Energy Conservation Strategies Research Articles

Prediction of residential building occupancy using Machine learning with integrated sensor and survey Data: Insights from a living lab in Morocco

Building occupancy information is essential for effective energy management in buildings through the adoption of energy conservation and occupant-centric control strategies. These strategies endeavor to contribute to optimizing energy consumption while ensuring occupant comfort. This study focuses on advanced occupancy modeling techniques to enhance energy efficiency in residential buildings, utilizing various data-driven techniques. Various Machine Learning models, such as Random Forest, Bayesian Network, Decision Trees, Support Vector Machines, K-Nearest Neighbors, eXtreme Gradient Boosting, and Regularized Greedy Forest, have been evaluated for predicting and classifying building occupancy. Employing a living lab approach within a residential setting, the research evaluates model performance using two ground truth datasets: IoT sensor and survey data. Experimental tests use Accuracy and F1_score as evaluation criteria, demonstrating accuracy rates ranging from 70% to 95.96%. The results highlight the performance of these models in predicting residential occupancy, offering valuable insight into two approaches to occupancy modeling. The Random Forest model performs exceptionally well in capturing occupancy trends, while the Bayesian Network model, combined with expert knowledge, provides detailed predictions of occupancy types and zones. The research also addresses challenges related to data collection, including privacy concerns. It presents effective occupancy modeling strategies for residential energy management.

Prediction of residential building occupancy using Machine learning with integrated sensor and survey Data: Insights from a living lab in Morocco

Building occupancy information is essential for effective energy management in buildings through the adoption of energy conservation and occupant-centric control strategies. These strategies endeavor to contribute to optimizing energy consumption while ensuring occupant comfort. This study focuses on advanced occupancy modeling techniques to enhance energy efficiency in residential buildings, utilizing various data-driven techniques. Various Machine Learning models, such as Random Forest, Bayesian Network, Decision Trees, Support Vector Machines, K-Nearest Neighbors, eXtreme Gradient Boosting, and Regularized Greedy Forest, have been evaluated for predicting and classifying building occupancy. Employing a living lab approach within a residential setting, the research evaluates model performance using two ground truth datasets: IoT sensor and survey data. Experimental tests use Accuracy and F1_score as evaluation criteria, demonstrating accuracy rates ranging from 70% to 95.96%. The results highlight the performance of these models in predicting residential occupancy, offering valuable insight into two approaches to occupancy modeling. The Random Forest model performs exceptionally well in capturing occupancy trends, while the Bayesian Network model, combined with expert knowledge, provides detailed predictions of occupancy types and zones. The research also addresses challenges related to data collection, including privacy concerns. It presents effective occupancy modeling strategies for residential energy management.

The Role of Greenhouse Technology in Streamlining Crop Production

Greenhouse technology has revolutionized modern agriculture by enabling year-round crop production, optimizing resource utilization, and enhancing crop yields and quality. This comprehensive review explores the multifaceted role of greenhouse technology in streamlining crop production processes. It delves into the principles of greenhouse design, covering essential components such as structural materials, covering materials, and environmental control systems. The article discusses the advantages of greenhouse cultivation, including extended growing seasons, protection from adverse weather conditions, and reduced pest and disease pressure. It examines the use of advanced technologies like hydroponics, aeroponics, and aquaponics in greenhouse systems, highlighting their potential for maximizing resource efficiency and minimizing environmental impact. The review also addresses the integration of precision agriculture techniques, such as sensors, automation, and data analytics, for optimizing greenhouse operations. Furthermore, it explores the economic aspects of greenhouse crop production, including initial investment costs, operational expenses, and market opportunities. The article emphasizes the importance of sustainable practices in greenhouse agriculture, focusing on energy conservation, water management, and waste reduction strategies. It also discusses the challenges associated with greenhouse technology adoption, such as high initial costs, technical complexity, and the need for skilled labor. Finally, the review concludes by outlining future research directions and the potential for greenhouse technology to contribute to global food security and sustainable agricultural practices.

