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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. [ABSTRACT FROM AUTHOR]

Climate change has emerged as a global focal point, notably affecting vulnerable countries like Pakistan. The country faces heightened risk, prompting concern among many due to its susceptibility to climate-related hazards. An imperative challenge arising from this phenomenon is the necessary shift towards sustainable energy, particularly concerning energy consumption within the building sector. Buildings significantly contribute to daily energy usage and subsequent GHG emissions. In Pakistan, transitioning to energy-efficient building stock holds pivotal importance in mitigating climate change impacts. This hinges on establishing a robust institutional framework and regulatory structure centered around energy efficiency. While Pakistan possesses policies and national guidelines advocating for energy-efficient buildings, their practical enforcement and application remain inadequate. The inception of the Building Energy Code of Pakistan in 1990, based on ASHRAE 90.1 standards, marked a step forward. However, obstacles rooted in institutional weakness and limited capacity building have impeded its effective adoption and adherence. Although the Energy Provisions of 2011 introduced modifications, their scope remained confined mainly to commercial structures. This paper conducts an extensive assessment of Pakistan's existing institutional and regulatory framework for building energy efficiency and transition. Drawing on literature insights and stakeholder perspectives, an in-depth understanding of prevailing policies and institutions uncovers underlying reasons for noncompliance and limited implementation. Additionally, input was gathered from stakeholders through interviews, aiming to identify barriers obstructing the reinforcement of building energy efficiency measures in Pakistan. Discourse and narrative analysis, informed by literature and stakeholder interviews, revealed the significance of awareness, participation, coordination, capacity building, technical expertise, finance, and resources as key factors contributing to deficient compliance and implementation of existing codes and policy guidelines. This paper also proposes actionable recommendations to expedite the transition towards a sustainable, energy-efficient building stock in Pakistan. [ABSTRACT FROM AUTHOR]

The article offers information on advancements and future directions in process design for sustainable energy systems. Topics discussed include optimizing energy management strategies for fuel-cell hybrid vehicles; reviewing energy-efficient and renewable systems in educational institutions; and developing automated methods for enhancing energy efficiency in industrial robotics.

Energy poverty affects numerous households across the globe and has several key implications and concerns for public health and social equity. Energy poverty is defined as "the lack of access to modern and affordable energy services". Individuals or communities in energy poverty face limitations in accessing reliable, affordable, and sustainable energy. This review paper examines a focused subset of recent research on energy poverty highlighted by the "NSF 2026: Priorities and Research Needs for an Equitable Energy Transition" workshop and the United States Department of Energy's Office of Energy Justice Policy and Analysis to help frame energy poverty's impacts on policy, poverty alleviation, environmental impact, and social inequity. This review paper uses five themes to organize previous energy poverty work: (1) Energy Poverty and Justice Definitions and Metrics; (2) Behavioral Aspects of Energy Poverty; (3) Efficacy of Energy Assistance Programs; (4) Efficiency of Energy Efficiency Policy; (5) The Energy Transition and Environmental and Energy Justice. We found that the literature examined how comprehensive assessment of energy poverty requires going beyond standard statistics and metrics and must include an understanding of how underserved households interact with energy. We found strong optimism for the clean energy transition's ability to significantly alleviate energy poverty, but only if policymakers include equity. Finally, we found that while there is plenty of work highlighting deficiencies there is a dearth of work examining successful implementations and how to replicate them which will be needed if the clean energy transition is to match its potential. [ABSTRACT FROM AUTHOR]

The object of the research of the article is transport system of a city. The paper reviews the necessity to assess the greenhouse emissions in the city and proposes the methods for greenhouse emissions inventory of the urban transport system. The proposed approach is aligned with guidelines for the development of Sustainable Energy and Climate Action Plan (SECAP) of Mayor Covenants of European Union (EU). The methodologies outlined in the paper allow to estimate annual greenhouse emissions from transport sector. The SECAP defines transport sectors based on ownership and functioning as following: municipal transport fleet, public transport, and private and commercial transport. The paper proposes the methodology to estimate direct and indirect emissions in each of the described sector based on the information that is typicaly available to municipalities in Ukraine. The assessment is conducted on disaggregated level for different fuel types (diesel, petroleum, natural gas, biofuel, electricity, etc.) and separately for each fleet type (buses, trucks, passenger vehicles, specialized machinery). Total CO2 emissions are then estimated by multiplying the amount of fuel consumed by the emission factor for each fuel type and vehicle type. Information of fuel consumption is estimated based on annual milage and estimated based on available data and number of assumptions proposed in the paper. The proposed methodology for greenhouse emissions inventory for the transport sector allows to analyze available data, recommendations for data collection and a methodology for determining CO2 emissions from the operation of the transport system with sufficient accuracy of calculations. Based on these results, it is possible to forecast changes in energy consumption and emissions in the transport sector as a result of various interventions. For example, in Zhytomyr city the results of inventory were used to develop a set of measures, which include updating the rolling stock of electric transport; increasing the energy efficiency of the power grids of the transport system, developing cycling infrastructure. [ABSTRACT FROM AUTHOR]

Power generation comprises high environmental and ecological impacts. The global power industry is under pressure to develop more efficient ways to operate and reduce the impacts of inherent process variability. With the rapid development of technologies within the energy sector, large volumes of data are available due to in-time operational measurements. With increased computer processing capabilities, machine learning is applied to explore these in-time operational measurements for improved process understanding. This research paper investigates machine learning algorithms for energy efficiency improvement at coal-fired thermal power plants by conducting a systematic literature review. This research is essential since it provides guidelines for applying machine learning towards sustainable energy supply and improved decision-making. Subsequently, efficient processes result in the reduction of fuel usage, which results in lower emission levels for equivalent power generation capacity. Furthermore, this study contributes towards future research by providing valuable insights from academic and industry-related studies. [ABSTRACT FROM AUTHOR]

The focus of this paper is the relationship between sustainable energy sources and financial development. The main research hypothesis assumes a positive link between these areas, with inevitable differences across countries and business sectors. The following research questions were asked: Is the impact of financial development on sustainable energy resources the same in different EU countries advanced in green transition processes? How is transition towards renewable energy sources progressing in different economic sectors? Does financial development influence sectoral transition in particular countries? This study uses the TOPSIS method and 25 variables for EU countries from 2013 to 2021. Key findings reveal that the link between sustainable energy sources and financial development varies across EU countries, country size affects energy autonomy, and the transition also differs by business sector. Surprisingly, higher financial development correlates with less progress in sustainable energy initiatives. The results of our research may be useful for government decision-makers in the process of designing and controlling the country's transition to sustainable energy. The original contribution of the study is expressed in its the diagnosis of the relationship between financial development and sustainable energy sources, while most studies have focused on the relationship between the energy market and financial development. [ABSTRACT FROM AUTHOR]

