Energy Efficiency Perspective Research Articles

The impact of artificial intelligence on global energy vulnerability

Investigating the effect of artificial intelligence (AI) on energy vulnerability (EVI) is crucial to understanding how technological advances are changing the resilience and sustainability of energy systems. However, their quantitative relationship still lacks empirical evidence. This study first constructs the EVI of 54 global economies from the perspective of energy security, energy consumption, energy efficiency, and energy availability from 2000 to 2019. Then, a fixed-effect model is employed to investigate the relationship between AI and EVI. Results show that (1) AI can considerably reduce global EVI. The core findings remain reliable after several robustness checks. (2) Mechanism analysis implies that AI can reduce EVI by promoting financial development and technological progress. (3) Heterogeneity analysis implies that the impeding role of AI on EVI is more pronounced in countries with low incomes and industrialization levels. Furthermore, the hindering effect of AI on EVI is strengthened after Industry 4.0 and the financial crisis. Some policy implications are further proposed accordingly to reduce global EVI.

Holistic Assessment for Social Housing Retrofitting: Integrating Seismic, Energy, and Social Aspects in the REHOUSE Project

There are many existing buildings for which seismic rehabilitation interventions are required, especially in earthquake-prone areas like Italy. At the same time, the huge energy cost increase in Europe highlights the need for sustainable techniques that are able to increase the energy efficiency of buildings. These issues are even more significant for weak social groups living in social housing buildings, often in poor and vulnerable conditions. In order to address the solution regarding building renovations from the social, structural, and energy efficiency perspectives, in the framework of the Horizon Europe REHOUSE (Renovation packagEs for HOlistic improvement of EU’s bUildingS Efficiency, maximizing RES generation and cost-effectiveness) Project, this paper proposes an integrated methodology of building assessment that was tested on a social housing building in Margherita di Savoia, a small town of Apulia Region, Italy. In addition to the structural and energy aspects, the social one is particularly important since the building is located in the “Capitanata Area”, considered to be one of the most socially vulnerable areas in Italy. For this reason, an assessment methodology must consider reducing the overall impact of the assessment activities while explaining to tenants the purpose of the assessment and future renovation actions, maintaining the accuracy of the assessment results. Therefore, this study outlines an assessment methodology, demonstrated through its application to the case study building, that integrates the structural, energy, and social aspects, showing that the tenants’ involvement is also crucial for the technical evaluations. The final result is a low-impact approach for the building knowledge gathering needed to start a deep renovation intervention in social housing.

Comparing green hydrogen and green ammonia as energy carriers in utility-scale transport and subsurface storage

Many of the challenges associated with utility-scale hydrogen transport and storage relate to its low density, high diffusivity, and the risk of hydrogen embrittlement, motivating consideration to integrating ammonia as an energy carrier. Compared to hydrogen, ammonia is more compatible with pipeline materials and delivers energy at higher density. Ammonia is also a mature industry with a greater extent of established pipeline networks and regulations that may accelerate hydrogen transitions and penetration in energy grids. However, converting hydrogen produced by renewable-driven electrolysis into ammonia (and back to hydrogen, depending on end use) complicates logistics, and associated energy and resource demands may offset the green hydrogen's carbon neutrality. This work outlines core considerations for the use of hydrogen vs. ammonia during transport and storage operations, with an emphasis on green hydrogen or green ammonia pathways coupled to pipeline transport and underground storage. We compare tradeoffs in pipeline infrastructure and operations; subsurface storage options; and project economics. We also evaluate round-trip efficiencies (RTE) for both pathways, which indicate that hydrogen is more attractive from an energy efficiency perspective for hydrogen end-use applications due to the efficiency penalties of initial ammonia synthesis and subsequent cracking, but RTE's for ammonia transport and storage are comparable to hydrogen for direct use or ammonia-to-power systems. The tradeoffs presented in this work would need to be considered on a case-by-case basis, but indicate that selective use of ammonia as an energy-dense hydrogen carrier could support decarbonization goals in industry and hydrogen economies.

