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Smart charging is a means of monitoring and actively controlling EV chargers to optimize the distribution and consumption of energy with a focus on peak-load avoidance. This paper describes the most important requirements that have influenced the design and implementation of the "Smart Charging System" (SCS). It presents the architecture and main functional building blocks of the SCS, which have been realized in an iterative development process as an extension component of the already existing open-source solution "Open e-Mobility". We also provide details on the functionality of the core smart charging algorithm within SCS and show how various data sources can be utilized by the system to increase the safety and efficiency of EV charging processes. Furthermore, we describe our iterative approach to developing the system, introduce the real-world testbed at SAP Labs France in Mougins/France, and share evaluation results and experiences gathered over a three-year period. [ABSTRACT FROM AUTHOR]

This paper reanalyzes the determinants of the CO emissions in France. For this purpose, it considers the unit root test with two structural breaks and a dynamic ordinary least squares estimation. The paper also considers the effects of the energy consumption and the economic complexity on CO emissions. First, it is observed that the EKC hypothesis is valid in France. Second, the positive effect of the energy consumption on CO emissions is obtained. Third, it is observed that a higher economic complexity suppresses the level of CO emissions in the long run. The findings imply noteworthy environmental policy implications to decrease the level of CO emissions in France. [ABSTRACT FROM AUTHOR]

This paper develops a pseudo-panel approach to examine household electricity demand behavior through the household life cycle and its response to income variations to help strengthen the energy policy-making process. Our empirical methodology is based on three rich independent microdata surveys (the National Housing Surveys), which are representative of the French housing sector. The resulted sample covers the 2006–2016 period. Using within estimations, this paper finds striking evidence that the income elasticity of French residential electricity demand is 0.22, averaged over our four cohorts of generations. In light of other works, our estimate stands in the lower range. The empirical results also show that residential electricity consumption follows an inverted U-shaped distribution as a function of the age of the household's head. Most notably, it appears that households at the mid-point of their life cycle are relatively the largest consumers of electricity. This outcome has important implications for policy-making. Any public policy aimed at reducing household energy consumption should consider this differentiation in consumption according to the position of households over the life cycle, and therefore target as priority households at the highest level of consumption. [ABSTRACT FROM AUTHOR]

This paper proposes an integrated model for multi-machines dynamic lot sizing aiming to produce a single item, considering the energy consumption during the production horizon. The objective is to find, firstly, the optimal lot size as well as the number of machines that satisfy a random demand under given service level and secondly, maintenance plan depended to production planning to minimise the total production, energy and maintenance costs. In fact, the problem of energy consumption is one of the most evoked topics especially with the decision of many governments to reduce theirs (For example France is willing to reduce the total consumption by 20% by 2020). The keys of this study are to consider, firstly, the correlation between the forecasting of demand, the variation of the working machines as well as their production rates under energy constraint and secondly the correlation between the production cadences and the maintenance strategy of all machines. [ABSTRACT FROM AUTHOR]

A large fraction of heat production from power sources is wasted in the environment, despite its numerous potential energy uses, for example, district heating, seawater desalination, or hydrogen production. In this paper, we use the MIXOPTIM methodology to evaluate performance indicators of mixes of electric power sources with and without cogeneration of heat to assess the benefits it entails. It appears from the study that the cogeneration option is highly interesting for mixes with a large nuclear share. The case of France is analyzed in detail, with an evaluation of the overall potential of cogeneration in terms of economic competitiveness as well as in terms of greenhouse gas emission reduction. [ABSTRACT FROM AUTHOR]

This paper examines how intermediaries could interact with other important actors identified by the multi-level perspective (MLP) framework, the niche actors and regime actors, to create niches for nuclear heat production in France. Whatever is the source, recovering the wasted heat is a matter of energy efficiency. Nuclear plants could remain used for several decades in France. It is thus legitimate to investigate those possible niche nurturing processes which may allow a more efficient use of this technology. Challenges are high, and our conclusions modest regarding the possible breaking through of such exploratory and collective systems. Without significant windows of opportunity, even the most willing intermediation may not be able to change the status quo. It is however important to highlight the multifarious pathways that energy transitions could follow. Drawing on lessons from the MLP, this paper proposes three key actions for intermediation willing to move beyond technology-push approaches that can lead to tension and low legitimacy. These are, sharing questions instead of knowledge; mobilise, interest, involve a legitimate place; and prevent or avoid conflicts among stakeholders. Regime changes possibly enhancing the deployment of sustainable heating systems, not only nuclear plant sourced, are also discussed. [ABSTRACT FROM AUTHOR]

In order to more accurately predict the global solar energy consumption, a new grey prediction model FDGM(1,1, t α ) is proposed in this paper. The grey wolf optimizer (GWO) is used to optimize the fractional-order r and the time power α in the model. The proposed FDGM(1,1, t α ) model, two statistical models and other five existing grey models are used to simulate and predict the solar energy consumption in the four economies (France, South Korea, OECD and Asia Pacific region) from 2010 to 2029. The simulation results show that our proposed FDGM(1,1, t α ) has higher accuracy than the other seven models. The prediction results based on FDGM(1,1, t α ) show that in 2029, the solar energy consumption in South Korea, the OECD and the Asia Pacific region will reach 33,935.32 Ten-trillion J, 1,222,123.45 Ten-trillion J and 2,297,274.45 Ten-trillion J, respectively, but that in France will slowly increase in the next few years and will gradually decrease after reaching a peak of 14,727.34 Ten-trillion J in 2026. The better forecasting solar energy consumption by using the proposed model can provide useful information for the policy-makers to formulate and improve energy policies and measures. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of heating expenses in a large social housing stock in the North of France. An artificial neural network (ANN) approach is taken for the analysis of heating consumption data collected over four years in 84 social housing residences containing 13,179 dwellings that use collective heating. Analysis provides an understanding of the influence of both physical and socio-economic parameters on heating expenses and proposes a predictive model for these expenses. The model shows that the heating expenses are influenced by both the buildings' physical parameters and social indicators. Concerning the physical parameters, the most important indicators are the area of the dwellings, followed by the building age and the DPE (energy performance diagnostic). The family size as well as tenant age and income have an important influence on heating expense. The model is then used for establishing a data-based strategy for social housing stock renovation. [ABSTRACT FROM AUTHOR]

