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This study reexamines the causal nexus among electricity consumption (EC) and economic growth (EG) for a panel of 31 countries in Latin America and the Caribbean between 1980 and 2021. We find that there are statistically significant feedback impacts among the research variables in the long run. A 1 percent augment in EC raises EG by 0.5 percent and a 1 percent augment in EG produces a 1.54 percent increase in EC which reflects the nature of the latter as a luxury good and implies a tradeoff between economy and environment, since although greater electrical infrastructure drives EG, the latter also increases the EC whose use in a non-responsible manner could lead to environmental degradation through higher CO2 emissions. Therefore, the main policy implication is that, it is necessary to promote EG based on infrastructure focused on sustainable development, ensuring the well-being of present and future generations.

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The prediction of domestic electricity consumption is relevant because it helps to plan energy production, among many other benefits. In this work a dataset was collected from one house in an urban city of north-east of Mexico. An ad-hoc acquisition system was implemented to collect the data using a smart meter and the open weather API. The data was collected every minute over a period of 14 months since November 5, 2022, to January 5, 2024. The dataset contains 605,260 samples of 19 variables related with energy consumption and weather data. This dataset is specifically tailored for predicting domestic energy consumption and understanding consumption behaviours, filling a void in the existing literature where such datasets for Mexico are scarce. Moreover, the multivariate nature of the dataset allows researchers to investigate and propose new techniques for forecasting or pattern classification using multivariate data collected in a real scenario.

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We conduct a sectoral analysis of electricity consumption during the Coronavirus disease 2019 (COVID-19) pandemic for the primary sectors that make up Colombia's unregulated and regulated markets. Applying a model of seemingly unrelated regression equations to examine data between February 2015 and May 2021, we evidence the recomposition of electricity consumption related to mandatory preventive isolation during the pandemic. Average consumption in the residential sector increased by 16.9% as working from home became prevalent. In contrast, unregulated market sectors subjected to quarantines presented a significant decrease in consumption, up to 32% in the financial sector. While industries that were not subjected to mandatory confinement, such as health, food (agriculture), and water supply, had no significant effect. Our results are relevant for informing demand forecasts and planning network expansions to guarantee the reliability of the supply as pandemic practices such as working from home become permanent.

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During the COVID-19 pandemic, policymakers needed to assess the impact of large monetary and fiscal policy interventions in as close to real time as possible-yet existing survey-based indicators are usually released monthly or quarterly. The use of high-frequency data to track economic activity has become widespread. This paper constructs a near real-time economic activity indicator for the Brazilian economy during the COVID-19 pandemic. Brazil's integrated national electricity sector, which covers over 98% of the population, allows us to construct an economic activity indicator based solely on electricity consumption data that are available at near real time and accounts for activity in the large informal sector of the economy. We construct our indicator by isolating the variability in electricity consumption that is not related to economic activity, then measure how well monthly and quarterly versions of our indicator track against standard economic indicators. The results show strong correlation with standard indicators, notably during economic shocks.

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Since developing countries experience economic and environmental sustainability challenges, it is desirable digging into the linkages between economic and environmental parameters. The purpose of this work is to evaluate the existence of the environmental Kuznets curve (EKC) theory (i.e., the inverse U-shape connection between real GDP per capita and per capita carbon dioxide emissions) in the sample of 11 developing countries. By using balanced annual panel data in the period between 1992 and 2014 and two alternative estimation techniques, we explored the potential inverted U-shaped linkage between carbon dioxide emissions and real GDP per capita in the sample of interest. For analysis purposes, Pedroni and Westerlund co-integration techniques are employed. Then, fully modified ordinary least squares, pooled mean group methods are applied for long-run parameter estimations. And, the Dumitrescu-Hurlin causality approach is employed for causal directions. Firstly, this work's findings provide the supportive evidence to the inverse U-shaped linkage in the long-run, indicating that an increase in real GDP per capita and electricity consumption tends to mitigate long-run carbon dioxide emissions in the developing countries, for the whole sample. Secondly, the country-specific findings suggested the presence of EKC theory for Brazil, China, India, Malaysia, the Russian Federation, Thailand, and Turkey. It implicated that these countries are on the path of attaining environmental sustainability in the long-run. However, Mexico, Philippines, Indonesia, and South Africa failed to lend credence to the EKC theory. It manifested that these countries need to design strategies directed to reduce carbon dioxide emissions from economic activity and electricity generation through efficiency improvement or promotion of renewables. Finally, bidirectional causal links are observed among all the variables of interest. The findings suggest that country-specific targeted action plans should be implemented to ensure the environmental sustainability in the developing world.

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Cities are the point of concentration for most of the current environmental problems, due to their fast growth and their dependence on ecosystems beyond urban limits. Changes in cities and cultural patterns that shape modern life have accelerated the metabolism of cities and consequently have negatively impacted the environment. Different approaches have been explored to understand and manage this situation. In this sense, various studies have been developed regarding the impacts of feedback information on water and electricity consumption in order to determine and understand ways to manage domestic demand. This paper presents the results obtained through the execution of an experiment on the effects of feedback information on water and electricity consumption at the household scale. During the study, participating households were exposed to different types of information, including their own consumption, comparisons with their neighbors and saving tips. The results obtained show that feedback information has a significant but differentiated effect on water and electricity consumption, and that the way in which feedback information is perceived is different in both flows.