A Comprehensive Review of Energy-Efficient Techniques for UAV-Assisted Industrial Wireless Networks

The rapid expansion of the Industrial Internet-of-Things (IIoT) has spurred significant research interest due to the growth of security-aware, vehicular, and time-sensitive applications. Unmanned aerial vehicles (UAVs) are widely deployed within wireless communication systems to establish rapid and reliable links between users and devices, attributed to their high flexibility and maneuverability. Leveraging UAVs provides a promising solution to enhance communication system performance and effectiveness while overcoming the unprecedented challenges of stringent spectrum limitations and demanding data traffic. However, due to the dramatic increase in the number of vehicles and devices in the industrial wireless networks and limitations on UAVs’ battery storage and computing resources, the adoption of energy-efficient techniques is essential to ensure sustainable system implementation and to prolong the lifetime of the network. This paper provides a comprehensive review of various disruptive methodologies for addressing energy-efficient issues in UAV-assisted industrial wireless networks. We begin by introducing the background of recent research areas from different aspects, including security-enhanced industrial networks, industrial vehicular networks, machine learning for industrial communications, and time-sensitive networks. Our review identifies key challenges from an energy efficiency perspective and evaluates relevant techniques, including resource allocation, UAV trajectory design and wireless power transfer (WPT), across various applications and scenarios. This paper thoroughly discusses the features, strengths, weaknesses, and potential of existing works. Finally, we highlight open research issues and gaps and present promising potential directions for future investigation.

A Comprehensive Review on Enhancing Seasonal Energy Storage Systems through Energy Efficiency Perspectives

A Comprehensive Review on Enhancing Seasonal Energy Storage Systems through Energy Efficiency Perspectives

The impact of trees on the peak cooling load of detached rural residences

Trees can reduce heat radiation for adjacent farmhouses, achieving cooling and energy-saving effects in summer. However, there is still a lack of research on the quantitative influence of trees’ parameters and their spatial orientation on the cooling load of farmhouses. This knowledge gap hampers the scientific greening of residences from an energy-efficiency perspective and leads to wasted ecological benefits. Taking Gao Hong Town’s residences in China as an example, by comprehensively applying remote sensing technology, frequency statistics, and numerical simulation, the representative tree-farmhouse information model was constructed. The ENVI-met software was used to simulate and extract the temperatures of external walls under 54 scenarios. The Radiant Time Series Method (RTSM) was then used to calculate peak cooling load with trees under different scenarios. Sensitivity analysis indicates that trees on the south side have the most significant impact on the disturbance rate of peak cooling load of trees to farmhouses (PCLTD), reaching up to 4.4 %, followed by the west, east, and north sides with PCLTD of 1.6 %, 1.1 %, and 0.8 %, respectively. According to the sensitivity of the minimum distance between wall and tree canopy (DW-T) to PCLTD, the 1 m-5 m range of DW-T can be divided into three zones: high-sensitivity (1 m-2 m), medium-sensitivity (2 m-4 m), and low-sensitivity (4 m-5 m).For trees on the south side with leaf area density (LAD) of 1 m2/m3, 2 m2/m3, and 3 m2/m3, the corresponding PCLTD are 3.4 %, 4.4 %, and 4.9 %; for Diameter of Tree Canopy (DC) of 5 m, 7 m, and 9 m, the respective PCLTD are 4.4 %, 6.2 %, and 8.3 %.To maximize the energy-saving effects of trees on farmhouses, it is recommended that the DW-T for trees on the south be less than 3 m, and for trees on the west and east, less than 2 m.These findings support optimizing tree planting strategies adjacent to rural residences in China from an energy-saving perspective, contributing to the improvement of thermal environments and the assessment of energy efficiency.

PhotoROMP: The Future Is Bright.

