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The paper describes a new method for determining the energy efficiency of the life cycles of wind farms by the aggregated data of energy costs. The rationale for the use of aggregated data to determine energy costs during the life cycle of the wind farms is given. The classification of wind turbines and wind farms elements by the parameters and technical characteristics of the elements with subsequent division into groups for which aggregated data of energy costs are determined is given. Within the framework of the method have been developed an algorithm for determining energy costs on the production of elements of wind turbines and wind farms and formulas for their calculation during the life cycle of wind farms. In order to test the method, energy cost was calculated during the life cycle for two wind farms with wind turbines that differ parameters and technical characteristics of the elements and their energy efficiency was determined. It has been shown that the use of a hydrogen storage unit as part of a wind turbine makes it possible to efficiently use energy during down periods and increase the efficiency of the installation by 25–30%. It is noteworthy that a wind-hydrogen farm allows not only to accumulate excess energy during lean periods, but also to save the resource of wind turbines. When the energy reserve in the hydrogen battery reaches close to full, part of the wind turbines of the wind-hydrogen farm can be automatically temporarily stopped in a given order. This technology can provide an extension of the warranty service life for each wind turbine. [ABSTRACT FROM AUTHOR]

The measures needed to limit global warming pose a particular challenge to current fossil fuel exporters, who must not only decarbonise their local energy systems, but also compensate for the expected decline in fossil fuel revenues. One possibility is seen in the export of green hydrogen. Using Algeria as a case study, this paper analyses how different levels of ambition in hydrogen exports, energy efficiency and fuel switching affect the cost-optimal expansion of the power sector for a given overall emissions reduction path. Despite falling costs for photovoltaics and wind turbines, the results indicate that in countries with very low natural gas prices, such as Algeria, a fully renewable electricity system by 2050 is unlikely without appropriate policy measures. The expansion of renewable energy should therefore start early, given the high annual growth rates required, which will be reinforced by additional green hydrogen exports. In parallel, energy efficiency is a key factor as it directly mitigates CO2 emissions from fossil fuels and reduces domestic electricity demand, which could instead be used for hydrogen production. Integrating electrolysers into the power system could potentially help to reduce specific costs through load shifting. Overall, it seems advisable to analyse hydrogen exports together with local decarbonisation in order to better understand their interactions and to reduce emissions as efficiently as possible. These results and the methodology could be transferred to other countries that want to become green hydrogen exporters in the future and are therefore a useful addition for researchers and policy makers. • The required strong capacity expansion for PV and wind is challenging, but feasible. • "Energy efficiency first" benefits both the local energy transition and H2 exports. • Fully renewable power systems require a suitable political framework. • Higher hydrogen exports might help to reduce the specific power system cost. • Fossil capacity expansion must be stopped to avoid lock-ins and higher future costs. [ABSTRACT FROM AUTHOR]

Separate sensible and latent cooling (SSLC) is a promising technology for enhancing the energy efficiency of space cooling systems. In this paper, we propose an SSLC configuration consisting of an indirect evaporative cooling (IEC) device and vapor compression cycle (VCC) for handling space sensible load, and a desiccant wheel for handling space latent load. The performance of the proposed configuration is investigated using physics-based or empirical models for each component. A year-round simulation study of the proposed SSLC system is performed for 12 different cities with diverse climatic conditions. This study considers electrical, thermal, or solar energy for desiccant wheel regeneration. Parameters governing the system performance such as the air flowrate ratio in the IEC and the DW, DW regeneration air temperature, and supply temperature are studied. The proposed SSLC configuration is superior to the conventional system in all cities. The enhancement of seasonal coefficient of performance (sCOP) ranges between 50 and 261 %, 67 and 387 %, and 60 and 2072 % with yearly electrical energy savings of 33 and 72 %, 40 and 79 %, and 38 and 95 % for electrical, thermal, and solar energy for regeneration of DW, respectively. [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]

• 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]

