Sustainable Energy Consumption Research Articles

Optimized Smart Home Energy Management System: Reducing Grid Consumption and Costs through Real-Time Pricing and Hybrid Architecture

Utility authorities utilize various methods to promote end-user energy conservation, including higher tariff rates and demand response (DR) strategies. This paper investigates an Optimized Smart Home Energy Management System (OSHEMS) designed to minimize grid dependence and energy bills while ensuring reliable load delivery. A hybrid architecture prototype was implemented, integrating a photovoltaic (PV) array, battery storage, and the electrical grid. The system combines Maximum Power Point Tracking (MPPT) solar chargers and Pure Sine Wave (PSW) inverters for efficient energy management. The Home Energy Management Whale Optimization Algorithm (HEMWOA) was employed to optimize energy usage and achieve cost reduction while enhancing user comfort. Real-time pricing (RTP) tariffs incentivizing flexible energy consumption during peak hours were incorporated. OSHEMS manages, schedules, and monitors energy sources and appliances, determining the optimal consumption mix. Experimental results demonstrate a significant decrease in grid reliance (46.6%) and energy costs (57.7%) compared to non-scheduling scenarios. These findings highlight the potential of OSHEMS in promoting sustainable and cost-effective energy consumption in smart homes.

Sustainable energy consumption and finance in the presence of risks: Towards a green economy

Moving towards a green economy, sustainable energy consumption and financial development amid mounting risks moved to center stage of policymaking and academia. Strengthening energy consumption from renewable sources is integral to the attainment of the overarching sustainable development goals of the Paris Agreement. The study employs data from 19 OECD economies spanning from 1990 to 2020 to explore the effect of risks on sustainable energy consumption. Using a multifaceted empirical approach -- comprising Panel OLS, MG estimators, quantile regression analysis and local projection approach -- results establish a key role for political, economic and financial risks in determining energy consumption from renewable sources. Results for the impact of finance indicators on sustainable energy consumption provide robust, though mixed, findings on how to bridge the climate financing gap. Our findings underscore the significant positive influence of human capital development, economic growth, economic openness and oil prices on sustainable energy use. It is further shown that decreasing carbon emissions and making sustainable energy more affordable should be on the central agenda of policymaking for promoting environmental sustainability. A multi-lever strategy is needed when making environmental policies while distributional heterogeneity should also be considered.

Retraction Note: The influence of economic and non-economic determinants on the sustainable energy consumption: evidence from Vietnam economy.

Retraction Note: The influence of economic and non-economic determinants on the sustainable energy consumption: evidence from Vietnam economy.

Navigating towards sustainable energy consumption behavior of households in Lahore Division of Pakistan: consumer’s energy conservation preferences as a catalyst for change

Navigating towards sustainable energy consumption behavior of households in Lahore Division of Pakistan: consumer’s energy conservation preferences as a catalyst for change

Energy literacy among young adults in the European countries

Energy literacy is an essential prerequisite for informed and sustainable energy consumption habits. Our paper focuses on factors influencing young adults’ attitudes and behaviours and their knowledge of sustainable energy consumption practices. The research was conducted in five European countries, Austria, Croatia, Greece, Slovenia and Poland, and data were collected from 219 young adults between the ages of twenty-nine and thirty-nine. The methods used are statistical analyses, including principal component analysis, a technique for analysing large data sets and identifying influencing factors. We used a statistical software package (SPSS) for the analyses. Our analysis revealed five significant factors influencing the energy literacy of young adults. The key factors were education and awareness, investment in energy efficiency, age and gender, climate change and environmental protection, sustainable lifestyle and social environment. Policymakers, educators and other stakeholders can work towards creating a more energy-literate and sustainable society by understanding the key factors that influence energy literacy.

