Enhance Energy Efficiency Research Articles

Integrated Renewable Energy Systems for Buildings: An Assessment of the Environmental and Socio-Economic Sustainability

Developing a green energy strategy for municipalities requires creating a framework to support the local production, storage, and use of renewable energy and green hydrogen. This framework should cover essential components for small-scale applications, including energy sources, infrastructure, potential uses, policy backing, and collaborative partnerships. It is deployed as a small-scale renewable and green hydrogen unit in a municipality or building demands meticulous planning and considering multiple elements. Municipality can promote renewable energy and green hydrogen by adopting policies such as providing financial incentives like property tax reductions, grants, and subsidies for solar, wind, and hydrogen initiatives. They can also streamline approval processes for renewable energy installations, invest in hydrogen refueling stations and community energy projects, and collaborate with provinces and neighboring municipalities to develop hydrogen corridors and large-scale renewable projects. Renewable energy and clean hydrogen have significant potential to enhance sustainability in the transportation, building, and mining sectors by replacing fossil fuels. In Canada, where heating accounts for 80% of building energy use, blending hydrogen with LPG can reduce emissions. This study proposes a comprehensive approach integrating renewable energy and green hydrogen to support small-scale applications. The study examines many scenarios in a building as a case study, focusing on economic and greenhouse gas (GHG) emission impacts. The optimum scenario uses a hybrid renewable energy system to meet two distinct electrical needs, with 53% designated for lighting and 10% for equipment with annual saving CAD$ 87,026.33. The second scenario explores utilizing a hydrogen-LPG blend as fuel for thermal loads, covering 40% and 60% of the total demand, respectively. This approach reduces greenhouse gas emissions from 540 to 324 tCO2/year, resulting in an annual savings of CAD$ 251,406. This innovative approach demonstrates the transformative potential of renewable energy and green hydrogen in enhancing energy efficiency and sustainability across sectors, including transportation, buildings, and mining.

SWOT Analysis of Wind, Hydro, and Solar Energy Power Generation: Applications and Future Development in China

China is currently undergoing a transition in its energy structure, gradually reducing reliance on fossil fuels and increasing the proportion of clean energy sources. The government actively promotes the development of renewable energy, such as wind and solar power, while encouraging technological innovation to enhance energy efficiency. Additionally, China is exploring and promoting new energy technologies like nuclear and hydrogen power to establish a greener and low-carbon energy system in line with sustainable development goals. This paper provides a comprehensive analysis of the current status of wind, solar, and hydro energy in China using a SWOT analysis approach. It examines the strengths, weaknesses, opportunities, and threats associated with each energy source, focusing particularly on their environmental impacts, technological hurdles, and resource distribution. Wind power stands out as an essential element within China's renewable energy mix due to its substantial potential for power generation capacity - ranking second globally. However, it confronts concerns regarding its environmental implications as well as output variability. Solar energy has advantages in directing solar power conversion and easy recycling; it exhibits promising prospects. But encounters conflicts related to land use and efficiency issues. Hydropower continues to be a major contributor; nevertheless, it poses ecological and social challenges. Furthermore, this paper scrutinizes China's leadership in renewable energy while offering recommendations for sustainable development and policy improvements that can facilitate its ongoing transition towards cleaner sources of power.

The Impact of Courtyard Spatial Characteristics Across Historical Periods on Summer Microclimates: A Case Study from China

This study investigates the impact of spatial changes over a 400-year period on the summer microclimate of a residential courtyard in China. Using ENVI-met simulations, we analyze how factors such as courtyard orientation, building height, and opening positions affect the thermal environment. The results show that east–west-oriented courtyards experienced 0.2–0.4 °C lower daytime temperatures compared to north–south ones. Additionally, taller surrounding buildings increased the courtyard’s average daytime temperature by approximately 0.3–0.5 °C, while courtyards with a single opening facing the prevailing wind maintained the lowest temperatures. These findings underscore the importance of historical spatial characteristics in shaping microclimates and offer key insights for contemporary urban planning. By incorporating design strategies based on these historical spatial features, such as optimizing courtyard orientation, enhancing building height variability, and creating appropriate openings for natural ventilation, urban planners can improve microclimate conditions, reduce reliance on mechanical cooling, and enhance energy efficiency. This approach not only contributes to lowering carbon emissions but also boosts resilience to extreme heat events in urban areas, especially in regions facing rapid urbanization and climate change challenges.

