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Using robots to detect Marine structures is very important for maintaining the safety of Marine structures. This paper presents an underwater inspection robot specifically engineered for the assessment of underwater structures. The integration of reliable adhesion technology is identified as a critical factor in the development of such robots. The vortex suction cup, employed by the robot as its primary adhesion mechanism, outperforms traditional adhesion methods by enabling non-contact attachment while consuming less power. As the vortex suction cup is the core component of the underwater inspection robot , this study comprehensively investigates how variations in the vortex suction cup's structural and operational parameters influence its adhesion performance, measured from an energy efficiency ratio perspective. Initially, we delineate the vortex suction cup's design and succinctly explicate the mechanism underpinning the generation of negative pressure. Subsequently, we establish an evaluative parameter, the energy efficiency ratio (η = F / P), that is, the adsorption force obtained per watt of power consumption of the suction cup, serving as a metric for the adhesion performance. By simulating the structural and operational parameters of the suction cup, we extract the corresponding adhesion force, torque, and energy efficiency ratio. Lastly, we construct an experimental apparatus to measure the suction cup's adhesion force and output torque, validating the veracity of the simulated outcomes. Our simulation and experimental findings indicate that increasing the height of the suction cup housing enhances the adsorption force, however, this simultaneously diminishes its energy efficiency ratio performance. Likewise, an increase in the chamber inner radius amplifies the adhesion force, and the energy efficiency ratio commensurately increases. Augmenting the radius of the negative pressure effect board improves the adhesion force, decreases the required torque, and consequently amplifies the energy efficiency ratio. The suction cup's adhesion force and required torque display a direct relationship with its speed, but the energy efficiency ratio is minimally affected by speed. When the distance is close (h ¡ 4 mm), changes in the adhesion gap profoundly impact the suction cup's torque and energy efficiency ratio. However, when the adhesion gap ranges between 5–15 mm, the energy efficiency ratio exhibits a gradual decline. • This paper presents an underwater inspection robot with two vortex suction cup to adsorb on the surface of the underwater structure. • The effects of the structure and operating parameters of the vortex suction cup on their adsorption performance are explored. • A CFD method and a test platform are proposed to verify the adsorption performance of the vortex suction cup. [ABSTRACT FROM AUTHOR]

With the increasing complexity of the power grid, the precision of the thermal power units' execution of automatic generation control (AGC) commands is gradually increasing the impact on the online regulation of the power grid. The deviation between the actual output of thermal power units and the AGC command of the grid will not only affect the consumption of new energy output, but also endanger the safe operation of the grid. This paper introduces "deep learning" technology to solve the problem. Firstly, an AGC command execution effect identification and confidence evaluation algorithm (ACEEI-CEA) is proposed. The algorithm builds a neural network model to accurately predict the unit output and the confidence evaluation of the prediction results. Next, a high-dimensional input preprocessing strategy based on variational autoencoder (VAE) is proposed to reduce the dimensionality of the model input attributes, improving the convergence and accuracy of the model. Finally, an AGC optimal command fast inversion solution method (AOCFISM) is designed. This method transforms the unit output deviation problem into an objective optimisation problem. And improve the efficiency of solving the optimal AGC command value by constraining the unit command value. The calculation results show that the error of the prediction results of the model proposed in this paper is 5% lower than that of the traditional neural network. The difference between the output value of the optimal AGC command and the expected output value obtained is less than 0.5 MV, which can support AGC online decision-making.© 2017 Elsevier Inc. All rights reserved. • An AGC command execution effect identification and confidence evaluation algorithm (ACEEI-CEA) is proposed. • Results show the ACEEI-CEA performs well in command prediction compared to the state-of-the-art methods. • ACEEI-CEA achieves confidence assessment of predicted values. • The pre-processing strategy based on variational autoencoder shortens the training time of the model. • The AGC optimal command fast inversion solution method (AOCFISM) can obtain the AGC optimal command value. [ABSTRACT FROM AUTHOR]

This paper reports new insights into how the selection of route based characteristic parameters can influence the predicted energy consumption for next generation battery electric buses. 24 characteristic parameters have been studied to understand their relative importance on vehicle energy consumption and to develop new data-driven prediction models. The parameters are grouped into two scenarios, representative of the varying levels of route information available to a typical bus operator. A combination of feature selection methods was used to determine which characteristic parameters had the greatest influence on energy consumption. Regression based prediction models were developed, and models were then validated using standard and real vehicle drive cycles. The prediction models had a mean absolute percentage difference of 2.10–10.67%. This paper presents a novel methodology to estimate energy consumption of operating zero emission vehicles, which will support public transport operators, policy makers and energy suppliers in the decarbonisation of public transport. [ABSTRACT FROM AUTHOR]