LightGBM-, SHAP-, and Correlation-Matrix-Heatmap-Based Approaches for Analyzing Household Energy Data: Towards Electricity Self-Sufficient Houses

The rapidly growing global energy demand, environmental concerns, and the urgent need to reduce carbon footprints have made sustainable household energy consumption a critical priority. This study aims to analyze household energy data to predict the electricity self-sufficiency rate of households and extract meaningful insights that can enhance it. For this purpose, we use LightGBM (Light Gradient Boosting Machine)-, SHAP (SHapley Additive exPlanations)-, and correlation-heatmap-based approaches to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. First, we use LightGBM to predict the ESSR of households and identify the key features that impact the prediction model. By using LightGBM, we demonstrated that the key features are the housing type, average monthly electricity bill, presence of floor heating system, average monthly gas bill, electricity tariff plan, electrical capacity, number of TVs, cooking equipment used, number of washing and drying machines, and the frequency of viewing home energy management systems (HEMSs). Furthermore, we adopted the LightGBM classifier with ℓ1 regularization to extract the most significant features and established a statistical correlation between these features and the electricity self-sufficiency rate. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. The LightGBM-based model offers a global view of feature importance but lacks detailed explanations for individual predictions. For this purpose, we used SHAP analysis to identify the impact-wise order of key features that influence the electricity self-sufficiency rate (ESSR) and evaluated the contribution of each feature to the model’s predictions. A heatmap is also used to analyze the correlation among household variables and the ESSR. To evaluate the performance of the classification model, we used a confusion matrix showing a good F1 score of 0.90. The findings discussed in this article offer valuable insights for energy policymakers to achieve the objective of developing energy-self-sufficient houses.

The Evaluation of Use Photovoltaics (PV) in Renewable Energy Technology as Sustainability Strategies

The United Nations (UN) proposed the Sustainable Development Goals (SDGs) to make the earth peaceful and prosperous by 2030. Abundant water and food supply, sustainable energy consumption, climate change mitigation, and sustainable energy consumption are considered the keys to better sustainability. For example, the food sector is responsible for 30% of global energy consumption, 21-37% of greenhouse gas (GHG) emissions, and 70% of global water withdrawals. Integrating renewable energy into a country's energy mix largely depends on the implementation of renewable energy policies. Sustainably developed solar photovoltaic options to meet energy. The main focus is to achieve energy security and independence with special emphasis on solar energy, to drive transformative change towards widespread adoption of renewable energy. The research method uses a literature study and the findings are in the form of the direction of the Indonesian Government's policy setting, namely the National Energy General Plan (RUEN) which is the basis for regulation through Presidential Regulation Number 79 of 2014 with the aim of changing the increase in the national energy share to 23% by 2025. This regulation aims to create opportunities for PT PLN (Persero) customers in the household, business, government, social, and industrial sectors to be actively involved in the utilization and management of renewable energy in a sustainable manner and provide insight into the sustainability of solar energy, including environmental and economic development.

Application of hybrid systems for sustainable energy consumption

Application of hybrid systems for sustainable energy consumption

Municipal Energy Efficiency in Portugal: An Analysis of Electricity and Natural Gas Consumption

Analysing energy consumption efficiency is essential for understanding energy resource consumption patterns, identifying the economic consequences, and developing effective public policies. The study investigates energy consumption efficiency levels in Portuguese municipalities in order to analyse disparities in energy consumption efficiency. The aim is to observe the possible relationship between population density and the energy consumed by residents. The study uses the DEA model to detect benchmarking patterns, inefficiencies, and opportunities for improvement in energy consumption practices. The results suggest that there are serious disparities in energy consumption efficiency between Portuguese municipalities and a significant positive correlation between population density and the amount of energy consumed. The disparities can be attributed to the different levels of adoption of efficient energy consumption practices. The results point to the need to define public policies aimed at promoting more efficient energy consumption practices. The research emphasises the importance of implementing more effective public policies that encourage the adoption of sustainable energy consumption practices by residents. The conclusions have important practical implications for the formulation of public policies aimed at local energy efficiency and the development of sustainable energy consumption.

Smart and Sustainable Energy Consumption: A Bibliometric Review and Visualization

This paper presents a comprehensive bibliometric review and visualization of smart and sustainable energy consumption, delving into the challenges and opportunities of developing renewable and non-renewable energy sources. The study examines research trends and emerging themes about integrating smart solutions and sustainable energy resource consumption. The analytical methods used involve thoroughly analyzing empirical data, case studies, and review papers to map the research landscape. The results highlight dominant research topics, influential authors, and publication timelines in this field. The review identifies the key challenges in harnessing renewable and non-renewable energy sources, including the need for reliable energy sources, energy storage systems, and smart grid technologies. The paper concludes with insights into the most effective practices for promoting smart and energy-efficient methods while emphasizing the complexity of sustainable energy solutions.