Process Intensification (PI) is an effective way to enhance process efficiency and sustainability at affordable costs and efforts, attracting particular interest in the European area, as one of the most important chemical production areas in the world. PI primarily contributes by developing and testing new processing technologies that once integrated within a process improve the overall process performance substantially but as a result, it may alter the overall process (flowsheet) structure and its dynamic behavior. As such PI plays a key role in improving energy efficiency, optimizing resource allocation, and reducing environmental impact of industrial processes, and thereby leading to a cost- effective, eco-efficient, low-carbon and sustainable industry. However, along with opportunities, the PI new technologies have challenges related to failures in longer-term performance. In this respect, Process Systems Engineering (PSE) stance is more on integration aspects of new PI technologies into processes by making process (re)designs, doing operability studies, and performance optimizations within a supply chain setting. PSE contributes to overcoming the challenges by providing systematic approaches for the design and optimization of PI technologies. This perspective paper is a lightly referenced scholarly opinion piece about the status and directions of process intensification field from a PSE viewpoint. Primarily, it focuses on PSE perspectives towards sustainable lower energy usage process systems and provides a brief overview of the current situation in Europe. It also emphasizes the key challenges and opportunities for (new) PI technologies considering their integration in a process in terms of process synthesis and design, process flowsheet optimization, process and plantwide control, (green) electrification, sustainability improvements. Potential research directions on these aspects are given from an industrial and academic perspective of the authors. [ABSTRACT FROM AUTHOR]

The internet is expanding its viewpoint into each conceivable part of the cutting-edge economy. Unshackled from our web programs today, the internet is characterizing our way of life, regardless of whether it's sitting in front of the TV or driving an independent auto. The enchantment of the internet appears to be relatively unbounded. In any case, with each new spell there comes an ever-increasing amount of data, and interest for computational power. Cloud computing which is an on-request conveyance of computing power, applications, database storage, and other IT assets by means of the Internet has violently expanded our computerized lives. Though, there have been critical improvements as far as accessibility, fluctuation, time and quality in administrations are concerned; the unbounded development of our computerized way of life requires monstrous measures of power, especially for the data centers that fill in as the mind of the advanced economy. Data organizations foresee a decrease in the quantity of data centers, as more businesses close their little data centers and move towards cloud computing. All things considered, the move by clients towards cloud, will increase the general energy utilization significantly, exceeding any energy productivity increase; which has recorded for over 70% of data center development in 2018. Many research advancements are already made in this domain for minimizing the energy utilization of the computing types of gear included; for efficient power energy consumption, decrease of carbon impression and e-squander. These procedures are supporters of green cloud computing, which are focused on planning and advancing energy-proficient activities to contain inordinate energy utilization in data centers. This paper discusses different mechanisms for lowering the power utilization in data centers. It provides in depth detail about the various mechanisms that can be employed at the hardware component level so that the utilization of energy by component can be reduced. Techniques that can be applied at network, cluster of servers' level along with the various dynamic power management measures that can be employed at the hardware or firmware level and can lead to energy efficient or green data centers are also studied in detail. The paper concludes with the research challenges for building the green data centers. [ABSTRACT FROM AUTHOR]

Purpose: Energy consumption and renewable energy sources are included in the goals for the 2030 Sustainable Development Goal 7 (SDG7) agenda, and target buildings are the biggest electricity consumers. In turn, Netzero energy buildings (NZEB) contribute to achieve SDG7 goals. This paper aims to identify which Brazilian higher education institutions (HEIs) practices contribute to developing the NZEB concept. Design/methodology/approach: Case studies were selected to identify which implanted practices applied by HEIs in Brazil, listed in the UI GreenMetric 2020 Ranking, are related to the NZEB concept. The implemented sustainable practices were also analyzed to evaluate the connections and impact between universities and the local community. Findings: Results show the lighting and air conditioning retrofit were among the most common practices related to energy efficiency to reduce consumption. For renewable energy generation, photovoltaic solar energy is the most common practice used by HEIs. Research limitations/implications: Only Brazilian HEIs listed in the UI Green Metric Ranking were analyzed. No standard regulation or formal reports support the wide dissemination of the strategies adopted by HEIs in Brazil. Practical implications: The strategies adopted by HEIs related to Netzero buildings can reduce emissions, optimize operating costs and improve building comfort conditions, which connect all SDGs. Social implications: HEIs can promote awareness related to energy use and clean energy generation within the local community. Originality/value: This paper presents the most common strategies adopted by Brazilian HEIs. However, limitations related to lack of strategies, data transparency and specific Netzero energy regulation were also found. These issues can hinder other HEIs to adopt similar strategies and contribute to the promotion of SDG7 in Brazil. [ABSTRACT FROM AUTHOR]

Purpose: The paper presents the issues related to the sustainable consumption and energy efficiency. Design/methodology/approach: The study used world-bank reports from the University of Oxford publication Our World in Data and own research. Findings: The main purpose of the article is to increase consumer awareness and demand for energy needs. It is worth emphasizing the important role played by sustainable energy expenditure in this area. They are an important element of sustainable consumption, because the way society uses energy has a significant impact on the environment, health and energy resources. Sustainable energy expenditure is a way of using energy that allows you to achieve a balance between the demand for energy and its consumption. Selected measures of energy efficiency show that economic development does not have to be equated with an increase in the consumption of energy resources. Originality/value: The publication presents the results of research conducted on the basis the University of Oxford publication Our World in Data. [ABSTRACT FROM AUTHOR]

The implementation of non-intrusive load monitoring has gained significant attention as a promising solution for disaggregating and identifying individual appliances' energy consumption within households and commercial buildings. The issue at the core of non-intrusive load monitoring is the accurate separation of the aggregated energy consumption signal into the energy contributions of distinct appliances without requiring additional sensors or invasive measurements. The erroneous implementation of non-intrusive load monitoring model leads to poor results and a waste of time where the criteria for the implementation are necessary. This paper presents an overview of non-intrusive load monitoring's implementation, addressing the stages of non-intrusive load monitoring and advancements in the field. The overview explores the various techniques, methodologies, and algorithms employed in non-intrusive load monitoring systems to achieve load identification and energy disaggregation. By addressing the problem statement and reviewing the state of the art, this paper sets the stage for understanding the significance of non-intrusive load monitoring in commercial buildings and modern energy-efficient households. Moreover, the limitations, applications, and recommended criteria for the implementation of non-intrusive load monitoring are highlighted as a contribution to the field of load disaggregation. Future research should address scalability, privacy concerns, and the integration of non-intrusive load monitoring with smart grids to propel energy disaggregation towards more efficient, accessible, and sustainable energy management systems. We envision that this endeavour can serve as a guiding beacon, offering a roadmap for researchers and professionals. [ABSTRACT FROM AUTHOR]