Digital infrastructure serves as a crucial foundation for development in the era of the digital economy. In light of this, this paper takes digital infrastructure construction as its focal point. Utilizing Python technology and the Meta-frontier non-radial directional distance function to calculate the level of digital infrastructure construction and industrial energy efficiency. It then employs a dynamic panel data model to analyze the impact effects and mechanisms of digital infrastructure construction on industrial energy efficiency. Additionally, threshold models and modified gravity models are employed to explore the nonlinear effects and spatial impacts of digital infrastructure construction on industrial energy efficiency. The research findings reveal that the enhancement of digital infrastructure significantly improves industrial energy efficiency. Moreover, indicate a shift in the impact of digital infrastructure construction on industrial energy efficiency from inhibitory to promotional as the level of digital infrastructure construction increases. The mechanism of this effect suggests that digital infrastructure construction can promote the improvement of industrial energy efficiency through green technological innovation and the advancement of industrial structure. Further analysis shows that the spatial network characteristics of digital infrastructure construction notably elevate the level of industrial energy utilization efficiency. This study provides practical policy implications for sustainable development. • Digital infrastructure construction markedly enhances industrial energy efficiency. • There is a non-linear picture of the impact of digital infrastructure construction on industrial energy efficiency. • The effects of green technology innovation and advanced industrial structure are crucial channels. [ABSTRACT FROM AUTHOR]

Floating offshore wind turbines, as large equipment for deep-sea wind energy utilization, must be carefully studied for their aerodynamic performances under platform motions. In experiments, the model wind turbine designed by the traditional thrust coefficient similarity is usually insufficient for unsteady aerodynamic reproductions of the prototype wind turbine. In this paper, a dynamic aerodynamic similarity criterion based on the mapping of the optimal tip speed ratio is introduced for wind tunnel model tests, and a model wind turbine is designed using the NREL 5-MW prototype wind turbine. In this case, to avoid the over-height model tower aroused in pitch motions, a method of equivalent surge motions instead of pitch motions is proposed and validated for feasibility. Then dynamic aerodynamic similarities under different pitch amplitudes and frequencies are validated by the Unsteady Blade Element Momentum theory. Results indicate that temporal and spatial characteristics and hysteresis effects of thrust and power coefficients all maintain better similarity with those of the prototype wind turbine than those of the model wind turbine designed by the traditional criterion. This paper provides a criterion with equivalent pitch motions for unsteady aerodynamic studies in wind tunnel model tests, especially the high-fidelity Hardware/Software-In-the-Loop test. • A new similarity criterion is proposed for FOWT wind tunnel model tests. • The feasibility of equivalent surge motions instead of pitch motions is verified. • The problem of over-height model tower is avoided by equivalent pitch motions. • Spatiotemporal and hysteresis characteristics of unsteady aerodynamics are analyzed. • Unsteady aerodynamic performances of the prototype can be reflected more accurately. [ABSTRACT FROM AUTHOR]

• Based on the control input cost function of the traditional partial format model-free adaptive control, an effective greenhouse temperature controller is designed by adding an index term that limits energy consumption. • The multi-parameter sensitivity analysis method based on Monte Carlo is used to analyze the sensitivity of the controller parameters to determine which parameters have a greater impact on system performance. Then, the whale optimization algorithm is used to optimize the sensitive controller parameters. This improves the efficiency of parameter tuning. • The improved partial format model-free adaptive controller achieves a balance between control accuracy and low energy consumption. Compared with the traditional partial format model-free adaptive controller, the energy consumption of the improved partial format model-free adaptive controller is reduced by 12.35 %. Temperature is critical to the growth of crops in agricultural greenhouses. Thus, designing a greenhouse temperature controller that maximizes energy savings while maintaining control accuracy is very important. This paper proposes an improved partial format model-free adaptive control method and designs a greenhouse temperature controller based on this method to balance control accuracy and energy consumption. Firstly, a limited energy consumption term is added to the control input cost function of the traditional partial format model-free adaptive control to penalize excessive control input. We derive an improved partial format model-free adaptive control input algorithm and design a greenhouse temperature controller using this algorithm. Then, the controller's sensitive parameters are selected using a Monte Carlo-based parameter sensitivity method. Finally, the whale optimization algorithm is used to optimize the sensitive parameters. The insensitive parameters are set according to experience. This paper, a theoretical study based on simulated experiments, proves the convergent tracking error of the proposed improved partial format model-free adaptive algorithm. Simulation results show that the improved controller minimizes energy consumption while ensuring control accuracy, reducing power consumption by 12.35 % compared to the traditional controller. [ABSTRACT FROM AUTHOR]

• Proposed a novel advanced solar-driven combined heat and power system. • Constructed the overall heat current model and exergy analysis expression. • Analyzed the exergy loss and efficiencies of each component and the system. • Analyzed the influences of various parameters on the system exergy efficiency. Conducting research on advanced cycle of distributed energy system and improving energy utilization efficiency is an important approach to promote the development of distributed energy systems. The paper proposed a novel solar-driven supercritical carbon dioxide-heat pump cogeneration system based on solar power tower system and performed the overall modeling of the system using the heat current method. The overall exergy loss calculation model of the system was established by applying the exergy analysis method incorporating the standard thermal resistance-based entropy generation rate expression. The calculation results present that under rated condition, irreversible loss mainly occurs in the solar energy conversion part, accounting for 73.83 %, and the system exergy efficiency is 34.69 %. Besides, the paper investigated the steady state performance of the system under different working conditions and the influence of the turbine inlet temperature and the intermediate pressure on the system performance. When the direct normal irradiance increases, the proportion of exergy loss in solar energy conversion part increases by 62.13 %, while the change of system exergy efficiency depends on the operating state of the system. The optimum intermediate pressure is 11.72 kPa, when the net power output and the exergy efficiency of the whole system reaches the maximum. Finally, the proposed system contributes to the improvement of cascade utilization of energy, and the modeling method is effective for solar-driven supercritical carbon dioxide cogeneration systems. [ABSTRACT FROM AUTHOR]