Since the earliest investigations of olefin metathesis catalysis, light has been the choice for controlling the catalyst activity on demand. From the perspective of energy efficiency, temporal and spatial control, and selectivity, photochemistry is not only an attractive alternative to traditional thermal manufacturing techniques but also arguably a superior manifold for advanced applications like additive manufacturing (AM). In the last three decades, pioneering work in the field of ring-opening metathesis polymerization (ROMP) has broadened the scope of material properties achievable through AM, particularly using light as both an activating and deactivating stimulus. In this Perspective, we explore trends in photocontrolled ROMP systems with an emphasis on approaches to photoinduced activation and deactivation of metathesis catalysts. Recent work has yielded a myriad of commercial and synthetically accessible photosensitive catalyst systems, although comparatively little attention has been paid to achieving precise control over polymer morphology using light. Metal-free, photophysical, and living ROMP systems have also been relatively underexplored. To take fuller advantage of both the thermomechanical properties of ROMP polymers and the operational simplicity of photocontrol, clear directions for the field are to improve the reversibility of activation and deactivation strategies as well as to further develop photocontrolled approaches to tuning cross-link density and polymer tacticity.

Enhancing Occupant Comfort and Building Sustainability: Lessons from an Internet of Things-Based Study on Centrally Controlled Indoor Shared Spaces in Hot Climatic Conditions.

It is well known that buildings have a sizeable energy and environmental footprint. In particular, in environments like university campuses, the occupants as well as occupancy in shared spaces varies over time. Systems for cooling in such environments that are centrally controlled are typically threshold driven and do not account for occupant feedback and thus are often relying on a reactive approach (fix after identifying problems). Therefore, having a fixed thermal operating set point may not be optimal in such cases-both from an occupant comfort and well-being as well as an energy efficiency perspective. To address this issue, a study was conducted which involved development and deployment of an experimental Internet of Things (IoT) prototype system and an Android application that facilitated people engagement on a university campus located in the UAE which typically exhibits hot climatic conditions. This paper showcases data driven insights obtained from this study, and in particular, how to achieve a balance between the conflicting goals of improving occupant comfort and energy efficiency. Findings from this study underscore the need for regular reassessments and adaptation. The proposed solution is low cost and easy to deploy and has the potential to reap significant savings through a reduction in energy consumption with estimates indicating around 50-100 kWh/day of savings per building and the resulting environmental impact. These findings would appeal to stakeholders who are keen to improve energy efficiency and reduce their operating expenses and environmental footprint in such climatic conditions. Furthermore, collective action from a large number of entities could result in significant impact through this cumulative effect.

Energy-Efficient BWP Configuration for Multi-Slice Users.

Fifth Generation (5G) mobile networks introduce the concept of slicing to ensure isolation among the various supported heterogeneous services. The User Equipment (UE) can be connected to multiple slices simultaneously. Additionally, the notion of a Bandwidth Part (BWP) was also instigated to reduce power consumption. A BWP is a small chunk of the bandwidth scanned by the UE to retrieve its service data. Therefore, a UE connected to multiple services can be configured with multiple BWPs each associated with a given service. Such UEs find themselves scanning multiple BWPs, which can be time consuming and highly energy intensive. Hence, it is paramount to study the appropriate choice of the BWP configuration from an energy-efficiency perspective for multi-slice users depending on their battery level. In this paper, two energy-efficient BWP selection solutions are proposed for users connected to multiple slices. The first solution is based on a centralized approach where UEs are stirred optimally to the best BWP configuration, while the second solution relies on a user-centric distributed approach using non-cooperative game theory. The proposed schemes take into account the users' battery level and their sojourn time in the network as well as the scanned BWP size. Both solutions are compared with one another and against the legacy solution. Intensive simulation results demonstrate the efficiency of our proposition in terms of users' energy efficiency and quality of service.