A comparative analysis using LEACH protocol to enhance energy efficiency in wireless sensor networks with harmony search algorithm

Wireless sensor networks (WSNs) are critical to many applications, but their use is frequently hampered by energy constraints, particularly in remote locations. WSN nodes are typically installed in remote and frequently inaccessible locations, making battery replacement challenging, thus emphasizing the importance of energy efficiency. This research presents an energy-conserving approach centred on the Harmony Search Algorithm (HSA), optimized by considering key parameters such as the number of sensor nodes, initial energy levels, transmission range, and data rate. The network performance is tested against the LEACH algorithm by evaluating parameters including energy consumption, network lifetime, and throughput. The comparative analysis is performed using graphs depicting the energy consumption of nodes by both approaches. With the Harmony Memory Size (HMS), Harmony Memory Considering Rate (HMCR), and Pitch Adjustment Rate (PAR) adjusted for best outcomes, the suggested method maximizes the performance of WSNs by effectively regulating the energy consumption of sensor nodes. Unlike LEACH, which involves clustering of nodes and periodic rotation of clusters, HSA is based on energy-efficient harmony and does not rely on clustering, thereby finding the most energy-efficient communication path within the network. Simulation results indicate that the HSA algorithm is 9.52% more efficient, with its energy usage being 9.2% more economical compared to the LEACH algorithm. This demonstrates HSA's potential for enhancing WSN performance in energy-constrained environments.

Experimental study on designing smart antenna sensor networks and modelling management energy consumption for intelligent systems of internet of medical things

ABSTRACT The Internet of Medical Things (IoMT) is revolutionizing healthcare through technologies like artificial intelligence, data analysis, and remote monitoring. However, designing energy-efficient Wireless Body Area Networks (WBANs) remains challenging due to the complex propagation characteristics of on-body communication links, which vary with human body posture and size. This study aims to develop smart wearable antenna sensors and model energy consumption in on-body communication links. We have conducted experimental studies on monopole and patch antennas at 2.4 GHz, focusing on body morphological factors and channel characteristics. Our findings reveal that the path loss exponent of on-body links significantly varies with body posture and size, and the proposed energy consumption model effectively enhances energy efficiency during signal transmission. This research contributes to optimizing WBANs for improved healthcare applications.

Energy efficient green building design utlilising renewable energy and low-carbon development technologies

The core issue these days is to reduce carbon dioxide (CO2) emission and prevent the hole in the ozone layer. Numerous emerging environmental crises successfully tackled by coordinated global efforts in the past few years. Despite this, the present climate emergency is a much more serious threat than anything we have ever encountered and requires much more action consequently. Today, more attention is paid on green buildings in the society, which will make the use of sustainable buildings for the entire life cycle a necessity for future generations. Hence, this paper proposes a novel design model of an energy-efficient residential green building with low carbon emissions to maintain the health and enhances the productivity and living standards of inhabitants. Green building technology is utilized to enhance energy efficiency and lower carbon emissions. This design considers green, recyclable, and eco-friendly building materials, which are beneficial for human health and comply with relevant Indian standards and building codes. This building design proposes renewable energy sources (RES) integrated with the power grid, although RES powers most of the load of the green building. The proposed green building design shows effective results, i.e., building energy consumption has reduced by 50.54%, total energy consumption cost has reduced by 57.41%, and CO2 emission per month has reduced by 50.54%. In addition, stormwater-harvesting system is proposed to collect 54322.23 litres of rainwater annually, which helps in water conservation and contributes to improving the groundwater level. The proposed solid waste management plan has contributed to the achievement of regional and national Sustainable Development Goals (SDGs). Finally, there are some suggestions to promote the use of green buildings for sustainable development.