To identify the influence of digital transformation on energy consumption, this paper introduces digitalization and energy elements into the multi-sector energy efficiency analysis model. Furthermore, this paper empirically tests the influence of digital transformation on energy efficiency from the micro level. The results show that the digital transformation indeed improves the enterprises energy efficiency, in which enterprises with higher energy efficiency are more affected. The improvement effect of digital transformation on enterprise energy efficiency continues to increase over time. In comparison, digital transformation shows more effective improvement effect on energy efficiency in enterprises that substantive transformation priority, with same group and maturity stage. Mechanism analysis shows that digital transformation can improve the energy efficiency of enterprises by reducing costs, increasing income, improving production efficiency and promoting technological innovation. In addition, the digital inclusive finance, government subsidies, intellectual property protection and service industry opening show positive regulatory effects. This paper proposes that, with the goal of peak carbon dioxide emissions and carbon neutrality, enterprises should actively increase digital investment and strengthen digital management of energy utilization. [Display omitted] • Digital transformation indeed improves the enterprises energy efficiency. • The promotion effect of digital transformation increases over time. • Digital transformation drives efficiency improvement and technological innovation. • Digital transformation contributes to cost reduction and benefit increase. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative decision support system for improving ship energy efficiency. It combines an engine optimization model and an artificial neural network (ANN). Real-time data regarding the ship and engine performance is obtained along a specific ship navigation, and an engine optimization model is built using Ricardo Wave software. This model is validated with high accuracy. Ship-specific parameters are derived, and fuel consumption is estimated using ANN models with different structures. The study identifies the most suitable ANN model with 1 hidden layer and 5 neurons based on error metric evaluation where the 0.99697 R2, 0.00035 RMSE, and 0.06470 MAPE scores are calculated. This approach offers a cost-effective solution for shipping companies to monitor critical engine parameters in real-time without investing in sensors or data collection systems. Thus, it contributes to dealing with the problem of the scarcity of analyzable data in the maritime literature, which is one of the significant issues in the papers related to energy efficiency, machine learning, and deep learning. It is an innovative approach since the parameters that are related to real-time operations rather than considering only instruction book information are aggregated, and the produced data is analyzed by an intelligent tool. • A system is proposed to control ship energy efficiency level by combining an optimization model and a neural network • A simulation model is created in the Ricardo Wave tool and the engine model is validated by actual data. • The ship fuel consumption is estimated by an artificial neural network based on the derived input parameters. • The prediction process is evaluated by error metrics to determine its success. [ABSTRACT FROM AUTHOR]

In recent years, the severe environmental degradation and high levels of fossil fuel consumption linked to conventional ship energy systems have drawn attention to the advancement of alternative ship energy systems. Consequently, ship energy systems based on the use of an electrical microgrid are coming to the fore as an increasingly popular alternative solution. However, managing the energy flows within a shipboard microgrid can be highly challenging due to the multiple energy sources (including renewable energy sources) and types of loads involved. Additionally, the integration of an energy storage system has been identified as an effective solution for improving the reliability of shipboard power systems, pointing out the important role of energy storage systems in maritime microgrids and their potential to enhance the energy management process. As such, effective energy management strategies are necessary to optimize performance and ensure that the vessel's energy demands are met while minimizing fuel consumption and reducing cost and environmental impacts. This paper presents a comprehensive review of such strategies and methods recently presented in the literature associated with energy management in shipboard microgrids integrating energy storage systems and examine the different techniques that can be utilized to achieve optimal system performance. Moreover, the paper also sheds light on the future challenges and perspectives imposed by the modern shipboard microgrids operation on the energy/power management of these systems. The aim of this paper is to provide a helpful guideline for researchers and engineers conducting research in the field of electrically powered ships. [Display omitted] • A comprehensive review of EMS for electrical and hybrid ship is presented. • A comprehensive review of ESS which can be used in such ships is presented. • Technologies of ESS and their suitability to ships are discussed and commented. • Future challenges and perspectives imposed by modern SMG operation are presented. [ABSTRACT FROM AUTHOR]