The impact of varying trolley case usage modes and weights on body posture

ObjectiveTo study the body posture characteristics when walking with trolley case, and to explore the effects of different usage methods and weights of trolley case on body posture characteristics. MethodsFifteen subjects pushed and pulled(Condition 1 and 2) the case with three load weights of 10 %, 20 % and 30 % of their own body weight with 0 % no load as baseline for both conditions. The basic gait parameters, kinematic and kinetic data were collected using the VICON infrared motion capture system and a 3D force platform. Two repeated measures factor (condition×weight) analysis of variance was used for statistical analysis of the gait temporal and spatial parameters, as well as trunk angle, kinetic ground reaction force, shoulder joint force, and trunk moment. ResultsSignificant condition*weight interactions were detected in DLST (Double Limb Stance Time) (F=5.341，P = 0.006), GRF (Ground Reaction Force) in frontal plane (F=10.507, p < 0.001) and vertical plane (F=3.751, p = 0.021), shoulder joint force in sagittal plane (F=21.129, p < 0.001), and flexion-extension angle of the trunk in the sagittal plane (F=4.888, p < 0.010). Significant main effects were detected in walking speed (F=35.842, p < 0.001), right support time (F=12.156, p < 0.001), left swing time (F=8.506, p < 0.001), left support time (F=1.122, p < 0.001), right step length (F=33.900, p < 0.001), and left step length (F=14.960, p < 0.001) under different weights. A significant main effect was detected in sagittal GRF (F=11.77, p < 0.001), trunk rotation angle (F=4.124, p = 0.016), amplitude of COM (F=2.993, p = 0.046), under different weights. ConclusionWhen the weight of the case exceeds 20 % of the body weight, from the perspective of energy efficiency, the push method is more advantageous than the pull method. When walking with luggage, people tend to maintain the stability of their trunk posture by adjusting the force on their arms more often.

Energy Flow Modeling and Low Carbon Analysis of Processoriented Production Line

Nowadays, energy and environmental problems are becoming more and more prominent, and the energy-based manufacturing industry also needs to face huge energy consumption problems. Therefore, production processes need to be investigated from an energy efficiency perspective at an early design stage so that maximum benefits can be obtained at low cost, low time and low risk. This process industry carbon emissions system does not calculate the consumption of raw materials and electricity in a generalized way at the boundaries of the plant. Rather, we delve into each step of the process and perform mathematical modeling of the process through a graphical approach, incorporating each link and factor that constitutes and influences the change in carbon emissions, and performing an aggregation of carbon emissions for the entire production line. It facilitates the subsequent improvement and optimization of the entire process-based production line, providing the basis for implementing and establishing the best energy-saving system.

RIS-NOMA Integrated Low-Complexity Transceiver Architecture: Sum Rate and Energy Efficiency Perspective

RIS-NOMA Integrated Low-Complexity Transceiver Architecture: Sum Rate and Energy Efficiency Perspective

UAV-BS Integration with Urban Infrastructure: An Energy Efficiency Perspective

UAV-BS Integration with Urban Infrastructure: An Energy Efficiency Perspective

Improving agricultural sustainability through farm mergers: an energy efficiency perspective

ABSTRACT The aim of this paper is to investigate agricultural sustainability as a collective issue involving multiple rather than individual farms. Through the utilization of energy consumption as a proxy, we propose a novel methodology that evaluates the impact of farm consolidations on agricultural sustainability while accounting for resource preferences. Our approach incorporates the ordered weighted averaging (OWA) operator within an inverse data envelopment analysis (IDEA) model to identify post-merger farms that meet preset efficiency targets. We employ a DEA cross-efficiency (DEA-CE) procedure to select merger plans that maximize agricultural sustainability for each preference scenario. By analysing a case study of 43 tomato greenhouse farms in Biskra, northern Algeria, our findings demonstrate that mergers can significantly enhance agricultural sustainability, surpassing the potential of individual farms by a factor of over 15. Additionally, the adoption of the most sustainable merger plan can lead to energy savings of more than 69%. Irrespective of the preference scenario, substantial energy savings in machinery, fertilizers, diesel, and electricity ranging from 22.92% to 73.73% were observed. These results emphasize the strategic role of merger processes in promoting agricultural sustainability and optimizing resource utilization.