Unravelling the halophyte Suaeda maritima as an efficient candidate for phytostabilization of cadmium and lead: Implications from physiological, ionomic, and metabolomic responses

Cadmium (Cd) and lead (Pb) are among the most toxic heavy metals affecting human health and crop yield. Suaeda maritima (L.) Dumort is an obligate halophyte that is well adapted to saline soil. The inbuilt salinity tolerance mechanisms of halophytes help them to survive in heavy metal-contaminated rhizospheric soil. In the present study, growth and ionomic responses, reactive oxygen species (ROS) accumulation, modulations of phytochelatins, antioxidative defense, and metabolomic responses were studied in S. maritima imposed to Cd and Pb stresses with an aim to elucidate Cd and Pb tolerance mechanisms and phytoremediation potential of this halophyte. Our results showed a reduction of biomass in S. maritima, which may serve as an energy conservation strategy for survival under heavy metal stress. The increased accumulation of ROS with concomitant higher expression of various antioxidative enzymes suggests the efficient scavenging of ROS. The metabolite profiling revealed significant up-regulation of sugars, sugar alcohols, amino acids, polyphenols, and organic acids under Cd and Pb stresses suggesting their possible role in osmotic balance, ionic homeostasis, ROS scavenging, and signal transduction for stress tolerance. In S. maritima, the translocation factors (Tf) are <1 in both Cd and Pb treatments, which indicates that this halophyte has high phytostabilization potential for Cd and Pb in roots and through restricted translocation of heavy metal ions to the aboveground part. The findings of this study offer comprehensive information on Cd and Pb tolerance mechanisms in S. maritima and suggest that this halophyte can detoxify the HMs through physiological, ionic, antioxidative, and metabolic regulations.

Closing the Efficiency Gap: Insights into curbing the direct rebound effect of residential electricity consumption in Saudi Arabia

The rebound effect refers to the phenomenon where energy efficiency improvements lead to increased energy consumption, offsetting some of the expected energy savings. This article aims to estimate the direct rebound effect of residential electricity consumption in Saudi Arabia and explores potential solutions to mitigate its impact. Understanding the magnitude of the rebound effect is crucial for policymakers to develop effective energy conservation strategies. This study employs a time-series modeling approach, using a dataset covering 31 years, 1990–2021, and four regions within Saudi Arabia, incorporating various socioeconomic and energy-related variables. The magnitude of the rebound effect in residential electricity consumption in the Kingdom, which varies across regions, ranges from 41% to 71%. Since the inception of the first wave of the energy price reform in 2016, the Kingdom has witnessed a power consumption rebound in the residential sector totaling 39.02 TWh (6.5 Twh per annum), and a total of 28.13 Mt. in CO2 equivalent emissions (4.69 Mt. in CO2 equivalent per annum) during the period of 2016–2021. These findings add to the existing literature on the rebound effect, further enriching our understanding of this complex phenomenon and its implications. They also provide valuable insights for policymakers and energy planners in Saudi Arabia, helping them develop effective strategies to minimize the rebound effect and promote energy conservation.

Sleep Posture Influences Metabolic Rate And Vigilance in The Common Whitethroat (Curruca Communis).

Migration is an important life-history strategy that is adopted by a significant proportion of bird species from temperate areas. Birds initiate migration after accumulating considerable energy reserves, primarily in the form of fat and muscle. Sustained exercise, such as during the crossing of ecological barriers, leads to the depletion of energy reserves and increased physiological stress. Stopover sites, where birds rest and restore energy, play a fundamental role in mitigating these challenges. The duration of resting at stopover sites is influenced by environmental and physiological conditions upon arrival, and the amount of body fat reserves plays an important role. While sleep is recognized as essential for all organisms, its importance is accentuated during migration, where energy management becomes a survival constraint. Previous research indicated that individuals with larger fat reserves tend to sleep less and favor an untucked sleep posture, influencing energy recovery and anti-predatory vigilance. We explored the relationship between sleep behavior and posture, metabolic state, and energy conservation strategies during migration in the common whitethroat (Curruca communis). We were able to confirm that sleeping in a tucked position results in metabolic energy savings, at the cost of reduced vigilance. However, whitethroats did not show alterations of their sleep patterns as a response to the amount of stored reserves. This suggests that they may not be taking full advantage of the metabolic gains of sleeping in a tucked posture, at least at this stage of their migratory journey. We suggest that, to achieve optimal fuel accumulation and maximize stopover efficiency, whitethroats prioritize increased foraging over modulating their sleep patterns.

A Bibliometric Analysis of the Outdoor Thermal Environment Based on CiteSpace

The outdoor thermal environment (OTE) is closely related to sustainable urban development and human living, and related research has attracted widespread attention. The research hotspots and research frontiers were obtained using CiteSpace to analyze 4473 relevant studies published in English from the Web of Science (WOS) core database from 1998 to 2023. The results show that (1) Hong Kong Polytechnic University, National University of Singapore, Chinese Academy of Sciences, Tsinghua University, and Harbin Institute of Technology are important in OTE research. China has the largest number of publications in the field of OTE, but the United States has the greatest centrality and significant influence. (2) The focus of OTE keyword clustering research is divided into four main categories: thermal environment perception, the thermal environment index, thermal environment quality, and thermal environment optimization. (3) The frontiers of OTE research have changed from focusing on environmental quality, thermal perception, numerical simulation, urban space, and thermal adaptation to thermal mitigation, energy conservation, energy consumption, and optimization strategies. Visualization research in the field of OTE helps to provide references for the direction of future research on improving climate change, human thermal comfort, urban planning, and pre-planning.

