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AbstractAn arc‐furnace model consisting of non‐linear, time‐varying resistance, realized by the Alternative Transients Program (ATP), is presented in this paper. It is shown that the model is appropriate for flicker investigation in electrical networks supplying arc furnaces, constituting a valid alternative to the linear arc modelling realized by amplitude modulation of voltage generators. Block diagram of the procedure for ATP modelling of the nonlinear, time‐varying arc resistance, dynamic voltage‐current characteristic of the furnace electric arc, voltage and current arc waveforms and characteristic curves of an arc furnace, obtained by ATP simulation, are presented, referring to circuit parameters taken from an actual plant and to a sinusoidal law for arc‐length time variation. Aflickermeter ATP simulation is realized to derive equivalent voltage‐variation values in agreement with the actual flicker measurements.

Abstract The central role of occupants for achieving energy savings in residential buildings is increasingly recognised. Simulation programmes able to take into account occupant behaviour are considered to be powerful tools for bridging the gap between the predicted and the actual energy consumption for new buildings. Nevertheless, the majority of residential buildings that will constitute the housing stock in 2050 have already been built today, therefore occupant behaviour and building simulation tools need to be fully exploited for supporting the renovation of existing housing stock. The aim of this paper is to explore the role of occupant behaviour modelling in supporting decision-makers dealing with the design of renovation strategies for residential buildings. An Italian multi-family public housing building is assumed as case study to estimate the influence of three dimensions linked with occupant behaviour – management of the thermostat, management of the heating system, variation of building characteristics – on energy heating consumption. The results show that, while the occupant behaviour influences the heating loads up to 1/3 in case of high level of building retrofit, the less the building is renovated, the higher is the behavioural impact in absolute terms of energy reduction. Therefore, in order to be effective, renovation strategies are required to design appropriate informative instruments at an early stage to support behaviour changes towards responsible energy consumption.

The main objective of this paper is to illustrate the current state of the art of the newborn smart gas grid concept. We provide a detailed discussion of the envisaged features of the smart gas grid, giving attention to both the related academic literature and to the ongoing world-wide projects. In doing so, we also discuss the potentialities of rethinking the smart grid paradigm from the perspective of a whole energy system, that both encompasses the electrical and the gas grid, and identify some critical key aspects that must be handled while developing the new smart energy paradigm.

Abstract In this paper, a reintegration-based multi-objective intentional controlled islanding (ICI) model is proposed to enhance resiliency of electrical power systems under catastrophic events. This remedial measure plan relies on a mixed-integer linear programming model with two objective functions including reintegration risk and total load shedding value. While ensuring that each island includes only coherent generators, the proposed multi-objective model solves the controlled islanding problem using lexicographic optimization approach. To ease the islands’ reintegration, charging reactive power, reliability, capacity, and power flow disruption of transmission lines are considered in the model. After implementation of controlled islanding, each resulted island may face temporary active/reactive load-generation imbalance, which may put the islands at the risk of frequency instability, transient voltage instability or a combination of both. The proposed model reduces these risks by modeling energy storage systems (ESSs) and static VAR compensators (SVCs) as fast corrective control actions. In addition to modeling voltage dependent loads in the controlled islanding problem, a linear island frequency response (IFR) model is proposed for frequency stability assessment. The test results of the proposed ICI model on the IEEE 39-bus and IEEE 118-bus test systems demonstrate its performance.

Abstract This paper aims to present a feasibility study of the innovative plant for methanol synthesis from carbon dioxide-sequestered by fossil fuel power plant and hydrogen, which is produced by water electrolyzer employing the over-production on the electrical grid. The thermo-economic analysis is performed in the framework of the MefCO2 H2020 EU project and it is referred to the German economic scenario, properly taking into account the real market costs and cost functions for different components of the plant. Three different plant capacities for methanol production (4000 10,000 and 50,000 ton/year) have been investigated, assuming an average cost for electrical energy to feed electrolysers and analyzing the influence of the most significant parameters (oxygen selling option, methanol selling price and electrolysers’ capital cost) on the profitability of the plant. The analysis has been performed in W-ECoMP, software for the thermo-economic analysis and plant optimization developed by the University of Genoa.

Abstract In recent years living walls have increasingly spread, thus becoming a diffuse architectural envelope cladding technology. Consequently, a more precise understanding of their thermal behavior and impact on the building energy balance are needed. One of the most important effects provided by the use of living walls is the shading of the building envelope, with clear benefits during the cooling period. Furthermore, many features characterize the thermal behavior of living walls, namely plant species, leaf area index (LAI), evapotranspiration, emissivity and air cavity type. All these particular characteristics have been accounted in the mathematical model developed in the frame of the presented research, whose aim is to provide a tool for the prediction of the thermal behavior of living walls. Two kinds of living walls, one with grass and closed air cavity and the other one with vertical garden and open air cavity were considered. The results achieved by means of the developed model show a good agreement with the measurements also supported by model efficiency indexes such as Nash–Sutcliffe efficiency index (NSEC). Values of around 0.7 were obtained for the NSEC index for both the investigated living walls.

Abstract This paper presents experimental and numerical investigation of mistuned forced responses of an integrally bladed disk with full set of underplatform dampers (UPDs). This research aims at providing: 1. An experimental benchmark for nonlinear dynamics of a mistuned bladed disks with UPDs. 2. A numerical model that can account for features of a mistuned forced response level. Accordingly, a detailed experimental campaign is conducted on a static test rig called Octopus. This rig is specifically designed to investigate the dynamics of a full-scale integrally bladed disk (blisk) with UPDs in a noncontact manner so that the dynamic response of the system is not modified. The effect of mistuning on experimental forced response levels is assessed and a linearized model is proposed to predict the modulation of frequency response functions (FRFs) due to the frequency splitting. In the development of the model, the mistuning pattern identified from the linear blisk without UPDs is used and it is assumed that adding the dampers does not change the structural mistuning of the blisk. In this study, the fundamental mistuning model identification (FMM ID) was employed to identify the mistuning pattern of the blisk. It is shown that the proposed model successfully predicts the modulation of linear mistuned FRFs. The linearized model is also able to predict the modulation of nonlinear mistuned FRFs in stick condition (when nonlinear friction damping is negligible) with a good accuracy validating this assumption that adding the dampers does not change the mistuning pattern.

Abstract In developed countries, buildings are involved in almost 50% of total energy use and 30% of global green-house gas emissions. Buildings' operational energy is highly dependent on various building physical, operational, and functional characteristics, as well as meteorological and temporal properties. Besides physics-based building energy modeling, machine learning techniques can provide faster and higher accuracy estimates, given buildings' historic energy consumption data. Looking beyond individual building levels, forecasting buildings’ energy performance helps city and community managers have a better understanding of their future energy needs, and plan for satisfying them more efficiently. Focusing on an urban-scale, this study systematically reviews 70 journal articles, published in the field of building energy performance forecasting between 2015 and 2018. The recent literature have been categorized according to five criteria: 1. Learning Method, 2. Building Type, 3. Energy Type, 4. Input Data, and 5. Time-scale. The scarcity of building energy performance forecasting studies in urban-scale versus individual level is considerable. There is no study incorporating building functionality in terms of space functionality share percentages, nor assessing the effects of climate change on urban buildings energy performance using machine learning approaches and future weather scenarios. There is no optimal criteria combination for achieving the most accurate machine learning-based forecast, as there is no universal measure able to provide such global comparison. Accuracy levels are highly correlated with the characteristics of forecasting problems. The goal is to provide a comprehensive status of machine learning applications in urban building energy performance forecasting, during 2015–2018.