A Thermodynamics Model for the Assessment and Optimisation of Onboard Natural Gas Reforming and Carbon Capture

The paper examines pre-combustion carbon capture technology (PreCCS) for liquefied natural gas (LNG) propelled shipping from thermodynamics and energy efficiency perspectives. Various types of LNG reformers and CCS units are considered. The steam methane reformer (SMR) was found to be 20% more energy efficient than autothermal (ATR) and methane pyrolysis (MPR) reactors. Pressure swing adsorption (PSA) had a lower energy requirement than membrane separation (MEM), cryogenic separation (CS), and amine absorption (AA) in pre-combustion carbon capture, with PSA needing 0.18 kWh/kg CO2. An integrated system combining SMR and PSA was proposed using waste heat recovery (WHR) from the engine, assuming similar efficiency for LNG and H2 operation, and cooling and liquefying of the CO2 by the LNG. The SMR-PSA system without WHR had an overall efficiency of 33.4% (defined as work at the propeller divided by the total LNG energy consumption). This was improved to 41.7% with WHR and gave a 65% CO2 emission reduction. For a higher CO2 reduction, CCS from the SMR heater could additionally be employed, giving a maximum CO2 removal rate of 86.2% with 39% overall energy efficiency. By comparison, an amine-based post-engine CCS system without reforming could reach similar CO2 removal rates but with 36.6% overall efficiency. The advantages and disadvantages and technology readiness level of PreCCS for onboard operation are discussed. This study offers evidence that pre-combustion CCS can be a serious contender for maritime propulsion decarbonization.Graphical

District Energy Viewed from the New Bauhaus Initiative Perspective—Sustainable, Inclusive and Aesthetic Heat

(1) Background: To support the energy transition in Europe, the EU has launched multiple initiatives. Supporting the “Green Deal” is the New European Bauhaus (NEB). District heating and cooling (DHC) is an important part of a decarbonized European energy system, and its role in the transition has been stressed by the EU. In this paper, DHC is, for the first time, reviewed assuming the NEB principles. (2) Method: a literature review combined with a review of three cases was used for collecting data. (3) Results: It is confirmed that DHC has strong sustainability values. It is also identified that DHC can become increasingly inclusive by adopting updated digital platforms and new technologies for heat recovery that necessitate close customer interaction whilst recovering waste heat. The least exploited principle is aesthetics. It could sharpen city planning by combining energy system and energy efficiency perspectives, increase the practice of multifunctional buildings (for example energy provision and recreation), and foster a closer interplay between architecture and energy. (4) Conclusions: for both innovating and expanding DHC, the NEB principles can serve as catalysts.

Modeling uncertainty in positive energy districts through a non-probabilistic approach

Positive Energy Districts (PEDs) transcribe an emerging energy transition paradigm for rapid upscaling of building energy efficiency programs to match the urgency of climate mitigation and adaptation. PEDs facilitate pro-active sharing of information and experiences, responsive learning and dissemination, and cooperation across sectors and disciplines. The rapid evolution of technologies for energy efficiency and integration of renewable energy in buildings requires a research-to-design approach. Therefore, it is imperative that a designer makes informed decisions at an early stage of design from an energy-efficiency perspective. However, since PED design involves a significant number of stakeholders, the design parameters could be highly uncertain, which eventually affect the quality of the design solution space. This study uses a bilateral process workflow to quantify risks using a nonprobabilistic technique and a PED roadmap structure. The workflow evaluates different PED scenarios and quantifies the PED potential for the city of Sint-Niklaas in Belgium. The results indicate that risk quantification significantly improves PED decision-making when evaluating collective solutions (district heating) for a district.