Nuclear power is largely analysed as a contested energy production technology with a focus on the factors for the success or failure of the development of nuclear programmes but little questioning of the usages associated with this energy production. By concentrating specifically on the question of usage, this article sheds light on an original timeline of the development of nuclear power in France in the 1970s. It highlights the existence of an intense debate on the means of using the energy that would be produced by this industry and on the models of technical, political, economic and spatial organisation of the energy system that would result. Based on an analytical work of several historical archival funds, this paper brings into light how three sociotechnical regimes were in competition to organize the French energy system during the development of the national nuclear programme. From an historical geography perspective, this paper provides insights for a critical rethinking of the development of nuclear programmes as well as for the politics surrounding the phase-out of nuclear power. • The means of using nuclear energy were intensely discussed during the development of the French programme. • Three technical, political, economic and spatial models of nuclear development were in competition. • The development of nuclear power can follow several spatial routes. • The legacy of the electric heating choice restricts the construction of a new energy transition. [ABSTRACT FROM AUTHOR]

This paper presents an instructive case study showing how strategic communication designed to achieve European Union directives regarding energy saving plays out in practice. The two-year qualitative study examined the impact of a French energy supply company's strategic practices. These practices were designed to transform not only the way consumers think about energy but also their consumption practices and how they made sense of these practices. Paradoxically, the texts that the supply company exchanged with customers, as their primary form of strategic practice, acted in ways that blocked the achievement of their strategic intent. The texts exhibited alternative forms of agency that (re)constituted the company-customer interface. In revealing this outcome, the paper contributes to a scant literature on the performance of mundane strategic tools, offering a unique example of an "ideological fantasy of 'empowerment'" (Wright, 2012) that was not realized in practice. The findings provide a warning, in this case to energy suppliers, that strategic texts have unintended and independent agency in the collaborative process of negotiating customers' understanding of energy and consumption options. [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• The paper has a focus on energy consumption habits and trends using statistical methods. • Occupants' behavior is monitored using smart metering system and awareness surveys. • The impact of a serious game on occupant's behavior is evaluated. The paper has a focus on energy consumption habits, trends and intervention strategies in residential buildings, mainly through the serious game approach with a combination of direct consumer feedback through smart metering. More than 150 homes in France and Spain have been involved in the research experiment and the consumption habits of approximately 50 homes were deeply analyzed. The applied methods, processes, results and findings of the monitoring data analysis are presented in the paper with two aims. First, consumption profiles and trends were determined for apartment homes with regard to heating, domestic hot water and electric consumption. Second, the impact of a serious game experiment was assessed comparing energy consumption, indoor air temperature and users' habits (based on questionnaires) before and after launching the experiment. [ABSTRACT FROM AUTHOR]

• Overheating regulations and calculation methods in 26 European countries were compared. • Most of the existing calculation methods are outdated and do not fit climate-proof buildings. • France requires a mixed-mode operation of naturally ventilated households. • The UK developed a heatwave-based calculation approach. • Comfort-based, multi-zonal, and time-integrated calculation approaches are needed. With the ongoing significance of overheating calculations in the residential building sector, building codes such as the European Energy Performance of Building Directive (EPBD) are essential for harmonizing the indicators and performance thresholds. This paper investigates Europe's overheating calculation methods, indicators, and thresholds and evaluates their ability to address climate change and heat events. e study aims to identify the suitability of existing overheating calculation methods and propose recommendations for the EPBD. The study results provide a cross-sectional overview of twenty-six European countries. The most influential overheating calculation criteria are listed the best approaches are ranked. The paper provides a thorough comparative assessment and recommendations to align current calculations with climate-sensitive metrics. The results suggest a framework and key performance indicators that are comfort-based, multi-zonal, and time-integrated to calculate overheating and modify the EU's next building energy efficiency regulations. The results can help policymakers and building professionals to develop the next overheating calculation framework and approach for the future development of climate-proof and resilient residential buildings. [ABSTRACT FROM AUTHOR]

In the literature, it is well known that there is a bidirectional causality between economic growth and energy consumption. This is why it is crucial to forecast energy consumption. In this study, four deep learning models, i.e., Long Short-Term Memory (LSTM), stacked LSTM, bidirectional LSTM, and Gated Recurrent Unit (GRU), were used to forecast energy consumption in Brazil, Canada, and France. After a training test period, the performance evaluation criterion, i.e., R2, mean square error, root mean square error, mean absolute error, and mean absolute percentage error, was performed for the performance measure. It showed that GRU is the best model for Canada and France, while LSTM is the best model for Brazil. Therefore, the energy consumption prediction was made for the 12 months of the year 2017 using LSTM for Brazil and GRU for Canada and France. Based on the selected model, it was projected that the energy consumption in Brazil was 38 597.14–38 092.88, 63 900–4 800 000 GWh in Canada, and 50 999.72–32 747.01 GWh in France in 2017. The projected consumption in Canada was very high due to the country's higher industrialization. The results obtained in this study confirmed that the nature of energy production will impact the complexity of the deep learning model. [ABSTRACT FROM AUTHOR]

Light pollution from the use of artificial lighting poses significant impacts on human health, traffic safety, ecological environment, astronomy, and energy use. The advancement of characteristics of light pollution assessment technology has played a significant role in shaping prevention and control policies, thereby enabling measures, such as environmental standards and legislation and product procurement guidelines, but considerable variation in the definition, control strategies, and regulatory frameworks remains. Therefore, there is a need to review the characteristics of light pollution, including the assessment technique, policy, and legislation. Through the literature review, it can be found that technical standards are required to prevent light pollution. For example, light pollution is decreased by 6% in France through the legislation of artificial light. Key approaches are suggested to control global light pollution, including implementing ambient brightness zoning, regulating lighting product usage, and establishing dark sky reserves. Technology and policy should be integrated. The precise data coming from satellite imagery, drones, and balloons could provide guidance when making the policies. [ABSTRACT FROM AUTHOR]