The regenerator plays a crucial role in determining the energy efficiency of green liquid desiccant air-conditioning systems. This paper presents a novel air gap membrane distillation regenerator featuring heat recovery and portable water production. Based on a validated numerical model, performance evaluation of the regenerator combined with an external heat exchanger is conducted in terms of regeneration capacity (RC) and energy consumption (Q in). The comparison of flow patterns demonstrates that the counter-flow has a slightly higher RC , while the parallel-flow has a significantly lower Q in and is therefore preferable from the perspective of COP. The effects of key parameters including feed and coolant desiccant inlet temperatures (T f,in & T c,in), mass flow rate (m dil), membrane length (L), air gap thickness (δ ag), desiccant concentration (X dil) and solution heat exchanger effectiveness (ε she) on the performance are investigated. The results show that T f,in is the dominant factor on performance compared to T c,in and m dil , and increasing L leads to a marked growth in both RC and COP regardless of the raised Q in. Additionally, it is found that narrowing the air gap from 3 mm to 1 mm can improve RC and COP by 69.9 % and 50.1 % respectively. As for ε she , it has no influence on RC but remarkable impacts on Q in and COP. Moreover, the heat recovery by the coolant channel is proved to save nearly 8 % of energy input under the involved conditions. Finally, the NSGA-Ⅱ based multi-objective optimization is performed to obtain the Pareto front for maximizing RC and minimizing Q in. And the optimal solution through TOPSIS decision-making offers a RC = 975.8 g/h and a Q in = 1938 W. The findings provide a basis for design and application of the novel regenerator. • A novel air gap membrane distillation liquid desiccant regenerator is investigated. • Parallel-flow pattern is superior to counter-flow pattern in terms of energy efficiency. • Heat recovery by the regenerator can achieve about 8 % energy savings. • Effects of various design and operation parameters on the performance are explored. • Trade-off between regeneration capacity and energy consumption is realized by NSGA-Ⅱ. [ABSTRACT FROM AUTHOR]

Energy efficiency is a complicated process in designing Wireless Sensor Networks (WSNs). Effective routing is a precise solution for the energy efficiency constraint in WSN owing to the higher sharing of energy consumption during communication. Thus, routing is an alternative way out to this issue along with hierarchy-based clustering techniques. The clustering in WSN is carried out by picking the Cluster Head (CH), which is assumed as the essential or leader node. They perform more tasks, and thus, more energy is consumed. The clustering classifies the nodes into groups to avoid the huge communication range that is deputized to the CH. Hence, this paper establishes a routing algorithm for saving energy using a new optimization strategy via solving the multi-function formulation of the developed protocol in WSN. Here, the cluster head selection is performed with the Adaptive Remora Optimization Algorithm (AROA) to derive the multi-function derivation. The multi-function formulation undergoes with known factors such as energy consumption, distance, throughput, Packet Delivery Ratio (PDR), and path loss. The experimental result indicates an enhanced network lifetime and saving the energy of the developed heuristic-based routing protocol in WSN. [ABSTRACT FROM AUTHOR]

• TIP-EMS enhances EV energy efficiency by integrated prediction and energy management. • Significant driving economy boost; 1.6%-4.2% better than state-of-the-art PEMS. • TIP-EMS shows robust performance with varying prediction weight adjustments. To enhance the energy efficiency of electrified vehicles (EVs), developing effective energy management strategies (EMS) for hybrid storage systems is essential. Predictive EMS (PEMS) that foresee future vehicle speeds have demonstrated substantial potential in boosting EMS performance. However, traditional PEMS models, employing a sequential approach of speed prediction followed by energy allocation, are hampered by cumulative errors. These errors from the initial speed predss this issue, this paper introduces a novel solution: the trainable integrated preiction negatively impact the efficiency of subsequent energy management. To addrediction and energy management strategy (TIP-EMS). Contrasting with conventional sequential PEMS, TIP-EMS features a dual-branch, integrated neural network, which is fully trainable. This network processes driving status inputs via attention layers, with one branch dedicated to energy management objectives using a reinforcement learning (RL) algorithm, and the other to vehicle speed prediction. Both branches are trained simultaneously, but post-training, only the RL branch is activated for energy management. Implemented with a soft actor-critic RL algorithm, TIP-EMS is applied to a fuel cell EV for optimized energy management. The validation involved training TIP-EMS using 27 driving profiles, which developed its prediction and energy management capabilities, followed by tests in untrained scenarios. The results show that TIP-EMS surpasses conventional sequential PEMS by up to 4.2% in scenarios where prediction accuracies are comparable, highlighting the efficacy of the trainable integrated mechanism. In addition, TIP-EMS exhibits superior energy conservation compared to non-predictive RL strategies. Lastly, TIP-EMS exhibits robustness to adjustments in the weight given to the prediction objective, further confirming its practical applicability. [ABSTRACT FROM AUTHOR]

This paper reviews the recent evolution of unmanned aerial vehicles (UAVs) through the lens of thermodynamic design. Emphasis is placed on using constructal theory in order to understand the relationship between different degrees of freedom within these complex dynamic systems. Size scale, the way in which UAVs are categorized based on weight and dimensions and one of the most significant factors in the design of any UAV, is analyzed in terms of its relationship to energy consumption. Specifically, constructal theory is used to predict the minimum size at which any UAV will need to be tethered in order to support its energy requirements. [ABSTRACT FROM AUTHOR]