Application of Environmentally Friendly Building Materials in Urban Construction

Rapid industrialization and urbanization of modern society have led to significant environmental challenges, including climate change, resource depletion, and pollution. The construction industry, a major contributor to these issues, relies heavily on traditional building materials such as cement, steel, and bricks, which are associated with high energy consumption and environmental degradation. In response to these concerns, there has been a growing emphasis on integrating environmentally friendly building materials into urban construction to promote sustainability and reduce ecological impact. This review paper explores the development and optimization of eco-friendly materials, focusing on their benefits, types, and real-world applications. We discuss the environmental, health, and safety advantages of using sustainable materials, such as reduced resource consumption, improved indoor air quality, and enhanced energy efficiency. Various eco-friendly materials, including recycled aggregates, bio-based composites, and waste-derived products, are examined for their potential to mitigate environmental impacts and enhance building performance. Case studies of successful projects that incorporate green materials are presented to highlight practical implementations and lessons learned.

In-Depth Analysis of Photovoltaic-Integrated Shading Systems’ Performance in Residential Buildings: A Prospective of Numerical Techniques Toward Net-Zero Energy Buildings

The three categories of energy scarcity, population growth and environmental concerns explain the need for new energy sources. Saudi Arabia has become one of the regions capable of using solar energy, particularly through the use of photovoltaic systems, thanks to Saudi Arabia’s excellent ability to effectively utilize the sunlight. This study examines the performance of photovoltaic-integrated shading systems (PVIS) in enhancing energy efficiency for residential buildings under the extreme climatic conditions of Riyadh and Abha in Saudi Arabia. The study advances the knowledge of PVIS applications by addressing the dual challenges of energy efficiency and sustainability in urban residential settings. Leveraging numerical simulations conducted with EnergyPlus, the research evaluates various shading configurations, including louvers, horizontal and sidefin canopies, to quantify their impact on cooling, heating, lighting demands and energy production. The annual efficiency of the proposed integrated systems to achieve sustainable and net-zero energy buildings (NZEBs) is a key metric evaluated in this study. The key findings highlight the effectiveness of horizontal PVIS in achieving the highest energy efficiency, with up to 27.19% in Abha and 24.72% in Riyadh, based on the ratio of annual available solar energy to PV energy production. The integration of PVIS not only reduces the cooling loads by optimizing shading but also contributes significantly to renewable energy production toward NZEBs. The lifecycle cost analysis (LCCA) identifies horizontal canopies as the most cost-effective configuration, with a payback period of 8.6 years in Abha and 10.2 years in Riyadh.

Side-Gated Iontronic Memtransistor: A Fast and Energy-Efficient Neuromorphic Building Block.

Iontronic memtransistors have emerged as technologically superior to conventional memristors for neuromorphic applications due to their low operating voltage, additional gate control, and enhanced energy efficiency. In this study, a side-gated iontronic organic memtransistor (SG-IOMT) device is explored as a potential energy-efficient hardware building block for fast neuromorphic computing. Its operational flexibility, which encompasses the complex integration of redox activities, ion dynamics, and polaron generation, makes this device intriguing for simultaneous information storage and processing, as it effectively overcomes the von Neumann bottleneck of conventional computing. The SG-IOMT device achieves linear channel conductance performance metrics with switching speeds in the microsecond range and energy efficiency down to a few femtojoules, comparable to those of the brain. This finding demonstrates robustness, supporting the Atkinson-Shiffrin memorization model, and the four most common Hebbian learning rules. Overall, this SG-IOMT device architecture offers significant advantages over conventional architectures, as it yields remarkable image classification performance in convolutional neural network simulations.