Modeling an Optimal Environmentally Friendly Energy-Saving Flexible Workshop

From the perspective of energy efficiency and environmental sustainability, the scheduling problem in a flexible workshop with the utilization of automated guided vehicles (AGVs) was investigated for material transportation. Addressing the dual-constrained integrated scheduling challenge involving machining machines and AGVs, a scheduling optimization model was established with makespan, workshop energy consumption, and processing quality as the optimization objectives. To effectively solve this model, an enhanced whale optimization algorithm (IWOA) was proposed. Specifically, nonlinear convergence factors, adaptive inertia weights, and improved helix positions were introduced into the standard whale optimization algorithm to update the model. Furthermore, a loss function was constructed based on fuzzy membership theory to obtain the optimal compromise solution of the multi-objective model. The research results indicate that: (1) The IWOA obtained the optimal solutions on benchmark instances MK01, MK02, MK04, MK07, and MK08; (2) The IWOA outperformed the WOA(1), WOA(2), WOA-LEDE, and NSGA-II algorithms in the two instances provided in this paper, demonstrating strong robustness of the model; (3) Although the multi-objective model constructed in this paper could not surpass the single-objective optimal solution in individual objectives, it achieved compensation in other objectives, effectively balancing the trade-offs among the makespan, workshop energy consumption, and processing quality of the three objectives. This research offers an effective practical approach to address green flexible workshop scheduling with AGV transportation.

Symbiotic Backscatter Communication Underlying a Cell-Free Massive MIMO System

In ambient backscatter communications, backscatter devices (BDs) utilize ambient “legacy” radio signals as both a harvested energy source and a carrier on which to modulate data. Symbiotic radio, a subtype in which the legacy system assists both its own users and underlaid BDs, has attracted much research interest recently. Furthermore, cell-free massive multiple-input multiple-output (CF mMIMO) systems are promising for beyond-5G networks from both spectral and energy efficiency perspectives. To reap the benefits of both, we consider a primary CF mMIMO system where the access points (APs) aid an underlaid BD layer to both harvest energy and reflect information toward the primary receivers (which receive data from both layers). To acquire separate channel state information (CSI) of the direct and backscattered channels at the APs, a two-phase uplink pilot training method is proposed, with the effects of pilot contamination and spatial correlation between antennas accounted for. However, the receivers are assumed to only have partial CSI (statistical knowledge plus instantaneous phase information for partially-coherent reception). Assuming uplink/downlink radio channel reciprocity, the CSI is used to design downlink precoding vectors for the APs such that channel hardening is enhanced and both primary receivers and BDs benefit. We derive expressions for the average signal-to-interference-plus-noise ratios of both primary and backscatter signals, accounting for the effects of imperfect CSI, spatial correlation, pilot contamination, and channel hardening. Furthermore, the average power harvested in the BDs is derived. Simulation results demonstrate that the performance of the proposed scheme is much more uniform across all devices with CF mMIMO than with conventional co-located mMIMO. The use of CF mMIMO also largely removes the need for special consideration of the BD layer in the symbiotic system, which is not the case with co-located mMIMO.

Separation of a two binary-azeotrope acetonitrile-cyclohexane-toluene ternary mixture via continuous triple column extractive distillation with heat integration: design, simulation, and multi-objective genetic-algorithm (MOGA) optimization

ABSTRACT Using a sustainable method for separating azeotropic mixtures, such as extractive distillation, is crucial for environmental and resource sustainability. Cyclohexane, acetonitrile, and toluene are essential solvents in different chemical processes. This ternary mixture has two binary azeotropes between cyclohexane-acetonitrile and acetonitrile-toluene at atmospheric pressures. Using residue curve maps and a uni-volatility line, n-butylbenzene was selected as a viable entrainer for extractive distillation, among other possibilities. Unlike conventional designs, the recycled entrainer was only sent to the first column in this simulation. The wasted energy from the recycled entrainer was used to supply reboilers duty through integration. A 3-D material balance was performed to understand the separation procedures better. High-purity acetonitrile, cyclohexane, and toluene will also be obtained from the first, second, and third columns. Finally, a multi-objective genetic algorithm with 14 key decision variables was utilized to reduce total annual cost (TAC) and CO2 emissions and improve thermodynamic efficiency as objective functions from economic, environmental, and energy efficiency perspectives. Optimized results reveal that a heat-integrated design reduces almost 25% TAC and 46% CO2 emissions compared to conventional extractive distillation and does not significantly affect thermodynamic efficiency. This research could be valuable for separating azeotrope systems from other ternary mixtures.