Strategies for energy conservation and sustainability

Strategies for energy conservation and sustainability

Magnetic biochar catalyst from reed straw and electric furnace dust for biodiesel production and life cycle assessment

A novel magnetic carbon-based catalyst was prepared from solid waste (reed straw and electric furnace dust) by coprecipitation and high temperature pyrolysis with excellent application potential. Single factor and response surface experiments were used to optimize the catalyst preparation process (mass ratio of reed straw/electric furnace dust of 5:1 at 500 °C in 4 h) and biodiesel production, respectively, with results of 99.89 wt% biodiesel yield in the first cycle (93.61 wt% after 11 cycles) obtained at 74.15 °C in 4.16 h with a 14.06:1 M ratio of methanol/oil and 7.75 wt% catalyst. The life cycle assessment of magnetic carbon-based catalysts for biodiesel production suggested that the soybean oil extraction stage had the greatest impact on the environment, mainly from the use of soybeans and electricity. Solid waste as raw material to prepare catalysts for biomass energy conversion was proven to be a good strategy for energy conservation and emission reduction. This study provides guidance sustainable biomass energy conversion with low cost, low energy consumption, and minimal negative environmental impact.

MmcA is an electron conduit that facilitates both intracellular and extracellular electron transport in Methanosarcina acetivorans

Methanogens are a diverse group of Archaea that obligately couple energy conservation to the production of methane. Some methanogens encode alternate pathways for energy conservation, like anaerobic respiration, but the biochemical details of this process are unknown. We show that a multiheme c-type cytochrome called MmcA from Methanosarcina acetivorans is important for intracellular electron transport during methanogenesis and can also reduce extracellular electron acceptors like soluble Fe3+ and anthraquinone-2,6-disulfonate. Consistent with these observations, MmcA displays reversible redox features ranging from −100 to −450 mV versus SHE. Additionally, mutants lacking mmcA have significantly slower Fe3+ reduction rates. The mmcA locus is prevalent in members of the Order Methanosarcinales and is a part of a distinct clade of multiheme cytochromes that are closely related to octaheme tetrathionate reductases. Taken together, MmcA might act as an electron conduit that can potentially support a variety of energy conservation strategies that extend beyond methanogenesis.

Cu, Co co-doped Ni3S2 nanosheets grown on nickel foam as an efficient catalyst for urea oxidation reaction

Doping modification can significantly enhance the catalytic performance of Ni3S2 in urea oxidation reaction (UOR). In this study, we synthesized Cu, Co co-doped Ni3S2 nanosheets on nickel foam (Cu/Co-Ni3S2/NF) through a two-step hydrothermal reaction. Cu, Co dual-doped Ni3S2 nanosheets exhibited a thickness of about 30 nm, composed of nanoparticles. Benefiting from the synergistic regulation of Cu and Co dopants on electronic structure, increased availability of active sites, boosted electron transference rates, and improved electrical conductivity, Cu/Co-Ni3S2/NF exhibited an excellent UOR catalytic performance and enhanced reaction kinetics, offering a low potential of 1.350 V at 100 mA cm-2, along with a low Tafel slope of 15.5 mV dec-1. Moreover, Cu/Co-Ni3S2/NF coupled with Pt/C/NF only necessitated 1.68 V to drive 100 mA cm-2 for overall urea splitting, which is lower than that of traditional water splitting (1.996 V). This indicates that the addition of urea into electrolyte is an energy-conserving strategy for hydrogen production from water electrolysis. This work provides a novel dual-ion doping method to design a highly efficient electrocatalysts for UOR.