Federated Learning-Based Prediction of Energy Consumption from Blockchain-Based Black Box Data for Electric Vehicles

In modern society, the proliferation of electric vehicles (EVs) is continuously increasing, presenting new challenges that necessitate integration with smart grids. The operational data from electric vehicles are voluminous, and the secure storage and management of these data are crucial for the efficient operation of the power grid. This paper proposes a novel system that utilizes blockchain technology to securely store and manage the black box data of electric vehicles. By leveraging the core characteristics of blockchain—immutability and transparency—the system records the operational data of electric vehicles and uses federated learning (FL) to predict their energy consumption based on these data. This approach allows the balanced management of the power grid’s load, optimization of energy supply, and maintenance of grid stability while reducing costs. Additionally, the paper implements a searchable black box data storage system using a public blockchain, which offers cost efficiency and robust anonymity, thereby enhancing convenience for electric vehicle users and strengthening the stability of the power grid. This research presents an innovative approach to the integration of electric vehicles and smart grids, exploring ways to enhance the stability and energy efficiency of the power grid. The proposed system has been validated through real data and simulations, demonstrating its effectiveness and performance in managing black box data and predicting energy consumption, thereby improving the efficiency and stability of the power grid. This system is expected to empower electric vehicle users with data ownership and provide power suppliers with more accurate energy demand predictions, promoting sustainable energy consumption and efficient power grid operations.

From responsible sourcing of wastes to sustainable energy consumption in the blue hydrogen supply chain: Case of nearshoring in Nuevo Leon

Despite global uncertainties, Mexico has become the largest supplier to the United States, emphasizing its growing role in cultivating resilient supply chains. Nearshoring practices from Mexico and Canada to the U.S. present new production opportunities. Increasingly, U.S. consumers place a premium on sustainable consumption, so blue hydrogen plants must be sourced responsibly. This paper firstly goes beyond economic motivations, aiming to formulate a multi-stage methodology for assessing suppliers of municipal solid waste for blue hydrogen plants, marking a pioneering effort in catering to the environmentally conscious preferences of U.S. consumers. The purpose of this work is to examine a case study of Blue Hydrogen production in Nuevo Leon, emphasizing the importance of developing responsible sourcing criteria for waste suppliers to limited blue hydrogen plants. The developed hybrid approach integrates various methodologies, including Critical Systems Heuristics (CSH), fuzzy rough sets, hierarchical fuzzy rough analysis, Fuzzy rough WASPAS, TOPSIS, and Best-Worst Method (BWM), providing a comprehensive framework for decision-making under uncertainty. Key findings include the identification of water conservation (E2) and job creation (S2) as the top environmental and social criteria, respectively. Supplier WC2 was identified as the top-performing waste collector, achieving a final score of 4.77. This structured methodology prioritizes product categories for hydrogen consumption, considering sustainability criteria and U.S. consumer preferences, thereby offering valuable insights for businesses navigating this evolving landscape.

Transforming Indonesian Washing Machines into Efficient Wind Generators

People's consumption of household electronic devices is increasing, leading to higher energy demand in Indonesia, with washing machines being a significant contributor. This study explores repurposing used washing machine dynamos into electricity generators for windmills. Researchers used an LG washing machine dynamo and N52 neo super magnets, testing pulley diameters of 12 cm, 15 cm, 18 cm, and 20 cm. Results showed that larger pulleys increased generator output, with a 20 cm pulley producing 26 volts, 1.3 amperes, and 2525 rpm. However, the efficiency was low at 8.69%, indicating a need for further optimization. This approach has potential for sustainable energy solutions and reducing electronic waste. Highlight: Repurpose Dynamos: Converts washing machines to windmill generators, reducing electronic waste. Efficiency Challenge: Larger pulleys improve output but efficiency is only 8.69%. Sustainable Impact: Offers potential for sustainable energy and lower household consumption. Keyword: household electronics, energy consumption, washing machine dynamo, windmill generator, sustainable energy

Impact of Economic Awareness on Sustainable Energy Consumption: Results of Research in a Segment of Polish Households

