiserReprinted from in : Quaderni di Studi Arabi, Vol: 1, 1983

Gen-Set Control in Stand-Alone/RES Integrated Power Systems

Power supply in stand-alone power systems, such those in non-grid connected islands, represents an important area of study in investigating smart energy concepts. In particular, the discontinuity in renewable energy availability and the mismatch with power demand are likely to hinder grid stability and overall system efficiency. Typically, the load-levelling relies on diesel engine gen-sets which suffer the modulation of power output resulting in increased operation costs and life time reduction. Although energy storage can complement power fluxes balance, a proper dispatch strategy is needed in order to improve diesel engine operations in Renewable Energy Source (RES) integrated systems. The present study investigates the merit of a dispatch strategy aiming at improving gen-set performance in a hybrid RES/storage/Diesel Engine Generator set (DEGS) power configuration. The proposed dispatch strategy is modelled in a transient simulation software, with hourly based analysis over a year period and is applied to a small island case study

Multi-objective mathematical programming for optimally sizing and managing battery energy storage for solar photovoltaic system integration of a multi-apartment building

This article presents a novel mathematical formulation to solve the problem of optimally sizing and managing battery energy storage for the solar photovoltaic system integration of a multi-apartment building. The aim is the maximization of the collective self-consumption maintaining control over time of the energy sold and bought and the monitoring of the state of batteries while ranging from minimum to maximum levels. This is obtained through a new mathematical programming model with three different objective functions that can be tuned simultaneously to find Pareto optimal solutions to the problem. The computational results in detailed scenarios with real data verify the model's adequacy to deal with the real problem and give a measure of the saving of bought and sold energy

Complex Network Analysis of Photovoltaic Plant Operations and Failure Modes

This paper presents a novel data-driven approach, based on sensor network analysis in Photovoltaic (PV) power plants, to unveil hidden precursors in failure modes. The method is based on the analysis of signals from PV plant monitoring, and advocates the use of graph modeling techniques to reconstruct and investigate the connectivity among PV field sensors, as is customary for Complex Network Analysis (CNA) approaches. Five month operation data are used in the present study. The results showed that the proposed methodology is able to discover specific hidden dynamics, also referred to as emerging properties in a Complexity Science perspective, which are not visible in the observation of individual sensor signal but are closely linked to the relationships occurring at the system level. The application of exploratory data analysis techniques on those properties demonstrated, for the specific plant under scrutiny, potential for early fault detection