IoT energy efficiency routing protocol using FHO‐based clustering and improved CSO model‐based routing in MANET

SummaryMany protocols, services, and electrical devices with built‐in sensors have been developed in response to the rapid expansion of the Internet of Things. Mobile ad hoc networks (MANETs) consist of a collection of autonomous mobile nodes that can form an ad hoc network in the absence of any pre‐existing infrastructure. System performance may suffer due to the changeable topology of MANETs. Since most mobile hosts operate on limited battery power, energy consumption poses the biggest challenge for MANETs. Both network lifetime and throughput improve when energy usage is reduced. However, existing approaches perform poorly in terms of energy efficiency. Scalability becomes a significant issue in large‐scale networks as they grow, leading to overhead associated with routing updates and maintenance that can become unmanageable. This article employs a MANET routing protocol combined with an energy conservation strategy. The clustering hierarchy is used in MANETs to maximize the network's lifespan, considering its limited energy resources. In the MANET communication process, the cluster head (CH) is selected using Fire Hawk Optimization (FHO). When choosing nodes to act as a cluster for an extended period, CH election factors in connectivity, mobility, and remaining energy. This process is achieved using an optimized version of the Ad hoc On‐Demand Distance Vector (AODV) routing protocol, utilizing Improved Chicken Swarm Optimization (ICSO). In comparison to existing protocols and optimization techniques, the proposed method offers an extended network lifespan ranging from 90 to 160 h and reduced energy consumption of 80 to 110 J, as indicated by the implementation results.

Comparative analysis of space layouts and facade systems for office retrofit design in hot climate

ABSTRACT Worldwide, office buildings account for almost one-third of global energy consumption. Therefore, the energy retrofit design of office buildings could reduce total energy consumption. Considering the benefits of advanced facade systems, retrofit facade design is an effective strategy for energy conservation while improving daylight performance, occupant well-being, and productivity. This paper compares the daylight and energy performance of single and double-skin facade systems used in a typical office building in a hot climate with different space layouts. The main objective is to optimize the daylight and energy performance of various facade systems in combination with a wide range of design variables. Simulations were conducted in DesignBuilder software using a multi-objective optimization approach. Eleven design variables and 103 simulations were considered with the objective of enhancing daylight performance while reducing cooling and lighting loads. Based on the results, single-skin facade configurations could enhance daylight performance significantly compared to double-skin facades, while double-skin facades performed better by reducing the risk of glare and annual energy consumption. Using single and double-skin facade systems could reduce annual total energy consumption by 50% and 60% compared to the existing building.

Urban population density and energy conservation: Empirical evidence from 276 cities in China

Reducing urban energy consumption is a crucial step towards achieving sustainable urban development. Urban energy plays a fundamental role in urban development, and while previous studies have examined the relationship between population size and energy conservation, the impact of increasing population density on per capita energy consumption (PCEC) remains unclear. To achieve urban energy conservation in China, it is vital to comprehend this significant relationship. This study constructs a spatial regression model to examine the relationship between population density and PCEC using 9 years of balanced panel data from 276 cities to fill a gap in the literature. The results of spatial autocorrelation indicate a significant negative relationship and heterogeneity between population density and PCEC. The results of spatial regression show that for every 1% increase in population density, there is a subsequent increase in PCEC of 0.074%. Our findings suggest that lower PCEC correlation is associated with higher urban population density. This study can be a reference for policymakers seeking new energy conservation strategies for urban development.

Increased Confidence and Deeper Understanding of Fatigue Following Participation in Fatigue Education and Management Education in Systemic Sclerosis: A Mixed Methods Evaluation of a Virtual Intervention.

No fatigue-specific programs exist for people with systemic sclerosis (SSc) despite the burden of fatigue and negative impact on daily activities. This study used a convergent parallel mixed methods design to evaluate the impact of an adapted virtual intervention, Fatigue and Activity Management Education in Systemic Sclerosis (FAME-iSS), in the United States. Eighteen people with SSc participated in three separate six-week FAME-iSS programs. Participants completed the modified Fatigue Impact Scale (m-FIS), the Self-Efficacy for Performing Energy Conservation Strategies Assessment (SEPESCA), the Patient-Reported Outcomes Measurement Information System (PROMIS) Self-Efficacy for Managing Symptoms, and the Hospital Anxiety and Depression Scale (HADS) before, immediately after, and three months post intervention. Data were analyzed using descriptive and nonparametric inferential statistics. Participants' perceptions of the program and their use of fatigue management strategies were qualitatively analyzed using content analysis. Eighty-nine percent of participants were women with a mean ± SD age of 52.0 ± 11.6 years and a mean ± SD disease duration of 13.7 ± 14.5 years, and more than 70% had a college degree. Significant improvements were observed for self-efficacy on the PROMIS Self-Efficacy for Managing Symptoms (P = 0.002) and SEPESCA (P = 0.016) immediately post intervention, which continued to significantly improve up to the three-month follow-up (P = 0.006 and 0.035, respectively). Significant improvements were also observed for the m-FIS between baseline and the three-month follow-up (P = 0.029). Participants reported a deeper understanding of fatigue and that they liked sharing strategies and experiences with each other along with the facilitator, citing that "there was a power in our group because we had a common condition." FAME-iSS resulted in improvements in the impact of fatigue and self-efficacy for managing symptoms and performing energy conservation strategies. Feedback was positive, and the virtual format allowed for greater accessibility and sharing of strategies.