Energy consumption in the social housing sector constitutes a major economic, social, and environmental issue, because in some countries such as France, social housing accounts for about 19% of the housing sector. In addition, this sector suffers from ageing, which results in high energy consumption, deterioration in the occupant quality of life, and high pressure on the budget of low-income occupants. The reduction of the energy consumption in this sector becomes a "must". This reduction can be achieved through energy renovation and innovation in both energy management and occupant involvement by using smart technology. This paper presents a contribution to this goal through the investigation of the impact of smart monitoring on energy savings. The research is based on monitoring of comfort conditions in an occupied social housing residence in the North of France and the use of building thermal numerical modeling. Results of monitoring show that the indoor temperature largely exceeds the regulations requirements and the use of a smart system together with occupant involvement could lead to significant savings in heating energy consumption. The novelty in this paper concerns the use of comfort data from occupied social housing residence, occupation conditions, and building thermal modeling to estimate energy savings. The proposed methodology could be easily implemented to estimate heating energy savings in social housing buildings that lack individual energy consumption monitoring. [ABSTRACT FROM AUTHOR]

The circular economy is a decisive strategy for reconciling economic development and the environment. In France, the CE was introduced into the law in 2015 with the objective of closing the loop. The legislation also delegates energy policy towards the French regions by granting them the jurisdiction to directly plan the energy–climate issues on their territory and to develop local energy resources. Thereby, the SUD PACA region has redefined its objectives and targeted carbon neutrality and the transition to a CE by 2050. To study this transition, we developed a TIMESPACA optimization model. The results show that following a CE perspective to develop a local energy system could contribute to reducing CO2 emissions by 50% in final energy consumption and reaching almost free electricity production. To obtain greater reductions, the development of the regional energy systems should follow a careful policy design favoring the transition to low energy-consuming behavior and the strategical allocation of resources across the different sectors. Biomethane should be allocated to the buildings and industrial sector, while hydrogen should be deployed for buses and freight transport vehicles. [ABSTRACT FROM AUTHOR]

Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Macro defect free (MDF) cements are polymer-cement composites characterized by high biaxial flexural strength compared to traditional concrete, having as a drawback a low water resistance. Glazing these composite materials with an inorganic enamel containing TiO2 nano-particles has led to a high water-stable material with advanced photocatalytic properties. Classic glazing by thermal treatment of samples, at 1050 °C, requires energy consumption and long-time performing. The purpose of this paper is to test the use of solar radiation as a source of energy in the glazing process. A vertical axis solar furnace has been used, from PROMES-CNRS Solar Laboratory, Font-Romeu Odeillo, France, and it has been observed that a uniform appearance of the glaze coating has been achieved; it shows high scratch resistance, meaning a good hardness and adhesion to the substrate. The obtained film was also characterized by SEM, EDS and XRD, aiming to evidence the coat morphology, the TiO2 distribution and its crystallinity alteration, when compared to the samples obtained by classic thermal treatment. The conclusion of the paper is that using solar radiation in the MDF cement glazing process is a promising approach for obtaining multifunctional materials. [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

The relevance, relative importance and colinearity of input parameters to the results of building energy demand forecasts were investigated. Two calendar years of historical data including weather variables and days of the week were used. The study also aimed to assess the performance of multiple-linear-regression, support-vector-machine and artificial-neural-network models for predicting the daily heating, ventilation and air-conditioning energy consumption of a commercial building in France. Mean absolute error, root-mean-square error and coefficient of variation of root-mean-square error were selected as the performance criteria. The results showed that the best performance was achieved through the artificial-neural-network model according to all performance measures. Besides, the other two models were not able to meet the prediction requirements for energy consumption in a building since their coefficient-of-variation-of-root-mean-square-error values were not below 30%. The results also indicated that there was multiple colinearity between the number of degree days and outdoor temperature. Furthermore, the most significant parameter for daily energy consumption was found to be the number of degree days, followed by global radiation, sunshine rate and the day of the week. [ABSTRACT FROM AUTHOR]

To ensure regular and high yields, current agriculture is based on intensive use of pesticides and fertilizers, which are detrimental to the environment and human health. Moreover, as pest resistance to pesticides increases, and more and more pesticides are taken off the market, national and European policies are becoming powerful drivers to deliver pesticide-free farming systems. Whereas numerous studies have compared organic versus conventional systems, our study assessed, for the first time, the performances of a pesticide-free arable cropping system (No-Pesticide), using synthetic fertilizers, specifically designed to produce high yields and meet environmental goals. This system was compared with an input-based cropping system designed with the same environmental targets (PHEP: productive with high environmental performances) in an 11-year field trial in France (Paris Basin). Banning pesticides did not result in a significant average yield gap (in GJ.ha−1.year−1 or in kg N.ha−1.year−1) calculated over the crop sequence. Yet, some crops' yields significantly decreased, due either to pest damages, or to limited nitrogen nutrition. In the No-Pesticide system, the mycotoxin content of cereal grains was lower than the regulatory threshold, and the average wheat protein content was higher than the required standard for baking. Indirect energy consumption, total greenhouse gas emissions, number of technical operations, nitrogen fertilizer amounts, and treatment frequency indexes were significantly lower compared to the PHEP system. Conversely, results showed significantly higher direct energy consumption, direct greenhouse gas emissions, and number of work hours for weed control. We identify highly effective agricultural strategies to avoid pesticide use (e.g., widely diverse and long crop sequence; introduction of hemp) and pinpoint several technical lock-ins hampering steady production in pesticide-free systems. We argue that more experiments should be undertaken to deliver technical knowledge for managing major or orphan species within pesticide-free systems, and to provide supplementary results, including economic and social performances. [ABSTRACT FROM AUTHOR]