• The thermal, rheological, and optical properties of ferrofluids and how they change with magnetic fields were discussed. • The utilization of ferrofluids in solar energy systems was detailed in a state-of-the-art analysis. • The recommendations aimed to optimize the use of ferrofluids and magnetic fields in energy systems to enhance performance. Solar energy technologies play a crucial role in the transition to sustainable energy sources; however, there is an ongoing challenge in optimizing their efficiency and performance. This review paper thoroughly exposes the potential for enhancing solar systems by incorporating ferrofluids and utilizing magnetic fields. It provides a comprehensive examination of the rheological, thermal, and optical properties of ferrofluids, as well as their behavior when exposed to magnetic fields. The paper emphasizes the ability of ferrofluids to improve heat transfer efficiency, adapt to changing conditions, and enable precise control in the conversion of solar energy. Furthermore, the review addresses the obstacles and limitations associated with integrating ferrofluids into solar technologies, proposing potential solutions and outlining future research directions. [ABSTRACT FROM AUTHOR]

• Novel FADSS is fabricated for the water production from thin air. • It incorporates a small blower to facilitate airflow through the system. • Condenser is used for the condensation of desorbed vapour from silica gel. • Bed design study is performed for effective solar energy utilization. • Honeycomb bed, with an airflow rate of 30 LPM, is found as optimal. This paper presents an innovative approach addressing the problem of clean and drinking water scarcity by developing and optimizing a flow-assisted desiccant solar still (FADSS) that harnesses atmospheric moisture using solar energy. It is an extension of the conventional desiccant solar still incorporating a small blower to facilitate airflow through the system, and operates in a two-cycle process. During the night (adsorption process), ambient air is blown continuously through the bed, enabling the silica bed to adsorb moisture. During the daytime (desorption process), solar energy heats the silica bed, releasing the adsorbed water vapour to the circulating air, which carries it to the condenser. The water vapour condenses in the condenser, and the air returns to the bed. The paper focuses on optimizing the FADSS by studying the airflow rate, a critical parameter for maximum water production. It varies from 20 to 60 L per minute (LPM). Further, the paper also investigates the four different bed design configurations for maximum water production. The FADSS thermal efficiency is calculated to analyze its performance. The highest water production of 694 ml/day was achieved using a 0.25 m2 glazing area in the honeycomb bed design. This output was obtained by employing an airflow rate of 30 LPM and a 3 cm thickness of silica gel. Interestingly, The honeycomb bed effectively utilized ∼38 % of solar energy for water production in the FADSS, while about 9 % was lost due to sensible cooling of the air in the condenser. The findings suggest that the honeycomb bed, with an airflow rate of 30 LPM, represents the optimal operational parameters for this system. [ABSTRACT FROM AUTHOR]

Black liquor (BL) is a by-product in the paper and pulp industry. Although it has good potential for providing energy as an industrial waste, BL's high moisture content limits its usability. In this study, an integrated system to effectively co-produce power and ammonia (NH 3) from BL is modeled and evaluated. The modeling and integration are conducted using the principles of exergy recovery and process integration to effectively circulate the energy/heat throughout the whole system. The developed system involves BL evaporation, gasification, syngas chemical looping (SCL), and NH 3 synthesis. During SCL process, H 2 , CO 2 , and N 2 -rich gas are produced consecutively in the oxidation, reduction, and combustion reactors, respectively. The designed system can achieve the total energy efficiency of ~50%. The result also suggests that N 2 -rich gas and pure H 2 produced during SCL can be used directly for NH 3 synthesis without any additional energy penalty. The additional step for CO 2 separation can also be avoided, affording a cleaner and more efficient system that provides complete carbon capture. • An efficient energy system of a H 2 production is proposed. • The system comprises evaporation, gasification, syngas chemical looping and NH 3 synthesis. • High energy efficiency in NH 3 production can be realized. • The designed system achieved about 50% of total energy efficiency. • The system has cleaner and more efficient system with 100% carbon capture. [ABSTRACT FROM AUTHOR]

• A multi-constraint model for impulsive orbital pursuit-evasion game (OPEG) is constructed. • A learning-based algorithm (i.e. PRD-MADDPG) for impulsive OPEG is designed. • The Predict-Reward-Detect (PRD) training framework for improving MADDPG is established. • The PRD-MADDPG performs better than conventional MADDPG in impulsive OPEGs. • The winning mechanism of the game for both players under multiple factors is analyzed. This paper comprehensively investigates the problem of impulsive orbital pursuit-evasion games (OPEGs) by using an artificial intelligence-based approach. First, the mathematical model for the impulsive OPEGs in which the pursuer and evader both perform their orbital maneuvers by imposing the impulsive velocity increments is constructed. Second, the problem of impulsive OPEGs is transformed into a bilateral optimization problem with a minimum–maximum optimization index in terms of terminal time and multiple constraints such as maneuverability, total fuel consumption, and mission time, etc. To determine the optimal impulsive maneuvers for both sides, a PRD-MADDPG (Predict-Reward-Detect Multi-Agent Deep Deterministic Policy Gradient) algorithm in the frame of multi-agent reinforcement learning is designed. This novel algorithm uses the basic MADDPG to achieve the strategies training and learning, and applies the supplemental PRD to predict the change of game state during the interval between two adjacent impulsive maneuvers and incorporate these information into the algorithm training in the form of predicted reward. Finally, some pursuit-evasion missions near the Geosynchronous Earth Orbit are numerically analyzed to verify the validness and effectiveness of the algorithm. The results prove that the PRD-MADDPG algorithm is very efficient to find applicable strategies even considering rather complex constraints. It is also shown that the learning-based strategies can be effectively applied in the extended scenarios which are not seen in the training process. [ABSTRACT FROM AUTHOR]