Most hydraulic drive systems for robots are configured with one single pump and multiple cylinders, which suffers from low energy efficiency in the case of driving the variable loads. To solve the problem, this paper presents a multi-chamber hydraulic cylinder based on the bionic muscle drive mechanism. Firstly, the mechanical structure is designed, the mathematical models are derived, the mechanism of high energy efficiency is analyzed. Then, the simulation of load matching control is carried out, which shows the high energy efficiency improvement and the good position tracking. Finally, the multi-chamber hydraulic cylinder prototype is developed for experimental study, and output forces, output displacement, energy consumption, and friction characteristics are researched. The theoretical analysis and experimental research show that the bionic multi-chamber hydraulic cylinder can realize the power matching between the single power source and the variable loads in the hydraulic system, which provide a novel idea for the energy efficient hydraulic equipment. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze through simulation how the energy efficiency of a single electrolysis stack at various loads is affected by shunt currents and to determine the energy-optimal load distribution between lines in a multiline electrolysis system under various magnitudes of shunt current losses. A dynamic energy and mass balance model of an industrial 3 MW , 16 bar alkaline water electrolyzer (AWE) process was developed using MATLAB. The optimization goal is to determine the power supply for each AWE line so that it can meet any hydrogen demand while minimizing the global specific energy consumption (SEC). The Particle Swarm Optimization (PSO) algorithm is used to minimize the objective function. According to the results of the single stack investigation, shunt current reduction could significantly improve the energy efficiency of partial-load operation. In addition, the optimization study revealed that whenever two or more lines are required to run in order to satisfy the hydrogen demand, the global SEC is minimized when the lines operate at equal loads. [ABSTRACT FROM AUTHOR]

Energy wastage and service level access are challenges of cloud networks, while efficient migration of virtual machines is a solution for them. Of course, uncontrolled migration increases overhead in cloud comprising: violation in service and high energy consumption. Performance requirements is very important in cloud, generally, it in the form of service level agreements are formalized. The main goal of migration is energy and performance trade-off. Detecting overloaded and under-loaded physical machine as sub-problem of migration, which effects the performance and energy. In this paper, with definition a system modelling, in first for detect overloaded and under-loaded physical machines a predict detection method is proposed. The forecast of the future utilization of the processor by using predict physical machines utilization method is provided. Predict physical machine's utilization module in predict detection method has been called. Unlike the previous physical machine detection methods, the current load of physical machines along with the future load of them is considered, and will lead to more exact results. Then for selection of virtual machines on overloaded physical machines a fuzzy selection method is proposed. Unlike the previous virtual machine-selection methods, all affective variables are considered and will lead to better results. In overall, the predict detection-fuzzy selection algorithm as intelligent approach has proposed and simulated with PlanetLab workload, CloudSim toolkit and Matlab. Simulation results demonstrate that significantly outperforms benchmark algorithms in terms of the energy consumption, migration count, service level agreement violation, energy-service level agreement violation, and energy-service level agreement violation-migration. [ABSTRACT FROM AUTHOR]

Lower limb exoskeletons have garnered significant attention for their effectiveness in gait training for paraplegic patients. For patients with insufficient trunk or upper limb strength to maintain balance, employing an unpowered robotic walker with an exoskeleton for gait training is an effective approach. The energy efficiency of the actuation system is a pivotal consideration in the design of the exoskeleton–walker system due to its significant influence on the system's durability and service efficiency. The main contribution of this paper is the development of a Parallel Compliant Leg (PCL) for the exoskeleton–walker system. The PCL consists of both powered legs of the exoskeleton and a passive flexible mechanism within the walker. This integration allows for the storage and release of energy during cyclic walking, resulting in reduced system energy consumption. To enhance energy efficiency, the support force optimization of the flexible mechanism is established. Based on this optimization, a design scheme and parameter optimization for the flexible mechanism are proposed. The effectiveness of the proposed flexible mechanism is verified through simulations on a robot simulation platform. Experimental results demonstrate a remarkable 67.6% reduction in system energy consumption achieved by the optimized mechanism. [ABSTRACT FROM AUTHOR]