The interest in sustainability and energy efficiency is constantly increasing, and the noticeable effects of climate change and rising energy prices are fueling this development. The residential sector is one of the most energy-intensive sectors and plays an important role in shaping future energy consumption. In this context, modeling has been extensively employed to identify relative key drivers, and to evaluate the impact of different strategies to reduce energy consumption and emissions. This article presents a detailed literature review relative to modeling approaches and techniques in residential energy use, including case studies to assess and predict the energy consumption patterns of the sector. The purpose of this article is not only to review the research to date in this field, but to also identify the possible challenges and opportunities. Mobility, electrical devices, cooling and heating systems, and energy storage and energy production technologies will be the subject of the presented research. Furthermore, the energy upgrades of buildings, their energy classification, as well as the energy labels of the electric appliances will be discussed. Previous research provided valuable insights into the application of modeling techniques to address the complexities of residential energy consumption. This paper offers a thorough resource for researchers, stakeholders, and other parties interested in promoting sustainable energy practices. The information gathered can contribute to the development of effective strategies for reducing energy use, facilitating energy-efficient renovations, and helping to promote a greener and more sustainable future in the residential domain. [ABSTRACT FROM AUTHOR]

Energy keeps the global economy alive, while also being extensively exposed to various climate change impacts. In this context, severe business competition (e.g., the building sector) and the unwise use of natural resources and ecosystem services (e.g., fossil fuel energy sources) seem to sharpen the relevant effects of climate change. Indicatively, contemporary issues at the interface of building energy performance and environmental quality levels include consequences from global warming, the increasing release of carbon dioxide to peak electrical loads, power grids, and building planning, and energy demand and supply issues. In light of such concerns, the present review paper attempts to disclose the multifaceted and multidisciplinary character of building energy use at the interface of the economy, the environment, and society against climate change. This review highlights energy efficiency concepts, production, distribution, consumption patterns, and relevant technological improvements. Interestingly, the reviewed contributions in the relevant literature reveal the need and necessity to alter the energy mix and relevant energy use issues. These include developments in climate-proof and effective systems regarding climate change impacts and shocks. Practical implications indicate that the sustainable development goals for clean energy and climate action should be followed if we wish to bring a sustainable future closer and faster to our reality. [ABSTRACT FROM AUTHOR]

The energy revolution prioritizes efficiency, sustainability, practicality, and concreteness. Conventional energy processes remain crucial and will continue to be essential for a long time if they are based on renewable and clean sources. Biofuels, particularly biomethane, are gaining significant attention for their potential to replace fossil fuels and contribute to a greener energy landscape. This paper focuses on enhancing the energy efficiency of an anaerobic digestion plant for biomethane production. Oversizing issues in technical plants often result in excessive energy and economic costs. Therefore, this study aims to analyze plant sections that can be improved to enhance performance. An energy analysis quantifies the energy requirements for different sections and sub-sections, guiding the selection of energy interventions such as pipeline resizing, heat generator modifications, pump enhancements, and energy recovery opportunities. The methodology is applied to an existing biomethane plant, and graphical software is used for redesigning the heat generator, pumps, and pipelines. The results demonstrated that implementing energy efficiency measures improves system performance. The heat generator's capacity was successfully reduced by 100 kW, surpassing the initial design choice. Additionally, heat recovery from the biogas compression section has enhanced the overall thermal dynamics of the system. The estimated annual methane consumption in the boiler is approximately 12,000 Nm3, resulting in an expenditure of EUR 10600. These interventions have led to substantial savings, totaling EUR 133000 for the comprehensive thermal sustenance of the entire plant. [ABSTRACT FROM AUTHOR]

Purpose: The need to improve energy efficiency as an essential factor for achieving the Sustainable Development Goals (SDGs) through green financing is one of the most important issues worldwide. It is even more important for ASEAN (Association of Southeast Asian Nations) countries because of their potential for economic growth and the challenge of their environmental problems. This paper therefore addresses the question of whether and how green finance (with the proxy of issued green bonds [GBs]) promotes energy efficiency (with the proxy of energy intensity) in the ASEAN member countries. Design/methodology/approach: The paper runs a two-stage generalized method of moments (GMM) system model for the quarterly data over the period 2017–2020. It also uses a linear interaction model to explore how the pandemic may affect the relationship between green finance and energy efficiency in this region. Findings: The main results only demonstrate the short-term negative impact of GBs on energy intensity. Furthermore, per capita income, economic integration and renewable energy supply can be used as potential variables to reduce energy intensity, while modernization in ASEAN increases energy intensity. Establishment of digital green finance, long-term planning of a green finance market, trade liberalization and policies to mitigate the negative impacts of COVID-19 are recommended as golden policy implications. Research limitations/implications: The present study has several limitations. First, it accounts for explanatory variables by following a number of previous studies. This may lead to omissions or errors. Second, the empirical estimates were conducted for 160 observations due to the repositioning of GBs in ASEAN, which is not bad but not good for an empirical study. Originality/value: To the best of authors' knowledge, there has not been any in-depth study focusing on the relationship between energy efficiency and green financing for the case of ASEAN economies. [ABSTRACT FROM AUTHOR]

To face with the surge of cloud computing services, energy problem and carbon mission constraint, more and more geo-distributed hybrid powered data centers are build over the world. Geo-distributed hybrid powered data centers are located in different locations equipped with different types of green energy source. In this work, we propose a periodic requests dispatcher, including a periodic model and a spatial balance algorithm, to minimize the brown energy use. The periodic model divides the long-term period into several time slots, and the spatial balance algorithm achieves energy optimization by balancing user requests in each time slot. Besides, a research case is simulated by Cloudsim platform. We conduct several comparative analysis in aspect of energy utilization, electricity cost and carbon emission. The experiment results show that the dispatcher can effectively reduce the electricity cost, and reasonably achieve the request distribution balance in geo-distributed hybrid powered data centers. [ABSTRACT FROM AUTHOR]

Split incentives, in which the costs and benefits of energy efficiency upgrades are unevenly felt between landlords and tenants, are a powerful barrier that prevents retrofits from taking place. The problem is clearly playing out across the low-income, and inefficient homes of Bridgewater, Nova Scotia, Canada, where greenhouse emissions are high, and a large proportion of residents are burdened by energy poverty. To help solve the problem and facilitate home energy efficiency renovations, a project called Energize Bridgewater was developed. Guided by 10 semi-structured interviews with Energize Bridgewater team members (n = 4) and property managers (n = 6), we present a case study which sought to contextualize and better understand how Energize Bridgewater may incentivize owners of rental houses to participate in this clean energy transition. Our results focus on three main findings: i) the reality of the split incentive problem in Bridgewater; ii) barriers to landlord engagement; and iii) reactions to proposed programming. We close this paper with a discussion of the theoretical and practical implications of our work, including a set of recommendations for Energize Bridgewater and similar projects facing the split incentive problem while working toward a clean and cost-effective energy transition. [ABSTRACT FROM AUTHOR]

In this paper, we propose a model of national innovation production that formalizes the role of trade partnerships as a channel of knowledge spillovers across countries. The model is used to investigate the energy efficiency technological domain in the European Union (EU) using a panel database covering 19 EU countries for the time span 1990–2015. The model is estimated by using a novel empirical strategy which allows to assess the knowledge spillover effects benefiting a country depending on its relative position in the trade network, and correct for common endogeneity concerns. We show that being central in the trade network is a significant determinant of a country's innovative performance, and that learning-by-exporting mechanisms are responsible for increased innovation performances. We further reveal that neglecting network effects may significantly reduce our understanding of domestic innovation patterns. Finally, we find that the benefits obtained from knowledge diffusion varies with the domestic absorptive capacity and policy mix composition. Our main implication is that policy design informed by network-based case studies could help maximizing the exploitation of positive knowledge spillovers. [ABSTRACT FROM AUTHOR]