• The TM capture is first reformulated to nonlinear quadratic optimal control. • The high-efficiency NMPC with robustness and optimality is proposed for TM capture. • The mixed state and control constraints are integrated into the robust optimal control. • The proposed method guarantees the computational efficiency. This paper presents a nonlinear high-efficiency model predictive control (NHMPC) with constraints designed for the test mass (TM) capture phase of the drag-free satellite about gravitational wave observatory. To avoid collisions between test mass and satellite cavity, TM capture is the essential technology for drag-free satellite. Test mass is located inside an electrostatic suspension and locked by a clamp mechanism initially. The test masses are released with high initial offsets and velocities when the mechanism is retracted. The purpose of this phase is to guarantee the TM to be positioned at the cage center and attitude aligned with the local cage frame. Due to the low actuation authority of electrostatic suspension along with critical initial offsets and velocities, it is a challenging task to design the attitude and translation control schemes with simultaneous consideration of system performance and energy consumption. For the problem given above, the TM capture can be reformulated into a nonlinear quadratic optimal control problem with the state and input constraints. A nonlinear model predictive control (NMPC) structure is also designed to handle the noises by forming a closed loop. This control framework can realize optimality and robustness in a compromise. To improve the speed of solving high-dimensional nonlinear optimal control online for MPC, the indirect Chebyshev pseudospectral method with constraints is employed. The convergence and stability of the control loop are analyzed. Simulation examples show that the feasibility and performance of the designed control loop are verified compared with the existing methods and computation times in the millisecond range can be achieved. [ABSTRACT FROM AUTHOR]

Developing new technologies is a key to achieve renewable energy utilization. The near-field thermo-photovoltaics (NFTPV), an emerging power generation device, is investigated from the energy perspective in this paper. A novel oxy-enrich NFTPV system is proposed, and a thermo-physical model is established for sustainable fuel gas based on energy balance. The effects of parameters on system performance are numerically explored, including the furnace size, oxygen ratio, voltage and vacuum gap, etc. Moreover, special attention is paid to the effects of oxygen ratio on system performance under 2 atm of O 2 /N 2 and O 2 /CO 2. Besides, exergy analysis is conducted. The results show that it is more appropriate to control the power density of furnace at 50 kW/m2 in system design. The efficiency of NFTPV system is about twice greater than that of far-field TPV system. The power density of NFTPV system increases by more than 2.5 times when the oxygen ratio increases; the TPV volume can increase by 2–3 times and the efficiency is also improved. The results indicate that oxy-enrich combustion with higher oxygen ratio matches a larger NFTPV system, which reduces the manufacturing difficulty and is significant in engineering. This study provides new ideas and references for NFTPV practical application. [ABSTRACT FROM AUTHOR]

The increasing penetration of photovoltaic technology in the electricity market requires the development of a methodology that facilitates the optimisation of photovoltaic plants with single-axis trackers. This paper presents an optimisation methodology that takes into account the most important design variables of single-axis photovoltaic plants, including irregular land shape, size and configuration of the mounting system, row spacing, and operating periods (for backtracking mode, limited range of motion, and normal tracking mode). Equations for the determination of the optimal row spacing and operating periods have been developed and is presented in detail. A packing algorithm that takes into account the irregular land shape and the possible configurations of the mounting systems is also presented. The objective function is the total area of the photovoltaic field and the optimisation is performed by a packing algorithm. As the economic aspect of energy generation also plays a key role in decision-making, the levelised cost of energy has been used to assess the economic viability of the optimal layout of the mounting systems. The results show that the proposed methodology and packing algorithm are able to optimise the photovoltaic plant with single-axis solar tracking and provide reliable results after a reasonable computation time. The methodology was demonstrated in detail for a Spanish photovoltaic plant (Granjera photovoltaic power plant), including the optimal layout of the mounting systems and the cost analysis for this layout. The optimal layout of the mounting systems could increase the amount of energy captured by 91.18% in relation to the current of Granjera photovoltaic power plant. The mounting system configuration used in the optimal layout is the one with the best levelised cost of energy efficiency, 1.09. The presented optimisation methodology can be utilised to facilitate the optimal design of commercial photovoltaic plants with single-axis trackers. Therefore, questions such as: what is the optimal distribution of mounting systems?, how much energy will this distribution produce?, and at what cost will it produce it?, can be answered by using the proposed methodology. • The optimal layout of single-axis solar trackers in large-scale PV plants. • A detailed analysis of the design of the inter-row spacing and operating periods. • The optimal layout of the mounting systems increases the amount of energy by 91%. • Also has the best levelised cost of energy efficiency, 1.09. [ABSTRACT FROM AUTHOR]