Investing in energy efficiency measures is a major challenge for SMEs, both for environmental and economic reasons. However, certain barriers often make it difficult to invest in such measures. Although public financial support helps to overcome economic barriers, public bodies face the challenge of identifying which SMEs display the greatest potential to invest in energy efficiency measures. By applying a random forest technique and by using sampling balancing techniques, this paper identifies the profile of industrial SMEs that might be potential beneficiaries of public aid, thereby helping public institutions to target their calls and direct their efforts towards this group of SMEs. Specifically, liquidity and indebtedness are found to be the most useful predictors for SMEs in the industrial sector. The results are robust and reveal that applying a random forest approach for unbalanced samples offers greater predictive capacity and statistical power than applying traditional estimation techniques. By identifying potentially benefiting firms, this work helps to boost the effectiveness of public subsidies and to improve the channeling of public funds, which ultimately favors investment in energy efficiency. • Public subsidies favor energy efficiency measures by reducing the up-front cost and making the investment more profitable. • Subsidy effectiveness depends on the capacity to identify which SMEs are potential beneficiaries of energy subsidies. • We evidence that applying a random forest approach for unbalanced samples offers greater predictive capacity and statistical power than traditional techniques. • The most useful predictors for SMEs in the industrial sector are related to liquidity and indebtedness. [ABSTRACT FROM AUTHOR]

As the path of industrial eco-efficiency (IEE) needs to be re-examined from a multi-dimensional perspective, this research opens the internal "black box" of China's industrial eco-economic system driven by sustainable development goals (SDGs) and decomposes IEE into industrial production and sustainable development stages. It further divides the industrial production stage into two parallel subsystems of water use efficiency (WUE) and energy efficiency (EE) and derives SDG6 efficiency (SDG 6 E) and SDG7 efficiency (SDG 7 E) in the sustainable development stage respectively. The paper proposes a meta two-stage parallel entropy dynamic DDF-DEA model to re-measure IEE of 30 provinces in China from 2015 to 2021, discusses the relationship between overall efficiency and stage efficiency, and by using the Tobit model explores various types of influencing factors by subregion. The results show that the modified DDF-DEA model can explore China's IEE more accurately under SDGs. China's IEE is more stable from 2015 to 2021, with the efficiency value always fluctuating between 0.59 and 0.64, the overall level is low, and there is more room for improvement. There are significant inter-provincial differences in IEE and efficiency inertia. In more than 75% of the provinces SDG 7 E constrains IEE improvement, while the dynamic evolution of IEE and its subsystem efficiency varies across regions. Environmental regulation is a common factor affecting IEE across the country and in the east, central, and west regions, whereas the level of economic development, openness to the outside world, and urbanization rate are differential factors affecting IEE across the country and in the three major regions. This study offers new perspectives for exploring the path of IEE enhancement and providing empirical references for the collaborative construction of industrial ecological civilization. [Display omitted] [ABSTRACT FROM AUTHOR]

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies. • The internal mechanism of rebound effect is expounded from the view of producers and consumers. • The average energy efficiency of China's agricultural energy consumption was 68.9 % during 1999–2020. • The determinants of the agricultural energy rebound effect were further discussed by considering the spatial spillover effect. [ABSTRACT FROM AUTHOR]

The extensive utilization of wireless services, coupled with the exponential surge in data traffic, has triggered substantial energy consumption. Thereby, growing attentions have been paid to energy-efficient heterogeneous cellular networks (HCNs). In this paper, we concentrate on the joint resource allocation issue under the framework of the non-orthogonal multiple access (NOMA) assisted HCNs with wireless backhauls. To furthermore improve the total system energy efficiency (EE) while ensuring the quality of service (QoS), we formulate the optimization problem as a hybrid joint resource allocation (HJRA) of integer programming and continuous optimization under the cross-tier interference threshold and minimum data rate constraint. The non-convex nature of the optimization problem arises from the fractional objective function and non-convex constraints, making it intractable to efficiently get an exact solution. In this regard, a quantum-inspired political optimizer (QPO) algorithm is devised to find the optimal solution for the HJRA issue, which realizes synchronous allocation of backhaul bandwidth, sub-channels, and power. Simulation results confirm the superiority of the QPO regarding the total system EE over other strategies. [ABSTRACT FROM AUTHOR]