Abstract To the best of our knowledge, there is no econometric study on the causal relationship between renewable or fossil energies and terrorism, nor on terrorism in France. This paper tries to fill this gap and considers other variables as economic growth and trade openness. The autoregressive distributed lag approach and Granger causality are used for annual data on France covering the period 1980–2015. The Wald test confirms the existence of long-run relationships between the considered variables. Granger causality reveals long-run bidirectional causalities between all the variables. Interestingly, in the short-run, there are unidirectional causalities running from renewable energy to terrorism, and from terrorism to trade openness, and there is bidirectional causality between terrorism and economic growth. Long-run parameter estimates show that more renewable energy consumption and more trade increase both terrorism and economic growth. However, economic growth reduces terrorism in the long-run and appears as a powerful tool to combat terrorism in France. In addition, France is recommended to continue encouraging the use of renewable energies, and at the same time, to make more diplomatic efforts to resolve political and military conflicts in the world, and particularly in the Middle East. Highlights • There is long-run bidirectional causality between renewable energy and terrorism. • There is long-run bidirectional causality between fossil energy and terrorism. • There is short-run unidirectional causality running from renewable energy to terrorism. • In the long run, renewables increase terrorism and economic growth. • In the long run, economic growth reduces terrorism and increases renewable energy. [ABSTRACT FROM AUTHOR]

Highlights • We tackle the real-time Energy Consumption Minimization Problem. • It minimizes train energy consumption and delay, with given routing and precedences. • We propose an algorithm based on mixed-integer linear programming. • We test it on a critical French control area where traffic is dense. • The results show that good solutions can be often found in real-time. Abstract A new timetable must be calculated in real-time when train operations are perturbed. Although energy consumption is becoming a central issue both from the environmental and economic perspective, it is usually neglected in the timetable recalculation. In this paper, we formalize the real-time Energy Consumption Minimization Problem (rtECMP). It finds in real-time the driving regime combination for each train that minimizes energy consumption, respecting given routing and precedences between trains. In the possible driving regime combinations, train routes are split in subsections for which one of the regimes resulting from the Pontryagin's Maximum Principle is to be chosen. We model the trade-off between minimizing energy consumption and total delay by considering as objective function their weighted sum. We propose an algorithm to solve the rtECMP, based on the solution of a mixed-integer linear programming model. We test this algorithm on the Pierrefitte-Gonesse control area, which is a critical area in France with dense mixed traffic. The results show that the problem is tractable and an optimal solution of the model tackled can often be found in real-time for most instances. [ABSTRACT FROM AUTHOR]

We compare the performance of four types of support schemes aimed at improving residential energy efficiency in France: the income tax credit, a grant scheme, the reduction of the value-added tax, and the White Certificates. We use the TREMI dataset which covers close to 14,000 households that conducted conservation works. To address self-selection bias, we use a double-robust inverse probability weighting estimator. We assess the effect of the adoption of each scheme on the funding acquired, the private and total investment, and the reduction of the household energy expenses. For each scheme, we use the estimates to deduct its cost-effectiveness, the involved redistribution, and its ability to trigger additional investment in energy conservation works. We find funding from the schemes to reduce energy expenses most cost-effectively via the White Certificates. Redistribution is neutral for each of the four schemes: higher and lower income households equally benefit from them. [ABSTRACT FROM AUTHOR]

Buildings are the largest contributors to households' energy footprints. If both the energy for household mobility and the embodied energy are added to the energy for heating/cooling, domestic hot water, lighting, buildings are by far the main problem of energy consumption in France. This paper presents a review of the evolution of the main drivers of CO 2 emissions by buildings in France. Eventually, the paradox of the effect of density is discussed. Lower density of cities increases the energy spent per inhabitant, in particular for transport, but may also increase the production of low-carbon renewable energies, shifting the global energy balance and influencing the prospective studies of future, energy efficient, smart cities. [ABSTRACT FROM AUTHOR]

Earth–air heat exchanger (EAHE) systems are used to pre-heat or pre-cool air before entering into a building using shallow geothermal energy. Assessment of EAHE systems is important to quantify the profitability of these systems. For this purpose, an EAHE system built at ICUBE at the University of Strasbourg in the northeast of France was studied using energy and exergy analyses for a typical heating period (between 25 February and 3 March). Energy analysis was used to determine the heat gained by the air in the system during the studied period and to determine the Coefficient Of Performance (COP) of the system. Additionally, exergy analysis, which considered temperature, pressure, humidity, and the variation in the control volume boundary temperature, was realized to determine inefficiencies in the system by determining the exergy destroyed in each component of the system and evaluating its exergetic efficiency. Results showed that the heat energy gained using the system was around 63 kWh and that the exergetic efficiency of the system was about 57% on average. The comparison of exergetic efficiency between the EAHE components showed that the fan has the lowest performance and should be improved to achieve better overall performance. [ABSTRACT FROM AUTHOR]

This paper details a manual calibration of a 132 zones, highly monitored 5 434 m2 office building located in France. The calibration is conducted over one year of simulation at a five minute time-step. The model is mostly fed with input files containing measured data for each simulation time-step. First simulation results show that the model cannot be considered as being calibrated considering usual guidelines based on statistical indicators calculated on monthly energy consumption. Instead of going through a classical tuning process to match measured and simulated monthly energy consumption data, the choice was made to focus on explaining those discrepancies using available building information and monitoring data. A first dynamical heating and cooling powers analysis has been made, resulting in good correlation with measured values and explaining most of the discrepancies previously noticed, followed by a dynamical temperature analysis performed at the zone scale, and completed by a global statistical analysis at the building scale for the 132 zones of the building. Results showed very good agreement between measured and simulated temperature values with 90% of data points ranging between −1.72 °C and 2.02 °C of error. This demonstrate that a model that at first glance does not perform well considering particular statistical indicators can show an accurate dynamical behavior and a good performance when other variables and performance criteria are considered. This is followed by a discussion of the possible model improvements along with the limitations of statistical analysis compared to dynamic physical analysis for calibration performance assessment. The paper concludes with several proposals to improve the guidelines for calibration procedures involving the use of detailed monitoring data. [ABSTRACT FROM AUTHOR]