Most of the countries in South-East Europe primarily depend on fossil fuels to cover their energy demands. The paper discusses the future perspective on wind energy in the country, where over 90% of energy is generated in coal-fired thermal power plants. Given the energy crisis, that has gripped the world, the possibility of covering the increased energy demand is being studied, especially during the winter. Based on current trends on energy generation, with just symbolic participation of wind, hydro and solar energy, the potential for maximization of the use of wind energy is considered, which means the use of each identified adequate location throughout the country. The main advantage here is that the maximum energy produced by wind is during winter when demand increases. This is important to know that Kosovo faces significant heating problems and its demand is covered with electricity. Analyzes prove that the country has a generous wind capacity, which reduces to a certain extent the need to import and even enables the export of energy under certain conditions. The potential installation capacity in Kosovo is 510.9 MW, of which 32.4 MW is currently in operating conditions. From the analysis made for the current wind farm in operation, the plant capacity factor is 31.8%. The study of the results indicates a direct correlation between the increase in load during the winter season and the electricity production by wind farms, thereby, the energy demand can be sufficiently covered. [ABSTRACT FROM AUTHOR]

• A bibliometric analysis of the relevant literature on tunnel lighting was conducted. • The literature is sorted by energy saving, visual comfort, and low carbon. • The relationship between energy saving and low carbon is discussed. • The relationship between energy saving and comfort is also discussed. • The optimization methods of tunnel light environment are summarized. A reasonable and applicative tunnel light environment is important to ensure driving safety. This review aims to contribute to this growing area of research by exploring the tunnel lighting, which expands from safety to visual comfort, energy saving, and low carbon This paper employs bibliometric method to a visual analysis of the relevant literature and summarizes current research efforts and development directions. Firstly, the literature is visually presented by CiteSpace to elaborate the state-of-art with the dimensions of the timeline graph, the keyword co-occurrence graph, and the institutions & countries co-occurrence graph. Afterwards the literature is reviewed from three major perspectives: energy saving, visual comfort, and low carbon. Current research is mainly on luminaire arrangement, auxiliary lighting and other measures to reduce energy consumption. Visual comfort is mainly improved by optimizing the light environment's physical quantities, e.g. luminance, color temperature, color rendering etc. Current measures to achieve low carbon targets include green energy, green photoconductivity, green luminaires and green operation. Energy saving, visual comfort and low carbon are interrelated and complementary. However, a systematic understanding of how tunnel lighting contributes to carbon emission is still lacking. There is still room for development in tunnel lighting to achieve full intelligent control and the goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

The contemporary world faces several energy problems and struggles to balance sustainable energy and steady industrial development. In this context, the existing energy efficiency studies have not unfolded the mysteries surrounding the industrial units' energy-saving potential and the key determinants and impacts of the manufacturing units' energy efficiency levels. Therefore, there is a need to comprehensively study the existing energy efficiency studies and clarify the above. Considering two databases, Scopus and Web of Science, the study uses bibliometric analysis and a systematic literature review to analyze the current energy efficiency literature. The bibliometric analysis is based on 619 published papers and assesses the existing energy efficiency literature to ascertain the evolution of energy efficiency studies from 2001 to 2022. This investigation adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-2020) framework for a systematic review of ninety-three relevant papers from the existing energy efficiency literature. The systematic literature review (SLR) highlights twenty-seven theories discussed in several dimensions of the environmental and industrial linkages in the manufacturing sector. Subsequently, the study identifies energy efficiency measures and the associated methodological issues. Next, the study addresses the available set of determinants and the impacts of energy efficiency performance on manufacturing industries across the globe. It explores the potential research gap in the existing studies. Finally, the concluding remarks, discusses several policy implications, and suggests avenues for future research in the direction of theory, context, and methodology in energy efficiency domain. [Display omitted] • Bibliometric analysis and systematic literature review are performed to synthesize the current energy efficiency studies. • The study considers 619 energy efficiency papers from Scopus and Web of Science databases over the past 22 years. • The study uses the PRISMA-2020 framework and uses Bibliometrix in R (RStudio) and VOSViewer software for the analysis. • SLR considers 93 papers and identifies 27 existing theories, addresses determinants and impacts of energy efficiency. • The study identifies the research gap, presents several policy implications and provides the scope for future research. [ABSTRACT FROM AUTHOR]

Based on the Saudi Green initiative, which aims to improve the Kingdom's environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve netzero carbon by 2060, NEOM city has been proposed to be the "Saudi hub" for green energy, since NEOM is estimated to generate up to 120 Gigawatts (GW) of renewable energy by 2030. Nevertheless, the Information and Communication Technology (ICT) sector is considered a key contributor to global energy consumption and carbon emissions. The data centers are estimated to consume about 13% of the overall global electricity demand by 2030. Thus, reducing the total carbon emissions of the ICT sector plays a vital factor in achieving the Saudi plan to minimize global carbon emissions. Therefore, this paper aims to propose an eco-friendly approach using a Mixed-Integer Linear Programming (MILP) model to reduce the carbon emissions associated with ICT infrastructure in Saudi Arabia. This approach considers the Saudi National Fiber Network (SNFN) as the backbone of Saudi Internet infrastructure. First, we compare two different scenarios of data center locations. The first scenario considers a traditional cloud data center located in Jeddah and Riyadh, whereas the second scenario considers NEOM as a potential cloud data center new location to take advantage of its green energy infrastructure. Then, we calculate the energy consumption and carbon emissions of cloud data centers and their associated energy costs. After that, we optimize the energy efficiency of different cloud data centers' locations (in the SNFN) to reduce the associated carbon emissions and energy costs. Simulation results show that the proposed approach can save up to 94% of the carbon emissions and 62% of the energy cost compared to the current cloud physical topology. These savings are achieved due to the shifting of cloud data centers from cities that have conventional energy sources to a city that has rich in renewable energy sources. Finally, we design a heuristic algorithm to verify the proposed approach, and it gives equivalent results to the MILP model. [ABSTRACT FROM AUTHOR]

Environmental pollution, increased energy consumption, and growing demand for the energy sector have been widely discussed. Due to policymakers and different organizations impacting a lot of new regulations, tools have been implemented to use clean energy that has zero impact on the environment. The International Energy Agency (IEA) supports energy efficiency and evaluation by developing tracking indicators and analyzing energy consumption data. The purpose of the topic is to identify key indicators for green energy production, rank best performing countries, discuss their methods regarding energy production and suggest policy implications for improving energy efficiency. The presentation will be about the results of the paper analizing key indicators for green energy production in IEA member states. [ABSTRACT FROM AUTHOR]