Desain dan Prototipe Integrasi IoT dalam Pertanian Hidroponik Cerdas Berbasis Energi Terbarukan

This research aims to develop a prototype for an Internet of Things-based automation system powered by renewable energy, specifically solar panels, to enhance the efficiency and productivity of hydroponic farming. The study addresses critical challenges, including high energy costs and the intensive monitoring demands of conventional hydroponic systems. The experimental methodology involves designing hardware featuring Arduino Uno as the central control unit, environmental sensors (DHT22) for real-time monitoring, and automated actuators such as water pumps, fans, and LED lights. The system integration process encompasses linking the hardware to an IoT interface, followed by rigorous functional testing to evaluate system stability, energy efficiency, and operational performance under varying environmental conditions. The results demonstrate that the prototype successfully operates the entire hydroponic system using energy exclusively from solar panels, eliminating reliance on conventional electricity. The system achieves precise control over critical plant growth parameters such as temperature, humidity, and lighting, with high operational stability observed during trials. This research makes a notable contribution by innovatively integrating IoT, automation, and renewable energy, thereby enhancing energy efficiency while delivering a sustainable and environmentally friendly hydroponic farming solution. The findings have significant practical implications, particularly for implementation in remote areas with limited access to electricity. Furthermore, the study paves the way for future developments, including applications in other agricultural systems and the integration of artificial intelligence to enhance predictive analytics and automated control.

Data-Driven Technologies for Energy Optimization in Smart Buildings: A Scoping Review

Data-Driven Technologies for Energy Optimization in Smart Buildings: A Scoping Review

Evaluating the Performance of Fixed 3D-Printed and Dynamic Fabric Modules in a Second-Skin Façade System: A Residential Case Study in Southern Italy at Building and District Scales

The building sector accounts for 30% of worldwide final energy usage and 26% of global energy-linked emissions. In construction, innovative materials and systems can offer flexible, lightweight, energy-efficient solutions to achieve more efficient buildings. This study addresses the energy analysis and environmental impacts of retrofitting residential buildings in Monterusciello, Italy, using an innovative second-skin façade system design that incorporates 3D-printed and fabric modules. The purpose is to enhance energy efficiency and reduce the environmental impact of residential buildings originally constructed with prefabricated elements that have degraded over time. This research employed TRNSYS modelling to simulate energy consumption and environmental impacts at the single-building and whole-district levels, analysing the system’s effectiveness in reducing cooling and heating demands and using different materials for optimal performance. The results show that retrofitting with the second-skin façade system significantly reduces cooling energy demand by 30.2% and thermal energy demand by 3.84%, reaching a primary energy saving of 16.4% and 285 tons of CO2 emissions reduction for the whole district. The results highlight the potential of second-skin façade systems in improving energy efficiency and environmental sustainability, suggesting future research directions in material innovation and adaptive system development for district-wide applications.

Introduction to ORC–VCC Systems: A Review

The increasing demand for sustainable energy solutions has spurred significant interest in cogeneration technologies. This study introduces a novel integrated organic Rankine cycle (ORC) and vapor compression cycle (VCC) system, specifically designed to enhance energy efficiency and reduce greenhouse gas emissions in industrial applications and district heating systems. The key innovation lies in the development of an advanced coupling mechanism that seamlessly connects the ORC and VCC, enabling more efficient utilization of low-grade heat sources. By optimizing working fluid selection and implementing a shared shaft connection between the ORC turbine and VCC compressor, the system achieves dual functionality—simultaneous electricity generation and cooling—with higher efficiency than conventional methods. Thermodynamic analyses and experimental results demonstrate that the proposed ORC–VCC system can significantly reduce operational costs and decrease reliance on fossil fuels by leveraging renewable energy sources and industrial waste heat. Additionally, the study addresses integration challenges by introducing specialized components and a modular design approach that simplifies installation and maintenance. This innovative system not only enhances performance but also offers scalability for various industrial applications. By providing a detailed evaluation of the ORC–VCC integration and its practical implications, this work underscores the system’s potential to contribute substantially to a sustainable energy transition. The findings offer valuable insights for future research and development, highlighting pathways to overcome existing barriers in cogeneration technologies.