This paper presents a one-dimensional and semi-empirical model of a high-temperature PEM fuel cell (HT-PEMFC) to determine the performance characteristics through energy, exergy, and ecological analysis. The proposed model is compared with different experimental studies and supported by a few statistical approaches to prove its accuracy. As a result, the minimum and maximum R2 values are determined to be 99.67% and 99.97%, respectively. In addition, the performance of the fuel cell is investigated under varying leakage current densities and doping levels. Accordingly, increasing the leak current density decreases the power density, net output voltage, energy efficiency, and exergy efficiency by 5.77%, 5.88%, 5.44%, and 5.48%, respectively, whereas increasing the doping level boosts these parameters by 23.07%, 11.76%, 30.25%, and 32.52%, respectively. In addition, increasing the leak density decreases all ecological functions. In contrast, raising the doping level increases the ecological parameters considerably and reduces the improvement potential. • A novel one-dimensional and semi-empirical model of the HT-PEMFC was adopted. • The proposed model was compared and verified with different experimental studies. • Performance assessment was conducted via energy, exergy, and ecological analyses. • Increasing the doping level from 6.2% to 30% enhances exergy efficiency by 32.52%. • The doping level is more effective on the performance than the leak current density. [ABSTRACT FROM AUTHOR]

Due to the environmental and economic advantages of combined heat and power (CHP) units, their use in power grids has expanded. The entry of CHP into power systems increases the complexity of the economic power flow problem. This complexity is due to the introduction of multiple constraints into problem. A mere electricity supply is not optimal in today's networks, and energies such as heat, power and gas must be planned and managed simultaneously as an energy hub. Therefore, in this paper, an intelligent multi-energy microgrid (MG) consisting of power generation units, CHP units and gas units is modeled for day-ahead energy management (DAEM). The economic distribution problem focuses on the amount of power generation, heat and gas of the units in the system. In contrast, the total generation cost of the system is minimized, and all the equality and inequality constraints of the problem are observed. The proposed microgrid includes various energy-dependent equipment such as CHP units, gas boilers, electricity-to-gas units, power and heat storage units and electric heat pumps. Also, price-based load management was included to reduce costs due to the transfer of information between the consumer and the generator in the context of smartization. Since the above problem is difficult to solve due to various constraints and decision parameters, a newly developed optimization method based on water flows was proposed. The simple movement of water flows on the ground is efficient and optimal and always follows the shortest and fastest path to reach the deepest point. In the proposed algorithm, simple movements of water in routing, a change of direction and even the creation of rapids and vortices were simulated as various mathematical operators. Finally, the proposed model and method were examined in different scenarios. The numerical outcomes demonstrated that, the proposed modeling framework is superior to hub-based multi-carrier microgrid models in terms of power system security. The sensitivity of operational expenses to changes in initial values of energy storage systems (ESS) and thermal storage system (TSS) is proved that the cost of operation reduces as the baseline values of ESS and TSS are reduced to 0.2% of the maximum capacity. Because DAEM performance is less flexible when the primary values are reduced by 0.2% of the maximum value, the system running expenses increase marginally. [Display omitted] • Introducing a novel developed algorithm based on water flows. • DAEM in the microgrid in the form of an energy hub. • Application of internal grids & energy flow of energy carriers in multi-energy MGs. [ABSTRACT FROM AUTHOR]

Internet of Things and growing popularity of connected devices are increasing the demand for wearables applications, which is driving the development of ultra-low power secure systems. Thus, having a system running at low voltage with low power consumption introduces the use of ambient energy harvesting. Besides, batteries have several limitations reducing their compatibility with wearables, including periodical need for recharge, limited life-time, heavy and large form factor and non-eco-friendly life-cycle. Therefore ambient energy harvesting technology gives a promising alternative for self-powered wearables. The integration of these solutions on the same silicon support is a real technological challenge. This paper proposes a multi-harvesting fully-integrated system architecture combining AC and DC sources. Based on a MATLAB/Simulink model, the proposed system allows the calibration of an optimal solution. It is designed and simulated in 40 nm CMOS process, demonstrating the use of an AC source as secondary input to start a harvesting system with very low DC source as main source. • Ambient energy harvesting technology gives a promising alternative for self-powered wearables. • Multi-harvesting fully-integrated system architecture combining AC and DC sources. • Energy harvesting system level modeling using MATLAB/Simulink. [ABSTRACT FROM AUTHOR]

The new powder engine is an efficient power system with powder fuel as propellant. Its excellent performance is inseparable from stable and efficient powder feeding assisted by carrier gas. In this paper, we investigate the effect of carrier gas type (air, N 2 , CO 2 and He, gas viscosity: CO 2