This manuscript explores the relationship between the economic awareness (as a part of energy awareness) of Polish households and their sustainable energy consumption practices. Sustainable consumption is measured by the frequency of behaviors such as turning off electrical devices when not in use, removing mobile device chargers from sockets, switching off lights when leaving a room, preferring showers over baths, using washing machines and dishwashers only when full, and purchasing energy-efficient appliances and light bulbs. Economic awareness is gauged through variables such as knowledge of electricity tariffs, understanding of electric bill components, awareness of electricity prices, exact knowledge of electricity expenses, electricity usage in kWh, knowledge of effective energy-saving methods, and familiarity with the energy efficiency classes of appliances and light bulbs. This study presents profiles of households with high and low economic awareness regarding their electricity expenditures and examines how these profiles differ in their sustainable energy consumption behaviors. This research is based on a survey of 1407 Polish households conducted online in 2023. Data collected from the survey were subjected to statistical analysis and are presented in tables and graphs. The findings are discussed in the context of the existing literature in the field, highlighting the implications of economic awareness on sustainable energy consumption practices. This research contributes to understanding how economic knowledge influences energy-saving behaviors among Polish households, providing insights for policymakers and energy conservation initiatives. One of the key findings of this paper is the significant association between economic awareness, energy-saving knowledge, and the adoption of sustainable energy consumption behaviors among Polish households. This study reveals that households with higher levels of economic awareness demonstrate a notably higher frequency of practices related to sustainable energy consumption compared to those with lower economic awareness. Similarly, households equipped with greater knowledge about energy-saving techniques exhibit a higher propensity to adopt energy-efficient behaviors. This underscores important roles of economic literacy and education in fostering behavioral changes towards more sustainable energy practices, highlighting the importance of targeted interventions and educational campaigns aimed at enhancing economic awareness and promoting energy-saving knowledge among consumers.

Sustainable Energy Consumption Analysis through Data Driven Insights

Energy is the backbone of our society, supporting our daily activities and driving progress. It plays a crucial role in shaping our modern way of life. The future of global energy consumption is influenced by many factors, including demographics, economic dynamics, technological developments, political actions, environmental demands and geopolitical considerations. As the world's population continues to grow and urbanize, the demand for energy is increasing. At the same time, rapid technological innovations are shaping the energy landscape and changing production, distribution and consumption patterns. In the midst of this development, it is very important to optimize energy consumption, accurately anticipate needs, curb climate change, limit emissions of greenhouse gasses, fight against pollution and promote sustainability. This study includes an in-depth analysis of historical consumption trends, assessing the multiple benefits of renewable energy integration, estimating carbon emissions, formulating practical policy recommendations and providing empirically informed insights. The work is based on various data obtained from platforms such as Kaggle and using advanced visualization techniques such as Power BI dashboards. The study provides invaluable perspectives on future energy needs, the penetration of renewable sources into the energy mix, and the strategic needs to achieve sustainable energy use.

Who brings emissions home? Comparing female and male breadwinner households by matching techniques

This paper tests the hypothesis that female and male breadwinner household present significant differences in the greenhouse gases (GHG) emissions patterns induced by consumption. We investigate this issue by studying a sample of consumption basket of Spanish households for 2008, 2014, and 2018, linking consumption levels with emissions by means of input-output analysis. Once a vector of GHG emissions have been calculated for each household sampled, we apply the Propensity Score Matching estimator to analyze the mean difference between households with female and male breadwinners, finding a significant negative effect of having female breadwinner households on the GHG emissions patterns derived by household energy consumption, mainly due to the larger use of private transport by male breadwinner households. These results contribute to the growing demand for studies linking environment and gender and to expose the role of women in sustainable energy production and consumption. Therefore, policies that encourage the inclusion of women in different economic activities are also likely to have climate related benefits.