Considering the escalating global warming and its severe consequences, the exploitation of hydrogen, an eco-friendly energy carrier, is gaining great interest. This paper comprehensively reviews the most common hydrogen production, storage, transportation and utilization processes, while their effectiveness is explored from energy, water, economic and environmental perspectives. Their main characteristics, advantages, shortcomings and challenges are discussed as well. The research reveals that the hydrogen's water footprint, energy consumption, carbon emissions, and cost vary significantly depending on the specific technologies used throughout its life cycle, from production to end use. For instance, fossil fuel-based hydrogen production methods, such as steam methane reforming, offer elevated energy performance and cost-effectiveness, but have a significant carbon footprint. In contrast, water electrolysis is environmentally friendly, but requires more water and has lower energy efficiency. Besides, high-pressure containers are the preferred method for hydrogen storage, while liquid and solid storages are better suited for high-energy-density applications. Regarding hydrogen transportation, pipelines are effective over long distances, whereas tankers are convenient for short distances. Furthermore, fuel cells are more energy, carbon and water efficient when using hydrogen as fuel, but they are generally more expensive than internal combustion engines. [Display omitted] • Hydrogen production, storage, transportation and utilization methods are reviewed. • Their energy efficiency, water use, cost, and environmental impact are explored. • Key recommendations to boost the utilization of hydrogen systems are outlined. • Fossil fuel-based technologies are more energy-efficient and cost-effective. • Renewable-based processes are more environmentally friendly but water-intensive. [ABSTRACT FROM AUTHOR]

The world's industries, transportation systems, and households rely heavily on fossil fuels despite their limited availability and high carbon content. Therefore, it is of the utmost importance to improve fossil fuel energy efficiency in order to facilitate the shift towards a sustainable energy system with reduced greenhouse gas emissions. This paper employs a slacks-based measure network data envelopment analysis model with undesirable outputs to assess the efficiencies of fossil fuel energy in the Association of Southeast Asian Nations (ASEAN) countries during a span of seven years, specifically from 2015 to 2021. The inclusion of undesirable outputs in this study is important because it allows for a more realistic assessment of efficiency by considering factors like CO2 emissions, which are undesirable outcomes associated with fossil fuel use. The datasets utilised in this study are sourced from the U.S. Energy Information Administration and the open data website of Our World in Data. Based on the findings, it can be observed that Singapore and the Philippines have demonstrated outstanding performance in maximising the utilisation of fossil fuels. In contrast, Myanmar exhibits the lowest level of efficiency in this analysis. By identifying top-performing countries in terms of fossil fuel efficiency, it is possible to implement measures to boost efficiency in under-performing countries. This can be achieved through the promotion and adoption of cleaner energy alternatives, specifically renewable energy sources that exhibit a low or negligible carbon footprint. These findings offer significant contributions to policymakers exploring sustainable energy usage, environmental stewardship, and the formulation and execution of comprehensive strategies that aim to mitigate carbon dioxide emissions arising from the consumption of fossil fuels in the ASEAN region. [ABSTRACT FROM AUTHOR]

Statistics confirm that in the EU, buildings consume approx. 40% of final energy, which accounts for 36% of total European greenhouse gas production after energy consumption. Energy efficiency measures are urgently needed to effectively reduce greenhouse gas emissions. Decreasing fossil fuel consumption would have a major impact on declining energy demand per unit of gross domestic product. In 2014, European leaders adopted the ambitious Climate and Energy Framework 2030, in which the three key targets were raised: a 40% reduction in greenhouse gas emissions by 2030, a 27% reduction in RES and a 27% increase in energy efficiency. Then, in November 2016, the European Commission (EC) proposed the Clean Energy for All Europeans package, designed to support and accelerates the transition to a carbon-free energy system. This paper comprises a case study of the current situation of these matters in Romania and focuses on steps and methodology of what actions are reliable and available to be put into practice on this matter. [ABSTRACT FROM AUTHOR]

The importance of using clean energy in electrical energy generation and transportation network planning has recently increased due to carbon footprint rising. In this direction, the use of electric vehicles (EV), known as ultra-low carbon emission vehicles, has become widespread in addition to renewable energy sources (RES) such as wind and photovoltaic (PV) power generations. The trend of EVs to be preferred the primary means of transport has revealed the effects of charging an additional load on the grid. There is a need to create coordinated charging methods by considering the approaches for real-time charging models of EVs. In this paper, SOC-based EV coordinated charging was proposed for power management to prevent adverse effects including transformer overload, instantaneous peak loading and line overload in the existing distribution network. The proposed coordinated EV charging method was tested on the modified Roy Billinton test system (RBTS) Bus 2 network. AC 11 kW uncoordinated charging units have been respectively 123.76% distribution transformer and 115.16% distribution line overloading for 500 EVs on the grid with 13,9% diversity factor. However, these values that are 72.05% of distribution transformer and 67.01% of distribution grid overloading according to permittable level were decreased by the proposed coordinated charging method. Also, the state of charge (SOC) based coordinated method can increase 3.5% rate the diversity factor of charging capacity at the charging station with PV and battery energy system (BES) while ensured grid stability and energy efficiency. [ABSTRACT FROM AUTHOR]

The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies. • Applied SDG policies focused on energy technology RD&D are presented. • The stochastic characteristics of energy technology investments are examined. • Carbon-reducing policies are recommended for the top five economies. • Energy technologies are perused through artificial intelligence approach. [ABSTRACT FROM AUTHOR]

The evolution in the Information and Communications Technologies industry results in excessive energy consumption and carbon dioxide emission in the wireless networks. In this context, energy efficiency in mobile networks has been attracting considerable attention as green communications and operational expenditures reduction depend on it. Although the Internet of Things is to be supported by devices that are low-energy consuming, the power consumption of the huge number to be connected for several applications and services demand significant attention. To offer insights into green communications, this paper reviews various energy efficiency improvement techniques. Also, we consider a hybrid model in which the main grid power and dynamically harvested green energy from renewable energy sources can be leveraged to support the energy demand of the radio access network. In this regard, we reformulate the energy consumption model and consider an energy-efficient power allocation algorithm for green energy optimization. Numerical results show that with resource allocation algorithm exploitation, the energy efficiency can be enhanced. Besides, the amount of the grid energy consumption can be considerably minimized, resulting in the greenhouse gas emissions reduction in the wireless networks. [ABSTRACT FROM AUTHOR]