Previously documented studies in the literature on how tourism leads to economic growth in the form of tourism-led growth hypotheses (TLGH) has been investigated. This study presents a new perspective on the growth of tourism by considering its impact on conventional energy consumption, real income level, and emission via the channel of globalization. Sequences of econometric tests were conducted to validate the hypothesized claims between tourism development and growth impact on conventional energy consumption and pollution proxy by ecological footprints, globalization GDP per capita, biocapacity, and tourists for the case of France. Empirical evidence from the Granger causality test presents a uni-directional causality from ecological footprints to GDP per capita and from biocapacity to ecological footprints. The correlation matrix shows interrelation amongst series with biocapacity significantly correlating with ecological footprints with tourist’s arrival having a positive correlation with ecological footprints and a negative one with biocapacity. GPD per capita was found to positively affect the ecological footprints and have a negative correlation with biocapacity and a significant relationship with tourists' arrivals. Additionally, globalization exerts a positive impact on ecological footprints, and its effect on biocapacity was found to be negative although globalization's effect on tourists’ arrivals and per capita GDP is significant. The ARDL estimation indicated biocapacity as a neutral agent for ecological footprints, tourist arrivals having a negative impact on ecological footprints, and globalization significantly affecting ecological footprints. From these findings, it is evident that tourism growth has a significant impact on energy consumption and pollution. Policy recommendations were also provided in this study accordingly. [ABSTRACT FROM AUTHOR]

Recent economics literature emphasises the inextricable link between economic prosperity and efficient energy supply and consumption, arguing vehemently that much of today's prosperity is predicated on secure and reliable energy use and that modern industry would grind to a halt without the necessary energy infrastructure. France is an example of an advanced country with enormous energy infrastructure. The country's economic growth has been rather sluggish in recent years, despite its robust and efficient energy production and consumption. The current study analyses empirically whether France's current sustainable electricity use defies the theoretical and empirical literature. To achieve this objective, the standard tools of growth empirics were used over the period 1961–2015. The Zivot–Andrews trended and de-trended structural break tests, as well as Autoregressive Distributed lag (ARDL) bounds testing were employed to analyse the data. The findings of this study demonstrated that France's economic growth is stimulated by electricity usage, financial development, capital, import, and export. The study sheds light on the feedback impact between economic growth and power usage as well as capital and economic growth. With these findings, we argue that it is not electricity that has ceased to serve a functional purpose in France, rather there is a need for entrepreneurial innovative capacity to create factors that require an infinite horizon for the continued use of electricity, which seems to be impeding the country's economic growth potential, among other things. [ABSTRACT FROM AUTHOR]

The accelerating depletion of fossil fuel reserves and the growing awareness about climate issues have put forth a plethora of interesting approaches that attempt to tackle the crucial problem of energy saving, specifically in buildings, known as a major energy consumer. Existing approaches tackle the problem of energy efficiency in buildings by proposing model-based approaches such as knowledge models (thermal, CO 2 , cost, etc.) and regressive models. However, different factors make the building of knowledge models particularly challenging, including the very complicated interaction between several heterogeneous phenomena that can impact the use of energy in buildings like the buildings envelope characteristics, their positions, the weather conditions, but also the occupant's behavior is a critical issue in the process. More Recently, techniques from machine learning (ML) to support energy saving in buildings gained increased interest. They learn from collected historical data a model that forecasts the future energy behavior of the building. Although occupant's behavior to save energy in the building is far from trivial, has received less attention from these studies. This paper takes on this challenge and proposes an energy management system based on historical data thanks to case-based reasoning approach. We guide the occupant by proposing an action plan (opening/closing of doors/windows, etc.) to help him in the process of improving his indoor comfort (thermal, air quality, luminosity, etc.) without using more energy if not using less. To encourage the occupant to trust the inference mechanism learnt and cooperate with the energy management system, this approach generates explanations arguing the proposed action plan. We assess the performance of our energy management technique on real-word data collected from a research building at the University of Grenoble, France. • Model-based systems are difficult to develop. • Case-based reasoning models building behavior without the need for a building model. • Explanation fosters cooperation between the user and the energy management system. [ABSTRACT FROM AUTHOR]

Peak power consumption is becoming an increasing problem worldwide and particularly in France during the late afternoon winter periods. This paper describes the experimental and numerical studies carried out to investigate the potential of a PCM (phase change material) – Air heat exchanger, conceived for load shifting purposes. The objective is to possess the necessary tools for the development of advanced control strategies taking into account various factors: peak power reduction, thermal comfort and indoor air quality. The experimental approach involved the construction of a heat exchanger coupled to an experimental cell. The heat storage system is composed of a set of PCM (paraffin) plates, embedded in the exchanger and integrated in a ventilation system. In parallel, a numerical model was developed using the apparent heat capacity approach and the finite differences method. Furthermore, a series of characterization tests was conducted and the experimental data were used for model calibration and validation. The model was then coupled with a building simulation program, presenting good agreement between the integrated model prediction and the experimental data. Finally, a preliminary control strategy of the test cell is presented along with results demonstrating the capabilities of such system for peak load management. [ABSTRACT FROM AUTHOR]

Saving energy is crucial for all sectors following the new framework presented by the European Commission to drive continued progress towards a low-carbon economy. Many studies focus on the residential sector, transport and energy-intensive industries, but there is a lack of tools to help decision makers in non-energy intensive industry (NEI). This paper presents the first bottom-up energy model developed for this sector. This prospective modeling enables us to analyze the impact of heat recovery using heat pumps (HP) in industrial processes up to 2020 in the French food and drink industry (F&D), the biggest NEI sector. The technology has high potential in this sector and may be eligible for Energy Saving Certificates. Our model determines the differentiated cost for energy savings in response to incentive policies under the ESC mechanism at a 4-digit level of NACE classification. Sensitivity analyses also show how gas prices and electricity carbon footprints impact on HP penetration. Our study of this particular sector shows that the model could be a useful decision-making tool for assessing potential energy savings and could be extended to other sectors of NEI industry for more efficient subsectoral screening. [ABSTRACT FROM AUTHOR]