This study performed the numerical simulation of the vortex finder (VF) diameter and depth effects on the separation performance of the hydrocyclone-type devices for multiphase fluid separation, namely the static pressure, pressure drop, split ratio, short-circuit flow, velocity field, and classification accuracy. The static pressure, pressure drop, and split ratio were found to be negatively related to the VF diameter. As the VF diameter increased from 0.26D 2 to 0.56D 2 , the maximum static pressure dropped from 94483.56 to 26067.86 Pa, and the pressure drop was reduced from 93336.50 to 26408.69 Pa. Meanwhile, the steepness index increased with the VF diameter in a particular range. The results strongly indicated that an increased VF diameter led to reduced energy consumption and improved separation accuracy of the hydrocyclone, decreasing the tangential velocity, increasing the short-circuit flow, and disrupting the symmetry of the locus of zero vertical velocity (LZVV). The effects of the VF depth on the separation performance were as follows: with increasing VF depth, short-circuit flow and split ratio decreased, the steepness index increased within a specific range, and the symmetry of the LZVV gradually improved. This implies that increased VF depths can help enhance the separation performance of the hydrocyclone but excessively large VF depths would deteriorate it. [Display omitted] • The accuracy of the mathematical model used in the paper was verified. • Effects of the vortex finder diameter on the classification performance were studied. • Effects of the vortex finder depth on the separation performance were studied. • Separation efficiency of the hydrocyclone was analyzed. [ABSTRACT FROM AUTHOR]

The increase of Renewable Energy (RE) production to fight the climate crisis is posing new technological and financial challenges, due to the availability and variability of RE Sources (RES). These challenges can be addressed by selecting the most suitable mix of RES to optimise power production, to assure grid resilience and to promote local energy use. To facilitate the selection of such combination, this paper presents an original methodology that allows to compare mixing scenarios with different RES, also in presence of batteries and backup system. It simultaneously optimises the energy surplus with respect to the eventual external electrical load and the missing energy with respect to the same electrical load. This method, which can cope with isolated or plugged-to-grid systems, is here applied to a novel case study, an oil&gas platform under decommissioning, located in the Adriatic Sea (Italy). The RE production from wind, wave and solar panels is supposed to support other activities for the platform reuse, such as aquaculture, monitoring and mineral deposition. In this case, solar energy is providing the greatest contribution to the optimal mix in terms of production, while wave energy assures the most relevant contribution in terms of continuity. [ABSTRACT FROM AUTHOR]

This paper evaluates the potential of using biodiesel from Dunaliella tertiolecta in the internal combustion engine to reduce emissions and fuel consumption and increase power output. The high cost of microalgae biomass production, the low efficiency of converting biomass into biodiesel and the increase in NOx production and fuel consumption with the combination of biodiesel in high percentages are the problems of this issue. In this article, by using the new solar still desalination/parabolic trough collector/geothermal hybrid system to supply the required water and heat and to investigate the effect of the influencing factors, the efficiency of microalgae production and transesterification process's conversion efficiency were obtained as 1.04 g/L and 80.22%, respectively. The addition of biodiesel from 0% to 20% in the fuel decreased CO, SOx and HC emissions, but CO 2 and NOx emissions increased. Also, fuel consumption increased and engine output power decreased. The optimum point was found in order to emit the least emissions and reduce fuel consumption and increase the output power for the composition percentage of 11.5% biodiesel in the fuel. [Display omitted] [ABSTRACT FROM AUTHOR]

With the rising usage of fossil fuels, there is an urgent need to develop new technologies specifically based on renewable energy sources to power the vehicles running on fuel. A fuel cell is an electrochemical cell that is used to convert the chemical energy of a fuel directly to electric power. Fuels cells possess advantages such as smaller size, high efficiency, silent operation, etc. However, there can be significant variations in the size and power output of the fuel cells depending upon the application. The focus of this paper is to estimate the performance of an integrated system comprising of Polymer Exchange Membrane Fuel cell (PEMFC) and vapour adsorption refrigeration system to produce electric output and cooling effect simultaneously. The adsorption system in this study is based on activated carbon and methanol combination. The effect of operating parameters such as the operating temperature, current density and evaporator temperature on the energy and exergy efficiency of the system is presented. The study shows a remarkable improvement in the performance of the integrated system compared to PEMFC alone. The results show that the system energy and exergy efficiency decrease as the current density value increases. Maximum system energy and exergy efficiency of 63.01% and 29.88% are achieved. In addition, a maximum energy efficiency of 65.39% was reported at an evaporator temperature of 5 °C and a current density of 0.8 A/cm2. • Thermal integration of PEMFC with vapour adsorption refrigeration cycle is studied. • Energy and exergy efficiency of PEMFC with and without VADRC is analyzed. • The influence of key operating parameters on system performance is investigated. • A maximum system efficiency of 66.83% is achieved after incorporating VADRC. [ABSTRACT FROM AUTHOR]

Worldwide about 550 hydrogen refueling stations (HRS) were in operation in 2021, of which 38% were in Europe. With their number expected to grow even further, the collection and investigation of real-world station operative data are fundamental to tracking their activity in terms of safety issues, performances, maintenance, reliability, and energy use. This paper analyses the parameters that characterize the refueling of 350 bar fuel cell buses (FCB) in five HRS within the 3Emotion project. The HRS are characterized by different refueling capacities, hydrogen supply schemes, storage volumes and pressures, and operational strategies. The FCB operate over various duty cycles circulating on urban and extra-urban routes. From data logs provided by the operators, a dataset of four years of operation has been created. The results show a similar hydrogen amount per fill distribution but quite different refueling times among the stations. The average daily mass per bus and refueling time are around 14.62 kg and 10.28 min. About 50% of the total amount of hydrogen is dispensed overnight, and the refueling events per bus are typically every 24 h. On average, the buses' time spent in service is 10 h per day. The hydrogen consumption is approximately 7 kg/100 km, a rather effective result reached by the technology. The station utilization is below 30% for all sites, the buses availability hardly exceeds 80%. • Small/medium-sized hydrogen refueling stations performance analysis. • Investigation of fuel cell buses operation under real-world conditions. • Actual demand is lower than the planned maximum capacity suggesting future bus fleets ramp up potentiality. • On average, the fuel cell buses consume 7 kg H2 /100 km, meeting the EU targets. • The majority of the refuelings are performed overnight from 8 p.m. to 3 a.m. to secure capacity and availability. [ABSTRACT FROM AUTHOR]