This paper investigates the sustainability of Tabriz City focusing on its decarbonization. Statistical, quantitative, and comparative research methods are used to analyze the total energy consumed, conversion of primary energy, final exergy, and losses analysis according to the renewable and carbon-based energies. Then, the renewable resource potentials of the city are simulated using Grasshopper plug-in-Rhino simulator, THERM, PVSyst photovoltaic software, and ArcMap. In terms of the socio-economic assessment, non-oil Per Capita GDP, emissions, and energy intensities are analyzed concerning the B2DS scenario by 2050. The per capita GDP of the city is 71% of the country's average value. Tabriz's real GDP growth averaged −1.11% per year, primary energy demand increased by an average of 6.1%, CO 2 emissions from energy use grew by an average of 6% annually and the emission intensity of the economy increased by a total of 52.02%, in the period from 2011 to 2019. Finally, it is shown that the city consumes 58050 GWh/year of different carbon-based resources that only produced 20110 GWh/year of useful work with 5.63 MT CO 2 emissions, while the same work could locally be supplied by 30000 GWh/year RE with a minimum rate of 0.18 MT CO 2 emissions. The city Landfill receives 1000 tons/day of MSW, but two-thirds of this amount can be recycled. Regarding different sectors, buildings produce half of the CO 2. The cement industry with dual pollutants (17%) is the most polluting factory. Carbon-based electricity (66%) is the most polluting form of energy. In terms of carbon sequestration requirements with trees, shifting from fossil fuels toward green energies, EE, and recycling MSW can plunge required trees from 81.9 to 1.16 million trees. This paper highlights the importance of electrification of transportation based on RE, energy performance of buildings, and all sectors. • Large city decarbonization strategies • Application of RE according to geographic and climatic factors. • Electrification of sectors based on RE locally. • MSW recycling and sequestration by trees for decarbonization regarding the LULC and NDVI analysis. • Conversion and storage efficiencies of carbon-based fuels vs RE. [ABSTRACT FROM AUTHOR]

The electrification of isolated or rural areas brings with it technical, economic, and social challenges that differentiate the operation of these networks compared to the traditional operation of large electrical power systems, such as the dependence of air or river transport on fuel for the supply of generation plants, the absence of individual measurement and the obsolete infrastructure of the distribution networks. Therefore, this paper proposes a hybrid methodology for studying a Colombian case, analyzing the development of programs for rational electricity use and energy efficiency in isolated areas. These first steps are related to the diagnosis of the current conditions of the power network, the identification of actors that can influence the regulation of the electricity service in the area, and the proposal of mechanisms that allow promoting the rational and efficient use of the electricity. [ABSTRACT FROM AUTHOR]

In order to achieve China's carbon peaking and carbon neutrality (double carbon) targets and to advance ecological conservation and high-quality development in the Yellow River Basin, it is essential that China reduces its energy intensity and increases its energy efficiency. This research developed an evaluation index system for energy efficiency and green development in the Yellow River Basin based on panel data collected from 64 of its prefecture-level cities and covering the period from 2011 to 2020. Each city's energy efficiency and green development level index was calculated, and was analyzed together with the characteristics of its spatial pattern progression. The STIRPAT model was then used to investigate the influence mechanism of energy efficiency on green development. The final step in the analysis was to assess the process by which technical innovation influences the rise in energy efficiency from a green development point of view. The findings of this study indicate that: (1) There was a marked improvement in energy efficiency and green development levels across the Yellow River Basin over the study period of 2011 to 2020, but there are notable disparities among prefecture-level cities, with higher levels found in capital cities and cities in the lower reaches of the basin. (2) The improvement in energy efficiency has had a positive impact on the transition to green development, with factors such as human capital, urbanization levels, and the upgrading of industrial structures contributing significantly, while the level of foreign direct investment has had a limited impact. (3) Technological innovation plays a partial role in mediating the relationship between energy efficiency and green development in the Yellow River Basin, and passes the single-threshold test. When technological innovation surpasses the threshold value, the effect of energy efficiency on green development is significantly strengthened. This study indicates that improving energy efficiency, stimulating emerging industries, and enhancing technological innovation capabilities can significantly promote transformative green and high quality development in the Yellow River Basin of China. [ABSTRACT FROM AUTHOR]

This study analyzes the impact of green finance and renewable energy on energy efficiency in E−7 economies. We analyzed the nonlinear and asymmetric effects of green finance and renewable energy on energy efficiency. We collected data from 1985 to 2017 and applied the NARDL and 2SLS methods. The results reveal that the differences in green finance development in the E−7 region are as follows: China (0.61), Brazil (0.55), India (0.53), Indonesia (0.49), Mexico (0.37), and Russia (0.39). In 2019, the Gini coefficient was the largest in Russia (0.57), followed by Turkey. Based on empirical findings, the largest barrier to green energy efficiency is insufficient private and governmental investment in the energy sector to improve access to power, to increase energy security and promote economic growth in an environmentally sustainable manner. The findings point to a promising but vulnerable future for renewable energy and energy efficiency deployment in E−7 countries. This paper emphasizes that green financing and renewable energy policy limitations must be addressed to realize the funding potential of energy efficiency in E−7 countries. • We have analyzed the barrieres for renewable energy and energy efficiency. • Non-linear and asymmetric effects is observed on energy efficiency. • We have applied NARDL model to examine the relationship among variables. [ABSTRACT FROM AUTHOR]

There has been increasing interest in reducing carbon footprints globally in recent years. Hence increasing share of green energy and energy efficiency are promoted by governments. Therefore, optimizing energy consumption is becoming more critical for people, companies, industries, and the environment. Predicting energy consumption more precisely means that future energy management planning can be more effective. To date, most research papers have focused on predicting residential building energy consumption; however, a large portion of the energy is consumed by industrial machines. Prediction of energy consumption of large industrial machines in real time is challenging due to concept drift, in which prediction performance deteriorates over time. In this research, a novel data-driven method multi-regime approach (MRA) was developed to better predict the energy consumption for industrial machines. Whereas most papers have focused on finding an excellent prediction model that contradicts the no-free-lunch theorem, this study concentrated on adding potential concept drift points into the prediction process. A real-world dataset was collected from a semi-autonomous grinding (SAG) mill used as a data source, and a deep neural network was utilized as a prediction model for the MRA method. The results proved that the MRA method enables the detection of multi-regimes over time and provides a highly accurate prediction performance, thanks to the dynamic model approach. [ABSTRACT FROM AUTHOR]

Energy consumption analysis has often faced challenges such as limited model accuracy and inadequate consideration of the complex interactions between energy usage and meteorological data. This study is presented as a solution to these challenges through a detailed analysis of energy consumption across UBC Campus buildings using a variety of machine learning models, including Neural Networks, Decision Trees, Random Forests, Gradient Boosting, AdaBoost, Linear Regression, Ridge Regression, Lasso Regression, Support Vector Regression, and K-Neighbors. The primary objective is to uncover the complex relationships between energy usage and meteorological data, addressing gaps in understanding how these variables impact consumption patterns in different campus buildings by considering factors such as seasons, hours of the day, and weather conditions. Significant interdependencies among electricity usage, hot water power, gas, and steam volume are revealed, highlighting the need for integrated energy management strategies. Strong negative correlations between Vancouver's temperature and energy consumption metrics are identified, suggesting opportunities for energy savings through temperature-responsive strategies, especially during warmer periods. Among the regression models evaluated, deep neural networks are found to excel in capturing complex patterns and achieve high predictive accuracy. Valuable insights for improving energy efficiency and sustainability practices are offered, aiding informed decision-making for energy resource management in educational campuses and similar urban environments. Applying advanced machine learning techniques underscores the potential of data-driven energy optimization strategies. Future research could investigate causal relationships between energy consumption and external factors, assess the impact of specific operational interventions, and explore integrating renewable energy sources into the campus energy mix. UBC can advance sustainable energy management through these efforts and can serve as a model for other institutions that aim to reduce their environmental impact. [ABSTRACT FROM AUTHOR]