This study aims to examine the relationship between military expenditure and environmental sustainability in developed Mediterranean countries: Greece, France, Italy, and Spain. Sustainable economic growth is strictly related to energy consumption which leads to producing a higher level of carbon emissions. Besides, there may be a nexus between military expenditures and environmental pollution. This study focuses on developed Mediterranean countries since carbon emissions and greenhouse gas emissions are relatively high in these countries. Furthermore, France and Italy are the top countries in terms of total military spending. We investigate the relationship between military expenditure and carbon emissions using the Global Vector Autoregression model proposed by Pesaran et al. (J Bus Econ Stat 22 129:162, Pesaran et al., J Bus Econ Stat 22:129–162, 2004) and Dees et al. (J Appl Econ 22(1):38, Dees et al., J Appl Econ 22:1–38, 2007) between 1965 and 2019. The empirical findings indicated that the relationship between carbon emission and military expenditure should be taken into account from a global perspective for environmental sustainability, and an increase in the global military expenditure seems to be very harmful to the global environment. It can be concluded that country-based prevention cannot provide the desired solution in combating environmental pollution. [ABSTRACT FROM AUTHOR]

In both the US and French building sectors, significant efforts have been undertaken to reduce the environmental impacts of new constructions notably their fossil energy consumption and related carbon emissions. This paper summarizes the results of a comparative evaluation of optimal design specifications for office buildings for selected locations in both US and France using life cycle cost analysis approach. First, an overview of both the US and French approaches for developing building energy efficiency standards and design of high performance buildings is outlined. Then, a general approach for design optimization of energy efficient office buildings is presented. Finally, selected results of the optimal analysis are discussed. In particular, it is found that optimizing life cycle costs (LCC) resulted on average in 30% in primary energy savings for office buildings located in the US and 40% savings in France. However, it is found that LCC-based optimal building designs do not meet the French energy efficiency RT 2012 standard. When accounting for typical operating conditions, photovoltaic (PV) panels are needed in order to comply with the RT 2012 required thresholds for the total primary energy consumption of the office buildings located in the French cities considered in the analysis. [ABSTRACT FROM AUTHOR]

• A retrospective material and energy flow analysis of the European flat glass industry over 75 years. • A long-term study of the use of raw materials and energy for architectural glass manufacturing. • A comparative analysis of the intensity and the total emissions of CO 2 resulting from the manufacturing process. • CO 2 emissions fell significantly until the 1980s, but have then levelled off and even increased. • Discussion on measures and research needs to foster decarbonisation through reuse and recycling of glazing. In our built environment, flat glass is an indispensable material. Its production requires the mining of raw materials and the use of fossil fuels and results in the emission of pollutants including CO 2. In Western European countries, these emissions have been the target of a series of energy efficiency measures and emission reduction policies since 1945. Beginning with that year, this article studies the material history of the flat glass industry in Belgium, France and the EU and analyses the evolution of the flows of materials, energy and CO 2 related to the manufacturing process. Based on a retrospective material and energy flow analysis (MEFA), the objective is to assess the environmental footprint of the architectural flat glass sector and to provide an understanding of the socioecological patterns that have shaped its metabolism. Based on an extensive data collection, this paper is the first publication of long-term time series on the manufacturing of architectural glass. The findings reveal two major concerns: on the one hand, energy efficiency measures have weakened ever since the 1990s, despite the tightening of the European environmental policies; on the other hand, the demand for architectural glass in the EU remains particularly high, resulting in a production rate that uses considerable energy and exploits a large amount of raw materials. The relative decoupling of the energy and CO 2 intensities seems to have reached a threshold and has not resulted in an absolute decoupling of environmental burdens from industrial growth. We discuss measures and research needs to support a decarbonisation of the flat glass sector. [ABSTRACT FROM AUTHOR]

The article analyzes mechanical wind-powered water supply systems situated in southern France and northern Germany in the time period between 1880 and 1950, when wind energy was not yet framed as a renewable, but as a rural, decentralized, and manageable solution to generate energy. Using a local approach, I highlight wind energy use in rural areas of Western societies as part of the non-synchronical process of technological modernization that unfolded at the same time as electrification, industrialization, and the implementation of large technological systems. I develop my argument in two steps. First, I provide the micro-historical case studies to examine socio-technological contexts that motivated people to advocate for the use of wind energy in times of electrification and industrialization. Second, I show the connection to general and specific contemporary discourses about wind energy and energy futures in order to provide evidence that the wind projects were part of rural modernization processes. [ABSTRACT FROM AUTHOR]

The EU27 countries exert significant influence on the global patterns of the CO 2 -Emissions-Water-Energy (CWE) nexus. However, whether the associated benefits are similar for all countries is unclear. In this paper, an EU27 multiregional input-output model, at a sector level to identify the inter-regional and -sectoral CWE flows, and clarify the regional, sectoral and worldwide patterns of EU27 CWE network is presented. The results revealed an environmental inequality across the EU27 and impacts on the rest of the world. The EU27 countries contributed 1.4 Gt less CO 2 emissions, 64.5 Gm3 less water utilisation and 49 EJ less energy consumption, compared to the rest of the world while generating the equivalent economic output in 2014. This has dramatic effects upon the global environment. Germany, France and Italy are the biggest beneficiaries in the CWE nexus in the EU27. It is recommended that the EU27 provide more technical support to upstream countries in the EU and elsewhere to strive to improve their resource utilisation efficiencies. • The critical Carbon-Water-Energy (CWE) flows across the EU27 are analysed. • The regional, sectoral and worldwide patterns of EU27 CWE network are clarified. • An environmental inequality across the EU27 and impacts on the rest of the world. • Germany, France and Italy are the biggest beneficiaries in the CWE network of EU27. [ABSTRACT FROM AUTHOR]