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The objective of this study is to investigate the role of democracy, ecological footprint, economic growth, and globalisation in enhancing sustainable electricity consumption in an ecological reserve-based country of Brazil over the period 1971-2014. To achieve this objective, the minimum Lagrange multiplier (LM) unit root and Bayer-Hanck combined cointegration tests are applied. The model is estimated using the fully modified ordinary least squares (FM-OLS) and dynamic ordinary least squares (DOLS) estimation procedures. The empirical results suggest that all the variables have a positive and significant effect on electricity consumption. This implies that increasing the level of these variables would stimulate electricity consumption. The long-run causality results indicate a one-way causality running from ecological footprint, democracy, and globalisation to electricity consumption. The results further discover that causality flows from ecological footprint, democracy, and globalisation to economic growth. In addition, a long-run bidirectional causal relationship between electricity consumption and economic growth is uncovered. In the short run, the result validates a bidirectional causality between ecological footprint and electricity consumption. More so, electricity consumption causes economic growth and democracy, whilst economic growth causes globalisation. The results are validated by the innovation accounting tests. The policy implication of the findings is that ecological-based conservation policies could have negative consequences on economic growth and electricity consumption because of a significant dependence of these two variables on the ecological footprint. Therefore, to guarantee sustainable electricity consumption, sufficient and sustainable green energy and optimum energy mix should be encouraged by the stakeholders.

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Improving and managing the electricity efficiency in hotel facilities is essential to reduce the hotel operation costs and its environmental impacts. The data presented shows the evolution of the electricity consumption and management between 2013 and 2015 in two hotel facilities in Cuba (one beach hotel and one city hotel). The data additionally includes the daily measures used to develop control tools for an energy management system. The data presented in the article relates to the research study: Tools to improve forecasting and control of the electricity consumption in hotels Cabello et al., 2016, and it corresponds to the energy audits developed in one beach hotel (Hotel A) and one city hotel (Hotel B) in Cuba.

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This study investigates the environmental Kuznets curve (EKC) hypothesis for Brazil, Russia, India, China and South Africa (BRICS) over the period 1990-2014, while considering agricultural activities, energy use, trade openness and mobile use as driving forces of environmental degradation. The empirical results verify an inverted U-shaped connection between carbon emissions and economic growth. This study confirms the unfriendly impact of agriculture on the environment. Electricity consumption and trade openness likewise exhibit similar impacts on carbon emissions. Mobile use however reduces pollution. A unique revelation from this study is that the interaction between electricity consumption and agricultural activities has an additional pernicious effect on the environment. The methodologies applied for testing the impact of selected independent variables on carbon emissions in BRICS are the Dynamic Ordinary Least Squares (DOLS) and the Fully Modify Ordinary Least Square (FMOLS) for long run regression. Empirical evidence confirms that agriculture exerts a negative impact on the environment in BRICS countries. This study therefore recommends the adoption of cleaner energy processes and enabling high-tech and clean foreign investment.

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Abstract The objective of this paper is to present a mathematical representation by Regression Analysis that enables the projection of electricity consumption according to the built area and population in Higher Education Institutions (HEI) and to define an Indicator that contemplates the most significant variable in consumption. of electric power. The Null Hypothesis -H0 is that in a HEI the most appropriate indicator is the Kilo Watt Hour per square meter (kWh / m2) as proposed by the Ministry of Planning and Management - MP. The research universe is 2,368 HEI, identified in a report from the Ministry of Education (2015). As Sample and case study, data from the thirteen Campi of the Federal Technological University of Paraná (UTFPR) are used. As a computational tool we use the IBM SPSS Statistics Base Software for Windows version 23 from SPSS Inc .. For the considered Sample and research design, the conclusion is that the null hypothesis is rejected accepting that the most significant indicator is the kilo. Watt Time per user (kWh / user). This conclusion does not exclude the relationship between constructed area and Energy Consumption, but reveals that it is not as significant as the number of individuals in HEI for this sample.

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Abstract Electricity is undoubtedly one of the most important resources in the modern world. As the demand for electric energy increases, conventional resources that are transformed into electric energy are being exhausted, generating a need to search for alternative sources, resulting in a significant increase in energy costs. This study presents an integrated project of an intelligent microgrid and energy management aimed at reducing energy costs. At the Federal University of Paraná (UFPR), electricity represents an annual cost of over BRL 13 million, which is the third largest operating expense of the university. In addition, the public education budget in Brazil has been decreased in recent years. Therefore, this study was conducted within the scope of UFPR and aimed to analyze three alternatives to reduce electric energy costs: i) demand management through an analysis of energy bills, ii) migration to the free energy market, and iii) the development of an in-house photovoltaic generation facility. A computational tool to optimize the contracted demand and simulate the annual savings with the free market and distributed generation projects was developed using Microsoft Excel. Payback, the net present value, and the internal rate of return were calculated. Finally, the economic viability of all alternatives was proven, with demand management demonstrating an economic potential of greater than BRL 500,000 per year, use of the free market saving more than BRL 300,000, and the developed in-house photovoltaic generation system achieving an economic impact of more than BRL 600,000 per year.

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Solid waste, including municipal waste and its management, is a major challenge for most cities and among the key contributors to climate change. Greenhouse gas emissions can be reduced through recovery and recycling of resources from the municipal solid waste stream. In São Paulo, Brazil, recycling cooperatives play a crucial role in providing recycling services including collection, separation, cleaning, stocking, and sale of recyclable resources. The present research attempts to measure the greenhouse gas emission reductions achieved by the recycling cooperative Cooperpires, as well as highlight its socioeconomic benefits. Methods include participant observation, structured interviews, questionnaire application, and greenhouse gas accounting of recycling using a Clean Development Mechanism methodology. The results show that recycling cooperatives can achieve important energy savings and reductions in greenhouse gas emissions, and suggest there is an opportunity for Cooperpires and other similar recycling groups to participate in the carbon credit market. Based on these findings, the authors created a simple greenhouse gas accounting calculator for recyclers to estimate their emissions reductions.

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