This study investigates the relationship between artificial intelligence (AI), industrial robots, and renewable energy consumption, driven by the rapid technological advancements and widespread adoption of AI tools in various industries. This research aims to evaluate the environmental implications of these technologies, specifically their impact on renewable energy usage. Employing a comprehensive analytical framework, this study utilizes advanced methodologies, including regularization factors, to accurately estimate the effects of these variables. Through a thorough data analysis, the research quantifies how AI and industrial robots influence the shift towards renewable energy sources. The findings reveal that investments in AI significantly enhance renewable energy consumption, as demonstrated by both conventional estimation techniques and those that integrate regularization factors. Conversely, the use of industrial robots is found to have a detrimental effect on renewable energy consumption. These results have important implications for policymakers, industry leaders, and sustainability researchers. This study encourages policymakers and investors to prioritize funding for AI solutions that promote renewable energy adoption, while it advises industry managers to strategically modify their use of industrial robots to reduce their environmental impact. Ultimately, this research lays a critical foundation for future inquiries and policy initiatives aimed at aligning technological advancements with sustainable energy practices. [ABSTRACT FROM AUTHOR]

Climate change and natural resource depletion have reinvigorated the relevance of technical advancements in energy efficiency, which has been emphasized by the Paris Climate Accord that includes a framework for carbon neutrality. In that effort, the governments have been allocating a considerable amount of budget shares to research and development relating to energy efficiency and green energy. Thus, this study primarily examines the impact and effectiveness of research and development on energy efficiency and energy sources (renewables and fossil fuels) on CO2 emissions in the European region using a novel Method of Moments Quantile Regression (MMQR). Our data cover annual observations of 9 EU countries, including Austria, Denmark, Finland, France, Germany, Netherlands, Norway, Spain, and Sweden, based on the period 1990–2021. Our empirical findings confirm that the U-shaped Environmental Kuznets Curve occurs across all quantiles at 1% significance levels. The findings reveal that energy consumption increases CO2 emissions across the lower to higher quantiles. We discover that (i) R&D on renewable energy cuts CO2 emissions just at the median and higher quantiles, (ii) R&D on Fossil Fuels decreases CO2 emissions just at the lower quantile, and (iii) R&D on Energy efficiency lowers CO2 emissions at both the median and higher quantiles. Therefore, empirical findings suggest that policymakers should maintain their incentives for energy efficiency R&D and renewable R&D to achieve sustainable development goals. [ABSTRACT FROM AUTHOR]

This article examines the comprehensive changes and adjustments made to the Bachelor's degree program in Electrical and Electronics Engineering (BSc) to align with the growing need for sustainable energy solutions. The primary objective of these revisions is to equip future engineers with a deep understanding of both traditional fossil energy sources and emerging renewable energy technologies, with a particular emphasis on smart grids. The revamped curriculum integrates advanced content delivery through a unique blend of professional laboratories, in-person lectures, discussions with industry experts, and online courses. By providing a holistic educational experience, the program aims to prepare graduates to lead the transition towards sustainable energy systems, fostering innovation and resilience in the energy sector. [ABSTRACT FROM AUTHOR]

The transition towards a sustainable and renewable energy future is essential to mitigate climate change and reduce greenhouse gas emissions. Small–medium combined heat and power (CHP) systems are increasingly popular for distributed energy generation, as they offer improved energy efficiency and reduced emissions compared to traditional power generation systems. This article reviews recent research articles related to small–medium CHP systems, including their role in renewable energy systems, use of biofuels, steam injection, diagnostics, and carbon capture. Throughout the research, the high potential of coastal regions has been observed and studied as a solid base for the later development of CHP systems. Based on the reviewed literature, the highest potential solutions are proposed to be further investigated as an efficient, economical solution for generating electricity and heat for various small-scale applications. [ABSTRACT FROM AUTHOR]

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This study aims to unveil the heterogeneous impacts of import product diversification and institutional factors for achieving energy efficiency in Organization for Economic Co-operation and Development (OECD) countries. In doing so, the study employs robust econometric techniques such as Fully modified ordinary least squares (FMOLS) co-integration, pooled Ordinary Least Squares (OLS), Feasible Generalized Least Squares (FGLS), pool mean group regressions, fixed effects, and random effects for panel data from 1990 to 2015 for selected OECD countries. The detailed empirical outcomes suggest that import product diversification is conducive to reducing the energy and carbon intensity (improvement in energy efficiency) in OECD countries. The empirical conclusions provide various guidelines to achieve cleaner and greener growth and align with various Sustainable Development Goals (SDG 7: Affordable and clean energy, SDG 9: Industry, innovation, and infrastructure, and SDG 13: Climate action) of OECD countries. The paper elaborates fruitful policy suggestions regarding the diversification of imports and energy use-carbon emission-nexus for the OECD member nations. Based on the findings, policymakers and environmental scientists should strengthen the trade-energy and import portfolio policies to attain energy efficiency. [ABSTRACT FROM AUTHOR]

The global energy crisis has spurred increased investments in energy efficiency and clean energy initiatives; however, the results have fallen short of expected effectiveness. Concurrently, population growth and urbanisation drive a persistent surge in energy demands, especially within the residential sector, significant to overall building energy consumption. Current research focuses on residents' responses to one-shot investments for energy efficiency or clean sources. The renovation wave, involving a massive number of existing buildings, calls for the mobilisation of huge investments that can be hard to afford in the short run. Sustainable behavioural change is complementarily rising as a key asset for maximising the overall estimated energy saving potential. Despite significant efforts to analyse household energy use and promote behavioural transformations, the literature remains gaping about future users, particularly the younger generation, as future leaders of sustainable development who exhibit a more responsible approach towards climate-related issues but also a strong dependency on digital-based solutions, which may influence energy use patterns and living habits, also impacting relations among peers and overall societal sustainability and energy efficiency. This article proposes a systematic literature review to analyse the variables affecting young people's energy behaviour at home. The aim is to investigate the engines and gaps between strategies or tools for behaviour change and the expected effects, then find potential methods to address that barrier to identify a more promising approach, encouraging the younger generation to translate towards more sustainable energy behaviours. [ABSTRACT FROM AUTHOR]

In this article, a novel cross-domain knowledge transfer method is implemented to optimize the tradeoff between energy consumption and information freshness for all pieces of equipment powered by heterogeneous energy sources within smart factory. Three distinct groups of use cases are considered, each utilizing a different energy source: grid power, green energy source, and mixed energy sources. Differing from mainstream algorithms that require consistency among groups, the proposed method enables knowledge transfer even across varying state and/or action spaces. With the advantage of multiple layers of knowledge extraction, a lightweight knowledge transfer is achieved without the need for neural networks. This facilitates broader applications in self-sustainable wireless networks. Simulation results reveal a notable improvement in the 'warm start' policy for each equipment, manifesting as a 51.32 % increase in initial reward compared to a random policy approach. [ABSTRACT FROM AUTHOR]