• A spatio-temporal analysis is proposed to simulate the household electricity demand related to electric appliances end-use. • A combination of a sample survey from 54 households in a urban context allowed for determining the influencing factors on possession of electric appliances. • The frequency of usage as well as the time of use of most of these appliances depend on the active occupancy of the household members. • The maximum energy demand is related to a middle-aged couple accommodated in a large dwelling. • The energy consumption per person is more efficient when various persons share the dwelling together. To analyse residential electricity consumption/demand, it is often broken down into five end-uses, namely lighting, hot water, space heating/cooling, cooking, and domestic appliances. Unlike other electricity end-uses, there is no specific method to determine the number of electric appliances in residential buildings, and it is difficult to estimate their pattern of usage due to household behaviour. The increasing demand of domestic appliance use in France in recent decades is attributed to advances in technology, increased dwelling size, and changes in lifestyle and comfort requirements, resulting in increased ownership and frequency of use of these appliances. Therefore, to gain a better understanding of the total demand, it is necessary to determine the variables impacting the ownership and utilisation of electric appliances. This paper provides a spatio-temporal analysis at a local scale, focusing on electric appliances in the residential sector. This analysis can be used to illustrate the areas where the application of energy efficiency measures can be improved. By identifying the socio-economic variables impacting electricity demand through micro- and macro-scale modelling techniques, we simulated the load profile of electric appliances, based on a survey of 54 households and national statistics regarding the daily activity of French people. The results demonstrate that size of dwelling, financial status, age of the reference person in the household, and household size and composition are the main variables determining the number of electric appliances owned by the household. These data are crucial for electricity demand forecasting, Demand Response and Demand-Side Management. [ABSTRACT FROM AUTHOR]

This article explores the effect of education and transportation infrastructure on foreign direct investment for the French economy over the period of 1965–2017. Economic growth, financial development and electricity consumption are also considered as additional determinants of foreign direct investment. In so doing, the SOR unit root test is applied in order to examine unit root properties of variables in the presence of sharp and smooth structural breaks in the series. To examine the presence of cointegration between the variables, the bootstrapping ARDL cointegration test is applied. The empirical results show the presence of cointegration between the variables. Education and transportation add to foreign direct investment. Financial development declines foreign direct investment. The relationship between electricity consumption (economic growth) and foreign direct investment is bidirectional. The nonlinear relationship between education (transportation infrastructure) and foreign direct investment is U‐shaped. [ABSTRACT FROM AUTHOR]

This article develops a quantile regression model to measure the magnitude of the direct rebound effect for residential electricity demand based on micro-level data from an original survey of a representative sample of 2356 French households. We explore the rebound effect for different groups of residents. Traditionally, debate has focused on decreased prices for energy services due to efficiency improvements and their effects on energy demand. The methodological innovation provided by this paper is that it implements two theoretical estimation strategies: (i) energy efficiency elasticity of the demand for energy services, and (ii) price elasticity of the demand for energy services. Our findings reject the hypothesis of a backfire effect in the context of residential electricity use. Specifically, based on energy efficiency elasticity, we provide evidence of a rebound effect of between 72% and 86% but with substantial heterogeneity among consumption quantiles. Our results show that the direct rebound effect has critical relevance for energy efficiency policy in the face of energy invisibility in France. • The rebound effect of residential electricity demand is estimated • The recent French PHEBUS survey and quantile regression are used • The results provide evidence of a rebound effect of between 38% and 86% • Findings reveal substantial heterogeneity among consumption quantile • The analysis suggests that the rebound effect has critical relevance for energy efficiency policymaking [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide an overview about the distribution of the environmental impacts arising from different domestic functions (i.e. storing and preparing food, washing dishes, watching television, reading, personal cleaning, washing, drying and ironing clothes, home cleaning, heating, cooling, lighting and mobility) typically performed within a common family home. The method has general validity but for reasons related to the availability of data in the literature it has been applied by way of example only in three EU countries: Italy, Germany and France. The study was performed by using Life Cycle Assessment (LCA) in accordance with international standard ISO 14067 for determining the carbon footprint of different alternative domestic components, mainly appliances, for each function, by exclusively exploiting data from scientific literature. The functional unit is defined comprising all most common referred domestic activities of a family of three members within a house of 100 m2. The study identified an optimal configuration and a worse one of the domestic components in terms of carbon footprint, showing how a wise choice of these can greatly affect the overall impact by reducing it compared to the worst by more than 22% in Italy, 45% in Germany and 56% in France. The average impacts between the optimal and the worst configurations of Germany are higher than Italy (+27%) and France (+44%). Considering the impacts among the domestic functions in the average configuration, mobility was the most impactful in all the three countries (35–48%), followed by heating (17–26%), personal cleaning (10–13%) and washing dishes (8–13%), while cooling is consistent only in Italy (13%), against 5% in Germany and 2% in France. The study also allowed to identify some generic criteria for defining the optimal configuration: the increasing in energy efficiency, the choice of the least impacting energy source depending on the geographical location, ensuring water savings and the early replacement of older domestic components. Finally, by comparing some common measures for improving the domestic sustainability, these criteria proved to be more effective than solar systems and improved electricity mix. The provided outcomes may be used by manufacturers for improving their product in a more sustainable way as well as by legislator and end user, respectively for boosting and choosing the greener domestic components. Image 1 • LCA for estimating domestic environmental impacts based on scientific literature. • Application to three EU countries: Italy, Germany and France. • Assessing Carbon Footprint of different alternative domestic components for each domestic function. • Determining the optimal and the worst configuration of domestic components to minimize the impacts. • Comparing possible improvements for minimizing carbon footprint. [ABSTRACT FROM AUTHOR]

This study offers a novel analytical approach on the relationships between renewable energy consumption, capital, labor force, new firm formation rate, and economic growth. It aims to investigate such causal relationships using different estimation techniques such as the ordinary least squares (OLS) model, dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and canonical cointegrating regression (CCR), along with necessary condition analysis (NCA), which are applied to data for France over the period 1987–2017. Our results show that all necessary conditions yield outcomes ranging from small- to large-sized effects on economic development. The French government should readdress its efforts towards encouraging more beneficial investments in renewable energy consumption. This study opens up new insights for policymakers to maintain environmental protection and ensure sustainable economic growth. Finally, the use of NCA reduces complexity and allows a better understanding of the relationships involved. [ABSTRACT FROM AUTHOR]