At present, the production of electric energy consumer remote from agro-based centralized networks is done using diesel-generator technology with limited service life of the engine and the extremely low efficiency in the use of expensive fuel. In this paper, is considered an innovative technology of combined production of electricity and heat using a preliminary conversion of diesel fuel in the synthesis gas and then serving it at high temperature electrochemical generator. Synthetic gas to operate the generator air conversion is made of an electrochemical engine diesel fuels in catalytic reactor-burner. On the basis of heat balances of the torch, battery power and boiler are calculated: battery electric efficiency SOFC, chemical efficiency burner, SOFC anode temperature, EMF Planar element, the proportion of hydrogen, oxidized anode SOFC, unit cost of diesel fuel for the production of electricity and thermal energy. Specific consumption of diesel fuel for the production of electrical energy 114 g/kWh (162 g. w. t./kWh), and thermal 31.7 kg/Gj (45.1 kg/GJ, w. t. 189 kg standard fuel/Gcal). [ABSTRACT FROM AUTHOR]

A small applied electric field is particularly crucial in the practical application of dielectric ceramic capacitors, since it means a longer lifetime of the capacitors in practical energy storage applications. Based on the traditional ferroelectric BaTiO 3 , the (1- x)(Ba 0.6 Na 0.2 Bi 0.2)TiO 3 - x NaNbO 3 medium-entropy material is designed in this paper, which correlates configuration entropy with energy storage performance. The findings demonstrate that the BNBT-0.15NN ceramic synchronously achieves high energy storage density (2.95 J/cm3) and the energy storage efficiency (95.2%) at 180 kV/cm when the configuration entropy rises to 1.43R. The idea of medium-entropy energy storage under low electric field is proposed for the first time, opening up a new avenue for research into the preparation of high energy storage dielectric ceramics via exploring medium-entropy composition. [ABSTRACT FROM AUTHOR]

The increasing pollution caused by conventional cars and the problems caused by the use of fossil fuels have drawn the attention of researchers and manufacturers to the design of cars that use clean fuels. Electric vehicles connected to the network have a significant impact on reducing environmental pollution and transportation costs, especially in big cities. The cost of supplying loads to subscribers in the distribution network also includes generation and transmission costs. These costs are directly related to the intelligence of the distribution network and the total amount of energy of electric vehicles. The contribution of each generation unit and each transmission line must be calculated to determine the generation and transmission costs. In this research, in order to maximize the profit of the parking lot owner, improve voltage drop and load factor, a comprehensive framework for optimal energy management in a parking lot is presented, which can provide a method to control the charging of electric vehicles, in addition to meeting the needs of their owners, only as a series of controllable loads that they need to receive electrical energy to charge their batteries. In the next step, considering the inherent characteristic of electric cars, i.e. having a battery, and looking at them as a series of storage resources that can return the electric energy in their battery to the grid if necessary, a method to simultaneously control their charging and discharging is provided. In the final step of the paper, it is assumed that hydrogen storage systems will also enter the circuit, and thus, a comprehensive method for energy management is proposed. Finally, the linearized model of demand response and the proposed scheme along with the modeling of hydrogen storage and electric vehicles are considered to be part of contribution to improve the operation and economic situation of the network. • In practice, the high cost that battery depreciation imposes on car owners when using the V2G feature makes the use of this feature not economically justified. • A comprehensive framework for optimal energy management in a parking lot with the aim of maximizing the profit of the parking lot owner, improving the voltage drop and network power factor is provided. • The proposed method for energy management in the presence of hydrogenous storage systems was applied in a sample parking lot and how it works. • Considering the hydrogenous storage systems, while significantly increasing the profit of the parking lot owner, it also significantly reduces the power received from the network during the peak hours of the network. [ABSTRACT FROM AUTHOR]

The paper puts forward an intelligent approach that deals with the computation of an optimal path with collision avoidance for the stick-carrying twin moving from a pre-assumed start position to a predefined goal position. It has been solved through the efficient implementation of modified cuckoo search, sine cosine algorithm, and particle swarm optimization to design a hybrid algorithm aimed at using the communal advantages of the search and position update ability of these algorithms. The benefits are realized by integrating the egg-laying behavior of the cuckoo species to achieve an efficient global search strategy with modified parameters, local search strategy of particle swarm optimization, and greedy approach of sine cosine algorithm. The proposed algorithm is validated using 10 standard benchmark functions, computer simulation using C language, and real robot platform using Epuck robot to illustrate minimal time, shortest distance, collision avoidance, path smoothness, synchronized action, and reduced energy usage in terms of the path traveled, execution time, the number of steps, and the number of turns in the static as well as the dynamic environment. [ABSTRACT FROM AUTHOR]