Sustainable energy consumption – Empirical evidence of a household in Poland

There is an expected increase in the demand for electricity from households in European countries. The outcome of the growing proportion of renewable energy sources in the energy supply mix should result in improved customer awareness regarding their electricity usage. Additionally, they must assume a more proactive role in overseeing their electricity usage. Innovation and pollution management have become crucial catalysts for promoting sustainable economic development and environmental protection. This is a response to the increasing threats posed by climate change. This study addresses this existing research gap in sustainable energy consumption. The research aims to examine the advantages of replacing traditional sources of heating with renewable ones. The empirical case study of households in Poland serves as an illustration of the theoretical foundation. The purpose of the study entails the construction of a multi-equation econometric model describing the mechanisms of electricity consumption in a specific household. The model hypothesis indicates that the model should take the form of a system of interdependent equations. The following will be described: the monthly volume of electricity consumption, the cost of this energy payment (in PLN), and the price per one MWh in a given month. Monthly time series from September 2015 to June 2023 were used. The resulting time series amounted to a count of 94 statistical observations. The results in the form of a multi-level empirical econometric model indicate that the economic, environmental, and social benefits of using renewable sources of heating can make a significant contribution to reducing fossil fuel consumption and CO2 emissions. In the context of growing environmental awareness and the need to reduce greenhouse gas emissions, heat pumps are becoming an increasingly important element in the discussion of the future of heating. Their role in transforming the energy sector in the direction of sustainability is crucial.

Physical and psychological rehabilitation for common weightlifting injuries

In the process of weightlifting, there is an increased load on both the respiratory system, the cardiovascular system, and on individual parts of the nervous system. At the same time, special attention is paid to the possibilities of providing a stable body functioning after the cancellation of treatment course and the corresponding pharmacological support of athletes with treatment schedule or without it. The novelty of the study is determined by the need to ensure constant and stable work of the cardiovascular system. The authors note that this is possible both when the body performance indicators return to the level before injury, and in conditions of returning to original sports results. It is determined in the paper that the use of the instrumental model will make it possible to develop sustainable energy consumption and coordinate the balancing of loads on an athlete during the period of recovery after injury. Model formation is based on uniform signals in a correlated random process in a simulation model. The practical significance of the study is determined by the need to structure the training loads in the post-traumatic period. This reduces a number of physiological and psychological stresses on a person and allows increasing in the long term the loads that the athlete plans to utilise after returning to the sports sector.

Smart life and sustainable development: a comparative analysis on energy and water efficiency in China and the EU

Smart life relies on huge volumes of data analysis, which makes data centers become important infrastructure in smart city areas. Nowadays, data centers are constructed in many countries and have become increasingly large electricity consumers. The consumption of electricity is caused not only by the servers of data centers but also by the cooling systems. Meanwhile, data centers also demand water - cooling methods, which result in water consumption. As for sustainable development, water and energy consumption are huge challenges. Laws and rules are necessary for utilizing efficiently relevant sources. This paper will analyze China and the European Union (EU) as two examples of jurisdictions to compare how the governments regulate the construction of data centers to implement the thrift of electricity and water. In China, provinces and cities established diverse regulations based on their different natural and climate conditions, thus there is not a uniform model for the implementation in the country. In the EU, the amendment of Energy Efficiency Directive seeks to establish common policies. The difference of rules in these two jurisdictions reflects that China and the EU have their own principles and objectives: China attempts to balance the demand of developing smart city infrastructures and the consumption on natural resources, but the EU has strong ambition on low carbon emission in the whole Union. However, the two jurisdictions still have a common goal to maximize the efficiency of water and electricity consumption which is a fundamental issue for accelerating the transition towards sustainability.

Financial expenditure, financial friction, and coal consumption for energy efficient environment: Role of financial inclusion

This research investigates the crucial role that adaptability and ongoing evaluation have in implementing sustainable energy and economic development strategies in China. It emphasises the need for collaboration between enterprises, governmental organisations, and academic institutions in order to achieve these goals. The study also discusses how financial inclusion impacts economic growth and stability and how energy-intensive companies might use the Logarithmic Mean Divisia Index (LMDI) approach to evaluate energy decomposition. The findings indicate that different provinces in China’s high energy-intensive (EI) economic sectors have different degrees of energy efficiency, with certain regions possibly having inefficiencies. The research underscores the need for targeted strategies to address these inefficiencies and disseminate efficacious approaches in new settings. The research also offers useful data that may be used to promote sustainable energy consumption and economic growth, with implications for policy-making and strategic initiatives. In summary, this paper presents specific policy recommendations and highlights the need for ongoing evaluation and collaboration to support China’s sustainable energy initiatives and economic growth.