Computational Fluid Dynamics Analysis of a Unique Biodiesel Production System based on Hydrodynamic Cavitations

Purpose: The study aims to improve biodiesel production through hydrodynamic cavitation, focusing on increased energy efficiency, higher yields, and reduced production time. By optimising the production process, especially with the use of waste cooking oil. Design/Methodology/Approach: A computational fluid dynamics (CFD) analysis was performed to model the flow of biodiesel within a multi-plate system featuring several orifices. Theoretical input and output velocities calculations were derived from experimental mass flow rates. The CFD analysis provided pressure distribution along the pipe walls, which was utilised to assess the lifespan and damage cycles of the cavitation pipe and to study the behaviour of fluid turbulence. Research Limitation: The research focuses on simulating flow behaviour in acrylic pipes within designated boundary conditions. Findings: The research showed that producing biodiesel through hydrodynamic cavitation markedly lowers production expenses and duration while enhancing energy efficiency and output. Computational fluid dynamics (CFD) analysis offered valuable information about the distribution of pressure, velocity, and turbulence, aiding in optimising the cavitation pipe design. Practical Implication: An optimised design for cavitation chambers has the potential to enhance the cost-effectiveness and efficiency of biodiesel production, positioning it as a useful substitute for traditional fuels. Social Implication: Embracing this technology can help mitigate environmental pollution by repurposing waste cooking oil and lessening reliance on non-renewable petroleum fuels, thereby supporting global sustainability objectives. Originality/Value: This study introduces an innovative method for producing biodiesel using hydrodynamic cavitation and CFD analysis to improve pipe design and production parameters. It addresses a significant gap in boosting biodiesel's economic and environmental feasibility, offering a scalable and sustainable alternative for fuel production. .

Enhancing sustainability in LNG carriers through integrated alternative propulsion systems with Flettner rotor assistance

The maritime industry is actively seeking sustainable solutions to reduce ship emissions and enhance energy efficiency. This study explores the use of alternative fuels and renewable energy sources, focusing on the potential environmental and economic benefits of combining natural gas (NG) fuel with Flettner rotor (FR) technology. The research employs technical, environmental, and economic models to evaluate various scenarios integrating NG fuel with FR in alternative propulsion systems. It investigates three propulsion configurations for LNG vessels: diesel engine (DE-FR), dual fuel diesel engine (DFE-FR), and combined gas and steam turbine engines (COGAS-FR). Results indicate that utilizing six Flettner rotors produces 1.254 MW, resulting in fuel savings of 3.49% to 4.49%, along with notable emission reductions. The COGAS-FR system emerges as the most environmentally friendly option, enhancing energy efficiency by 4.68% based on current ship standards. From an economic perspective, transitioning to the DFE-FR system is identified as an optimal eco-friendly choice, leading to a 9.85% reduction in the levelized energy cost compared to DE-FR. However, it is noteworthy that the COGAS-FR system has the most significant environmental impact, with a cost-effectiveness of $10,954.6 per ton.

Enhancing energy efficiency and QoS in 5G networks with dynamic resource optimisation green communication protocol

Enhancing energy efficiency and QoS in 5G networks with dynamic resource optimisation green communication protocol

Enhancing energy efficiency and reliability in wireless sensor networks using BioGAT optimization

The BioGAT model, as proposed, presents a novel methodology for enhancing the efficiency of wireless sensor networks (WSNs), which are essential elements of contemporary communication and sensing systems. For real-time monitoring and data analysis, WSNs are comprised of autonomous sensor nodes that are outfitted with processing, wireless communication, and sensing capabilities. These nodes are deployed in a variety of environments. By means of an advanced optimization model, this work aims to address critical challenges in WSNs, specifically in the areas of node placement, energy efficiency, and network reliability. By utilizing biogeography-based optimization (BBO) and graph attention networks (GAT), the BioGAT model endeavors to dynamically adapt to network changes while achieving a balance between efficient coverage and energy consumption. Cluster heads (CHs), which are essential for the aggregation of data, have a significant impact on improvements in energy efficiency and the longevity of networks. By means of comprehensive simulations and evaluation, this study presents exceptional outcomes. The BioGAT model outperforms prior approaches by attaining a 95% packet delivery ratio and an enhanced throughput. In addition, the model effectively decreases mean energy consumption, underscoring its capacity to improve the sustainability and dependability of networks in a variety of WSN applications.