The United Nations Sustainable Development Goal 7, which calls for universal access to affordable, reliable, sustainable clean energy for everyone, is expected to influence near-future trends in many countries across the European Union. Retrofitting buildings is an important milestone in the evolutionary development of energy-efficient residential buildings, yet a significant proportion of the south-eastern European social-housing stock is obsolete in this area; in addition to effective retrofitting strategies for these buildings, the occupants thereof, who represent different socio-demographic backgrounds, also require in-depth study. Even though this subject has been widely investigated, new approaches that consider connections between technology and the behavioural responses of residents are needed to continuously update retrofitting design strategies and energy-efficiency solutions. This paper aims to fill a research gap in the area of developing an evidence-based framework for energy-policy decision-making mechanisms related to the integration of the Energy Performance Building Directives at the level of conceptual and nationwide implementation schemes. In general, properties in this particular sector account for approximately 38% of the total housing stock and demonstrate some of the worst housing standards in Europe. The objective of this study is to focus on the interaction of such attitudes and the underlying determinant factors thereof with socio-cultural and contextual factors. A socio-technical-systems (STS) approach is used as a theoretical framework to integrate household socio-demographic characteristics related to energy use, the thermal-conductivity level of buildings and environmental factors; and to address the question of how different contexts influence motivation to develop energy-efficiency strategies. Drawing on the STS, this study investigates domestic energy use and measures thereof in post war social housing stock in the south-eastern Mediterranean, where the climate is subtropical (Csa) and partly-semi-arid (Bsh); these designations are according to the Köppen climate classification system; to improve the energy efficiency of archetype residential tower blocks (RTBs) that are embedded and interpreted in the socio-cultural local context of Cyprus. Feed-forward interviews of 100 flats revealed a moderate negative correlation (r = −0,329, p 〈0,01) between household income and tenancy status, and there was a moderate positive relationship (r = 0,252, p < 0,05) between household income and length of residency; this indicates that household income is a determinant factor related to energy use. Of the surveyed flats, 73% were owner-occupiers whose ages ranged between 55 and 65 and 65-years-of-age and older; these age bands were in the high-income group, and the energy consumption of these households was higher than the national average, all of which demonstrates an association between the age and level-of-income factors. A moderate negative correlation (r = −0,229, p < 0,05) was found between the occupants' ages and their complaints related to thermal discomfort, which suggests that built-environment factors and household socio-demographic characteristics should be evaluated before any type of building retrofitting is developed. The study findings were implemented to develop policy design that considers the UN Sustainable Development Goals related to energy-and-recovery plans; implications on domestic energy use in the south-eastern Mediterranean climate are expected to influence future trends in EU countries. The flow diagram demonstrates the novelty of the socio-technical-systems conceptual framework developed for this study. [Display omitted] • Socio-technical associations between energy use and occupants' thermal comfort were examined. • Social households in vivo experiences on energy use were explored. • A moderate correlation (r = -0,329, p < 0,01) was found between income and type of tenancy. • A moderate correlation (r = 0,252, p < 0,05) was found between income and length of residency. • A moderate correlation (r = -0,229, p < 0,05) was found between the occupants' age and thermal discomfort. [ABSTRACT FROM AUTHOR]

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening—energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process. • Green innovation resilience can promote energy efficiency. • Early digital economy development can lead to resource grabbing and technology constraints effects. • Pursuing the policy orientation of "digital greening—energy efficient". [ABSTRACT FROM AUTHOR]

The purpose of the study is to test the role of market timing between oil price shock and energy efficiency mitigation in ASEAN countries. To achieve the study objective, a persistence econometric modeling technique is applied. The results revealed that oil prices are now the other main source of energy efficiency mitigation in ASEAN economies. Market timing-based factors are replaced with for oil price shock to increase, warranting a collaborative environment. Moreover, green financing loan schemes invest both public and private funds in energy efficiency mitigation to capitalize on a cleaner environment by controlling the oil price shock. The consideration and application of financial consideration for sustainable innovation-financing projects or companies is limitless. Providing for screening CO2 emission reduction and cooperation proposals with speedy greenhouse gas reduction rates might have large opportunity costs. There may be a case for governments to increase industrial growth, improve resource efficiency, and increase factor productivity while tackling energy efficiency. Economic growth in ASEAN may have an even greater influence on greenhouse gas reduction than in other countries. On such points, there is a need to pay attention. If the suggested policy suggestions are implemented successfully, they would help enhance the scope of financing considerations for sustainable innovation to uplift energy efficiency mitigation through market timing-based mechanisms. [ABSTRACT FROM AUTHOR]

The ambitious targets of peaking CO2 emissions before 2030 and reaching carbon neutrality before 2060 (Goal 3060) have emerged as the driving force in the development of China's low-carbon energy policy. Adopting a systematic review approach, this article provides a timely analysis of key Chinese renewable energy and energy efficiency policies under Goal 3060 across five sectors: electricity, industry, transportation, buildings, and local governments. In addition, the review identifies challenges to be addressed and offers policy recommendations. There are five main conclusions: (1) expedite the development of market-based and network-based governance systems; (2) pursue the harmonization of policies by avoiding contradiction and fragmentation; (3) develop new policies, especially in the building and transportation sectors; (4) embrace surveillance technologies to improve implementation and compliance; and (5) ensure just transition by implementing policy to reduce the negative socioeconomic impacts on fossil fuels-based communities and workers. This review serves as a useful guide for scholars interested in China's clean and low-carbon energy transition. [ABSTRACT FROM AUTHOR]

Adoption and improvement of energy efficiency is one of the recommended pathways to tackle the problems of growing energy demand and greenhouse gas emissions. However, studies show that rebound effects from energy efficiency improvements can erode anticipated energy savings. This paper elucidates the rebound effect arising from energy efficiency initiatives in Kenya. The study uses Index Decomposition Analysis to assess the drivers of Kenya's total primary energy supply. The paper then adopts the neoclassical growth model in the empirical analysis of energy and carbon rebound effects at the macro-economic level. Cobb-Douglas production function is further applied using Solow growth model and energy as a factor of production to approximate technological progress. Results of decomposition of energy supply show that energy intensity and affluence are the drivers with the most significant effect on energy supply while population has less critical effect. Average energy and carbon rebound effects show partial rebounds of 15.64% and 31.41%, respectively. These results imply that there is need to accelerate the pace of transitioning to green energy as the ultimate solution to minimizing environmental impacts arising from energy use and tackling climate change. • Carbon and energy rebound effects of energy efficiency initiatives is studied. • Decomposition analysis is used to investigate drivers of energy supply. • Energy intensity and affluence have most significant influence on energy supply. • Average estimates of carbon and energy rebound effects are partial rebound effects. [ABSTRACT FROM AUTHOR]