This article analyzes energy poverty in Latin America and the Caribbean and the importance of energy efficiency to address this issue. The paper also touches upon energy subsidies in Mexico and their negative environmental and social consequences. Then, the article studies the potentially detrimental billing practices of Mexico's state electricity company, which are provoked by the enterprise's growing past-due portfolio and losses, and the possible infringement of electricity consumers' rights. The authors propose three courses of action for consumers to protest the company's possibly perjudicial billing. Finally, the authors suggest that a distributed electricity system in Mexico could combat energy poverty and strengthen electricity users' rights. [ABSTRACT FROM AUTHOR]

Intermittent embedded devices and systems are widely used in various scenarios, but they often experience power failures due to unstable power supplies. Non-volatile memory (NVM) is gaining popularity in embedded systems due to its byte-addressability, low access latency, and high density. As a result, backups can be stored in NVM, and global data are directly manipulated in NVM in this architecture. However, NVM has limited write endurance and modifications to global data frequently occur which results in a significant number of writes. As a result, the extensive NVM accesses may lead to poor performance for intermittent programs. This paper presents an energy-efficient approach, called shadow-stack to minimize NVM write overhead while ensuring consistency. Furthermore, we propose a series of principles to assist programmers in rewriting the programs. And we prove the correctness of these principles using formal methods. Experimental results demonstrate that shadow-stack achieves an approximately 95.1%, 81.3%, and 76.6% improvement in NVM writes overhead compared with log-based, Coach, and Clank, respectively on average. Simultaneously, shadow-stack also significantly reduces energy and time consumption compared with log-based approach by up to 19.4 × and 6.87 × , Coach by up to 4.2 × and 2.46 × , and Clank by up to 3.4 × and 2.26 × respectively. [ABSTRACT FROM AUTHOR]

—This paper proposes two real-time energy-oriented driving strategies to minimize the energy consumption for electric vehicles on highways with varying slopes. First, a novel strategy, called normalized-energy consumption minimization strategy (NCMS), adopts a designed kinetic energy conversion factor to convert the vehicle kinetic energy change into the equivalent battery energy consumption. By minimizing the total normalized energy consumption, the energy-orientated vehicle control sequence is calculated. In addition, a logic car-following algorithm is developed to enhance NCMS for avoiding collisions with the potential preceding vehicle on the journey. Second, an improved model predictive control (MPC) is developed with a hierarchical framework, which achieves a balance between optimization and computational efficiency. In the upper level, a global, coarse-grained, iterative dynamic programming is employed to penalize the MPC terminal state, while the lower level performs online rolling optimization of the vehicle within a moderate time step. Thirdly, the performance of the proposed driving strategies is verified through a traffic simulation to evaluate the energy efficiency improvement and processor computation time compared to dynamic programming and constant speed strategy. Finally, a vehicle-in-the-loop test is carried out to validate the feasibility of the proposed two novel driving strategies. • A normalized energy consumption model is presented, combining two energy usage. • A novel eco-driving strategy is developed based on the proposed energy consumption. • The algorithm suits both free traffic and car-following scenarios with safety. • The characteristics of the four eco-driving strategies are compared. • The proposed strategy is verified by both simulation and vehicle-in-the-loop tests. [ABSTRACT FROM AUTHOR]

Wastewater treatment plants (WWTPs) play a pivotal role in natural water recycling and safeguarding the water security of approximately 42% of the world's population, yet they confront challenges posed by escalating energy consumption and regional energy constraints. In this study, we developed an evaluation framework that integrated regional energy scarcity with the operation conditions of WWTPs to quantify their energy efficiencies by applying multiregional input–output (MRIO) analysis and data envelopment analysis (DEA). A case study using this framework was conducted on 3776 WWTPs in 30 provinces in China. The results showed that the average scarcity-based energy efficiency level of WWTPs in China was low, of which those in northern provinces were higher compared to southeastern provinces. Furthermore, only 24 WWTPs in China attained the highest efficiency levels, while the rest had different degrees of input redundancy, indicating an energy-saving potential of 9.05 × 109 kWh. This paper enables the development of optimal efficiency strategies for WWTPs in different provinces considering the potential energy scarcity risks caused by trading activities. • The DEA and MRIO analyses were combined for 3776 WWTPs in China. • Efficiency evaluation index was modified considering energy scarcity levels. • Scarcity-based energy efficiency assessment framework for WWTPs was developed. [ABSTRACT FROM AUTHOR]