A novel optimization method of carbon reduction strategies implementation for industrial parks

The effects of various energy conservation and carbon reduction (ECCR) strategies can differ significantly despite equal investment. Given limited amount of capital expenditure, managers and planners of industrial parks must carefully select from different ECCR strategies and implementation technologies to maximize investment returns. This study establishes mathematical models for four ECCR strategies: forestry carbon sequestration (FCS), carbon capture and utilization (CCU), waste heat recovery (WHR), and photovoltaic (PV). A universal ECCR planning optimization model is constructed to maximize annual economic benefits or carbon emission reduction. Using an industrial park in southern China as a case study, genetic algorithms are utilized to solve the model and validate its feasibility. The study analyzes three key parameters: capital expenditure caps, carbon trading price in the Emission Trading Scheme, and transportation distance of captured CO2 products for sensitivity. The results demonstrate considerable economic benefits of the CCU strategy when demand matches appropriately. However, in cases with limited capital expenditure, implementing small-scale FCS strategies in industrial parks is not advisable from both an economic and environmental perspective.

Investigation of the Performance of Zero Energy Homes in Hot Climates

Globally, the rate at which buildings use resources and energy has been rising. Due to population growth, rise in living standard, and global warming, strategies for energy conservation have been adopted lately in zero energy buildings. Over the past decade, the energy consumption in constructions has increased at an unprecedented rate. Therefore, it is of great importance to mandate energy rationalization in building construction. This research investigates the impact of applying zero energy concept in homes in Egypt. The study begins by analysing the current situation of the energy sector and existing buildings in Egypt, the NZEB concept is defined and its different aspects are highlighted. Energy simulation by DesignBuilder simulation software is used to evaluate energy performance for a residential single family house model after applying Passive and Active design strategies. A number of energy saving strategies have been examined to optimize the building envelope with minimum energy requirements. The building energy consumption was reduced when various energy efficient strategies were combined. Besides utilizing energy efficient HVAC systems. a solar PV system is installed to meet the reduced energy. The case study was transformed into a zero-energy house. Results show that passive and active techniques can be dependable for steady energy production in buildings in hot dry regions.

A Safe Virtual Machine Scheduling Strategy for Energy Conservation and Privacy Protection of Server Clusters in Cloud Data Centers

A Safe Virtual Machine Scheduling Strategy for Energy Conservation and Privacy Protection of Server Clusters in Cloud Data Centers

Who Will Save Energy? An Extension of Social Cognitive Theory with Place Attachment to Understand Residents’ Energy-Saving Behaviors

With environmental concerns gaining prominence, the study of energy-saving behavior (ESB) has captured global expert attention. This research applied the SCT model and utilized survey data collected in Jiangsu Province to explore the factors influencing residents’ energy-saving behavior (ESB). The findings reveal that self-efficacy, attitudes, and social norms are direct positive determinants of ESB. Additionally, these factors mediate the positive relationship between knowledge and ESB. Notably, knowledge enhances self-efficacy, attitudes toward energy saving, and adherence to social norms, while outcome expectations improve attitudes and norms. Place attachment also emerges as a significant predictor of ESB, exerting its influence indirectly through attitudes and social norms. These insights enrich social cognitive theory by incorporating place attachment to examine ESB, substantially contribute to the discourse on environmental protection, and have implications for energy conservation strategies globally.

Passive Energy Conservation Strategies for Mitigating Energy Consumption and Reducing CO2 Emissions in Traditional Dwellings of Peking Area, China

Within China, brick dwellings stand as archetypal relics of traditional habitation, embodying a “living fossil” status. The sustainability of these dwellings is contingent upon the integration of energy-conservation strategies. This study scrutinized and empirically assessed a representative dwelling in the Peking area. Using numerical simulations, the impact on energy consumption of factors such as insulation and glazing type, external wall thickness, insulation thickness, and solar energy utilization was evaluated. The outcomes reveal that introducing external thermal insulation—specifically, expanded polystyrene panels with a thickness of 60 mm and 40 mm for the roof and exterior walls, respectively—along with a sunspace of depth 1.5 m yielded superior energy efficiency. Additionally, substituting conventional roofing with solar tiles exhibited a potential annual electricity generation coupled with an annual solar radiation conversion efficiency of 17%. Collectively, these strategies induced a substantial reduction in annual energy consumption. This study presents tailored energy-conservation measures and provides design decision support for architects’ practical recommendations on thermal environment control of passive traditional dwellings in the Peking area.