Globally, to build cities and communities more inclusive, safe, resilient and sustainable is one of the most important sustainable development goals. Eco-districts in cities emerged as an answer to current global environmental concerns and have been developed in France since the 1990s. The objective of this work is to gather operational feedback from sustainable neighborhood projects owners to better understand the key barriers of such projects and how to overcome them. A case study of the eco-district Les Tanneries, Lingolsheim showed that the carbon footprint of each inhabitant annually amounted to 4 tons CO2 equivalent, more than half of the French average. Rooms for improvements were clearly identified regarding transports and food carbon footprint. Indicators for energy consumption, social diversity and density reached the level of the eco-districts average. A governance review pointed out some superior practices such as the formalization of a specification requirements handbook, a competition between project management teams, and the use of neighborhood sustainability assessment tools to measure and track changes in performance. The validated tools and obtained results can be useful in building sustainable cities and even China's ecological civilization. [ABSTRACT FROM AUTHOR]

Buildings play a central role in energy transition, as they were responsible for 67.8% of the total consumption of electricity in France in 2017. Because of that, detecting anomalies (outliers) is crucial in order to identify both potential opportunities to reduce energy consumption and malfunctioning of the metering system. This work aims to compare the performance of several outlier detection methods, such as classical statistical methods (as boxplots) applied to the actual measurements and to the difference between the measurements and their predictions, in the task of detecting outliers in the power consumption data of a tertiary building located in France. The results show that the combination of a regression method, such as random forest, and the adjusted boxplot outlier detection method have promising potential in detecting this type of data quality problem in electricity consumption. [ABSTRACT FROM AUTHOR]

The building sector is responsible for 43% of France's final energy consumption and is strongly associated with a high environmental impact due to its high consumption of energy and natural resources. These impacts are significant in isolated islands. Due to its geographical isolation and an area of 2512 km 2 , Reunion Island has a heavily carbon-based economy with a high import rate of raw materials for the building sector. This study aimed to investigate the effect of electricity mix decarbonization on residential house environmental impact. The methodology consists of three parts: (i) evaluating environmental impacts of Single-Family Houses (SFH) using life cyce assessment(LCA), (ii) defining SFH typologies using the K-means clustering algorithm, and (iii) implementing energy scenario in LCA of SFH to assess decarbonization effect. The environmental results were particularly sensitive in the operational phase, with a decrease of 83% between 2020 to 2040 of the global warming potential (GWP). The structural phase highlights the weight of imports in the building sector, as a decrease of only 1% is observed. This study clearly shows the necessary energy transition for Reunion Island. In the structural phase, the study recommends that stakeholders reduce imports and increase the share of recovered materials to achieve a substantial reduction in impacts. [ABSTRACT FROM AUTHOR]

Worldwide, buildings are one of the main energy consumers and the improvement of their energy performance has attracted great interest and has been typically related to the optimisation, both design and operational, of Heating, Ventilation, and Air Conditioning (HVAC), lighting and DHW systems, to innovation in building materials, as well as to the integration of renewable technology in buildings. More recently, occupant behaviour has received increasing attention. Occupants' interactions with the building systems influence their energy consumption in diverse ways. Their behaviour may affect energy use just as the systems and materials may do. Researchers identified and highlighted various aspects of this occupant behaviour and were gradually led to the conclusion that its effect might be worth investigating. This study has a twofold aim. First, to present a general conceptual framework to define, monitor and eventually change user behaviour in buildings. This framework is called "event-driven"; events are distinct moments in time associated with a potentially problematic behaviour, and the framework aims at tracking, acting upon and reporting on these events. Second, we aim to demonstrate and discuss the application and the savings achieved by means of our proposed approach and in the case of such behavioural events, in the Challenger building of Bouygues, in France. [ABSTRACT FROM AUTHOR]

The sustainability of livestock systems can be assessed through their productive and environmental performance, the ecosystem services they provide or their resilience to hazards. We used a modelling approach to assess how key economic performance indicators respond to technical and market hazards in five different meat-sheep farms, across France and Ireland. Hazards were related to seven technical or economic variables: ewe fertility, prolificacy, lamb mortality, prices of light and heavy lambs, concentrate use and energy use. We used a mechanistic model to simulate farm functioning and assess farm performance over 3000 iterations, based on simultaneous random draws with hazards to the previously mentioned seven variables. We quantified this way (i) the compensatory effects of different types of technical and economic mechanisms that lead to more stable economic performance and (ii) the probability of economic collapse of meat-sheep farms through a diachronic analysis. We showed that variations in technical variables have larger effects on income variability than variations in economic variables. We also showed that the most resilient systems, i.e. those with the lowest coefficient of variation of net income, are those that combine a low level of inputs with at least two lambing periods per year. Short duration of pregnancy in ewes makes multiperiod lambing possible, which can buffer the variability of technical variables and enhance the adaptive capability of the system by offering the possibility to move empty ewes to a new batch for re-mating. We thus analysed for the first time farm economic resilience to combined technical and economic hazards, and highlighted the buffer and adaptive mechanisms of resilience, with a mechanistic model. [ABSTRACT FROM AUTHOR]

The energy consumption of an electric vehicle is primarily due to the traction subsystem and the comfort subsystem. For a regular trip, the traction energy can be relatively constant but the comfort energy has variation depending on seasonal temperatures. In order to plan the annual charging operation of an eco-campus, a simulation tool is developed for an accurate determination of the consumption of an electric vehicle throughout year. The developed model has been validated by comparison with experimental measurement of a real vehicle on a real driving cycle. Different commuting trips are analyzed over a complete year. For the considered city in France (Lille), the comfort energy consumption has an overconsumption up to 33% in winter due to heating, and only 15% in summer due to air conditioning. The urban commuting driving cycle is more affected by the comfort subsystem than extra-urban trips. [ABSTRACT FROM AUTHOR]