Approximate computing is one of the promising techniques in error-resilient applications to overcome high-density integration challenges, such as energy consumption and performance. Multipliers constitute a significant portion of computer arithmetic units, leading to considerable energy and time consumption. In this paper, we propose low-power and compact approximate compressors for composing approximate Dadda multiplier structures, including compressors, half adders, and full adders, which utilize three-phase partial product compression: truncated, approximation, and exact columns. In approximate columns, we consider approximate compressors derived from the truth table of the exact 4:2 compressor and simplified K-map entries based on the probability of each combination of inputs. An error-correcting module (ECM) is designed to distinguish specific cases and reduce the error metrics. All circuits were simulated using ModelSim and then synthesized using Design Compiler with the 15 nm FinFET technology. When compared to state-of-the-art works, our multipliers exhibit approximately 30%, 43%, and 10% reductions in power, area, and delay, respectively. To evaluate their functionality, we conducted image multiplication and implemented a simple multi-layer perceptron (MLP) neural network using the modified National Institute of Standards and Technology (MNIST) dataset in MATLAB with 0.998 mean structural similarity index metric (MSSIM), 51 dB peak-signal noise ratio (PSNR), and 95% classification accuracy. • Introducing novel ultra-compact approximate compressor structures to reduce design metrics. • Proposing an error-correcting module (ECM) for compensating errors of approximation. • Proposing truncated 8 × 8 Dadda multipliers using the proposed approximate compressors and ECM. • Evaluating the accuracy of approximate multipliers in error-tolerant applications. [ABSTRACT FROM AUTHOR]

This paper focuses on the comparative study of vertical and horizontal vacuum membrane distillation (VMD) modules coupled with mechanical vapor recompression (MVR) system to obtain the optimal system layout structure and further improve operation stability and energy efficiency in the wastewater treatment. Firstly, freshwater accumulation characteristic in the vertical VMD module was explored under different working conditions. Then, comparative experiments of vertical and horizontal VMD-MVR systems were conducted. Finally, comprehensive performance of horizontal VMD-MVR system were evaluated. The obtained results showed that freshwater production in the distilling tank and freshwater accumulation in the VMD module were affected by operation time, feed temperature, feed flow rate, feed concentration and vacuum side pressure. Furthermore, the horizontal VMD-MVR system was proved to be a better choice due to lower freshwater accumulation in the VMD module and energy consumption in comparison to the vertical VMD-MVR system. Finally, long term operation experiment of 240 h indicated evaporation rate dropped to 55 kg/h as operation time reached to 180 h owing to membrane fouling. After membrane cleaning, evaporation rate recovered from 55 to 62 kg/h with a higher recovery efficiency of 95.1 %. Compared to conventional wastewater treatment systems, the horizontal VMD-MVR system exhibited excellent comprehensive performance. [Display omitted] • Performance comparison of vertical and horizontal VMD-MVR were conducted. • Freshwater accumulation in the VMD module affected the evaporation rate. • Vertical VMD-MVR system had higher energy consumption than horizontal system. • Separation efficiency of horizontal VMD-MVR system was 99.9 %. • Evaporation rate recovered from 55 kg/h to 62 kg/h after membrane cleaning. [ABSTRACT FROM AUTHOR]

[Display omitted] • Feasibility of using organic wastewater as renewable energy source is verified. • ＞99% COD, TOC removal rate in the experimental platform. • Up to 78.75% of the energy recovery efficiency of the SCWO system. The degradation of high concentration organic wastewater and the recovery of energy using supercritical water oxidation (SCWO) technology have the potential to become viable in the future. High concentration organic wastewater contains a significant amount of energy. This paper focuses on utilizing high concentrated wastewater as a renewable energy source, from an energy system perspective, an experimental rig was designed to determine the optimal working conditions. The experiments were conducted with an oxidation coefficient of 1.1, a flow rate of high concentration organic wastewater of 9 ml/min, a heating temperature of 400 °C, and a reaction pressure of 25 MPa. Under these conditions, the COD and TOC removal rates of the high concentration organic wastewater were found to be 99.383 % and 99.876 % respectively. Additionally, the phenomenon of "Abnormalities in pressure sensitivity" observed during high concentration organic wastewater the experiment was further explained through additional experiments. Finally, by comparing the experimental energy recovery with the simulation results, an energy recovery efficiency of 78.95 % was achieved. The feasibility of the simulated energy recovery in practice was verified, confirming the potential to convert the previous energy-consuming wastewater treatment process into a productive one. This study provides a theoretical and experimental foundation for further related research. [ABSTRACT FROM AUTHOR]