Predictive Energy Demand and Optimization in Metro Systems Using AI and IoT Technologies

Introduction: With the rapid urbanization of modern cities, metro systems have become indispensable for efficient mobility. However, the increasing demand for public transportation has led to rising energy consumption, posing significant challenges for operational sustainability. Current energy management strategies in metro networks rely on static models and centralized systems, which often fail to adapt to real-time fluctuations in energy demand, leading to inefficiencies and wasted resources. Methods: This paper proposes an innovative approach to optimizing energy demand in metro systems by integrating Artificial Intelligence (AI) and the Internet of Things (IoT). By leveraging real-time data collected from IoT sensors deployed throughout the metro network, we apply machine learning algorithms such as Random Forests and Neural Networks to dynamically predict energy demand. These predictions enable metro operators to adjust energy consumption in real-time, thus improving overall system efficiency and reducing operational waste. Our approach was validated using data from the Parisian metro system through extensive simulations. Results: The results of simulations demonstrate significant improvements in energy efficiency. Optimized energy demand management led to a reduction in wasted energy during metro operations, particularly through the utilization of regenerative braking systems. Conclusions: Our findings suggest that integrating AI and IoT technologies into metro systems significantly improves energy efficiency by enabling dynamic energy demand prediction and real-time adjustment of energy consumption. The proposed system is scalable and adaptable, making it suitable for application in metro networks globally, thereby enhancing energy efficiency and supporting sustainable transport initiatives.

Developing a Passive Energy Consumption Reduction Solution

This study focuses on optimizing the energy efficiency of polyethylene tunnel greenhouses in Mediterranean climates using Design Builder and EnergyPlus software. The research examines the impact of different greenhouse orientations and opening configurations on energy consumption for heating and cooling. The east-west (90°) orientation was found to be the most effective in reducing cooling needs during summer while slightly increasing winter heating requirements. Various opening configurations were tested, including 0%, 20%, 40%, 60%, 80%, and 100%, with openings positioned at the bottom on one side and the top on the opposite side. The 20% opening configuration was identified as optimal for annual energy management. However, a monthly adaptive planning strategy was developed to further enhance energy efficiency. This planning involves keeping the greenhouse closed during winter, using 100% openings in summer, and 20% openings during transitional months. The proposed monthly planning resulted in a significant reduction in energy consumption, decreasing daytime usage by 27.3%, night time usage by 29%, and overall annual energy consumption by 27.6%. This research demonstrates that strategic orientation and adaptive opening management can substantially improve the energy efficiency of greenhouses in Mediterranean climates.

Utilization of refuse-derived fuel in industrial applications: Insights from Uttar Pradesh, India.

Urbanization and population growth in India have quickened, leading to an annual generation of around 62 million tonnes of municipal solid waste (MSW). Improper management of organic waste presents a major environmental problem due to air and water pollution, soil contamination and greenhouse gas production. This research aims to develop refuse-derived fuel (RDF) as a viable option, converting waste into a high-calorific energy carrier for industrial use. The RDF samples were collected from five strategic locations in Uttar Pradesh: Morta Site, Pipeline Site, and Sector 146 Noida, covering various waste compositions found at these landfill sites. Proximate and ultimate analyses of the RDF prepared from these sources were conducted, followed by in-depth Thermogravimetric Analysis (TGA) to validate its suitability as a potential feedstock. Careful waste segregation and treatment for better fuel quality can help minimize the difference in calorific values between different sites. Based on RDF tests, the waste-to-energy technology can divert over 30% of solid waste from landfills and cut greenhouse gas emissions by as much as 25% compared to traditional disposal methods. Unlike RDF, which is part of the replacement line for coal in industrial furnaces such as thermal power plants, it eliminates over 15% and 20% of sulfur dioxide (SO2) and nitrogen oxides (NOx). Ensuring that RDFs support sustainable energy technologies and align with circular economy principles, the study's results could enhance energy efficiency in waste management and complement environmental policy goals across all states in India and worldwide.