Recently-developed twisted multifilament artificial muscles are an intelligent material or device storing energy and outputing work under external stimuli. These muscles are fabricated by a twist-insertion procedure and share a two-step process in triggering rotation or contraction, that is volumetric expansion and tension-torsion coupling. The energy conversion efficiency of thermal actuation for the artificial muscles made of carbon nanotubes has attracted increasing attention due to the giant tensile stroke, record energy density, and easy controllability. In the present paper, the thermal actuation processes of artificial muscles are modeled by numerical simulations, in which the energy conversion efficiency is expressed as the ratio of work output to heat input. The Cosserat curve theory is introduced to analyze the geometric effect of cross-sectional shapes on the tensile TMFAM. The abilities of axial elastic deformation and stretching stable for the CNTBs with typical shapes are quantified. The work output and energy conversion efficiency are then evaluated, offering the opportunity to elevate the mechanical properties of artificial muscles. The strategy to improve the muscle performance is also outlined through their dependence on the geometrical and material parameters. [ABSTRACT FROM AUTHOR]

The focal length of the Fresnel lens changing with the light incident angle will decrease Fresnel lens solar concentrators' energy efficiency and daily working hours, which seriously hinders its commercial application. Existing solutions, mainly including single-axis tracking, two-dimensional tracking, and passive tracking have their limitations and fail to realize the maximum application potential of the Fresnel lens. This paper proposes a novel elastic Fresnel lens solar concentrator, whose focal length can be regulated by tensile deformation. The mechanical and optical coupling simulations are conducted to reveal its concentrating behavior during tensile deformation. An exemplary elastic Fresnel lens with an aperture width of 200 mm and an original focal length of 360 mm is designed and studied. The simulation results illustrate that the optimal base thickness of the elastic Fresnel lens is 1 mm when its prism thickness is 2 mm. Under the optimal thickness parameters combination, the elastic Fresnel lens has an effective elongation rate r about 15%, which increases the focal length by 163 mm and 47% to the original focal length. The focus width only increases from 16 mm to about 20 mm when adjusting the focal length from 360 mm to 523 mm. Besides, the step-zoom strategy increases the exemplified elastic Fresnel lens' acceptable angle from 30° to 45°. The tensile deformation caused zoom method increases the working hours of Fresnel lens by 1.5 times, demonstrating the effectiveness of this method. [ABSTRACT FROM AUTHOR]

This paper investigates conversion of a Nordic oil-heated townhouse into carbon-neutral by different energy efficiency (EE) improvements and an off-grid system including solar photovoltaics (PV), wind power, and battery and hydrogen energy storage systems (BESS and HESS). A heat-pump-based heating system including waste heat recovery (WHR) from the HESS and an off-grid electrical system are dimensioned for the building by applying models developed in MATLAB and Microsoft Excel to study the life cycle costs (LCC). The work uses a measured electrical load profile, and the heat generation of the new heating system and the power generation are simulated by commercial software. It is shown that the EE improvements and WHR from the HESS have a positive effect on the dimensioning of the off-grid system, and the LCC can be reduced by up to €2 million. With the EE improvements and WHR, the component dimensioning can be reduced by 22%–41% and 13%–51% on average, respectively. WHR can cover up to 57% of the building's annual heat demand, and full-power dimensioning of the heat pump is not reasonable when WHR is applied. Wind power was found to be very relevant in the Nordic conditions, reducing the LCC by 32%. [Display omitted] • Energy efficiency improvements notably reduce dimensioning of system components. • Waste heat from FC and electrolyzer covers up to 57% of the annual heat demand. • A full-power-dimensioned GSHP does not reduce the fuel cell dimensioning. • Seasonal storage on a small scale makes the system not economically viable. • Small-scale wind power is expensive, but it significantly reduces the system LCC. [ABSTRACT FROM AUTHOR]

In this paper, we explore the co-movements between renewable and non-renewable energy sources and CO 2 emissions and GDP per capita in Saudi Arabia, respectively. Using the spectral Granger causality approach, our results suggested that non-renewable energy sources lead to carbon emission expansion in the frequency domain. Taken together, a significant causal relationship from fossil to economic growth is perceived over the long-term horizon while renewable energy source drives economic growth over different frequencies and considerably contributes to carbon emissions reduction. The wavelet plots revealed strong discrepancies in all variables in the time-frequency space. While non-renewable energy sources indorsed the economic growth across short-and medium-term scales and contribute to a polluted environment, renewable energy consumption has a substantial effect on carbon emission drop and on economic growth in the short-term. The multiple wavelet outcomes show that renewable energy may not only stimulate the economic growth but also promote sustainable and cleaner environment. The combined effects of non-renewable energy sources rise the carbon emissions. Thus, Saudi's government is counselled to promote the green energy investments and accelerate the transition to renewable energy production as its use as a substitute of fossil fuels carries advantages and opportunities alternating from environment to social-economic. [Display omitted] [ABSTRACT FROM AUTHOR]

Obtaining reliable and high-quality wind speed probability forecast results is of great significance to wind energy utilization and power system management. In this paper, multi-network deep ensemble method, which combines the intelligent optimization algorithm and deep ensemble method, is proposed to deal with the probabilistic prediction problems. This method can effectively integrate a variety of different deep learning neural networks and provide reliable uncertainty estimates for prediction. Furthermore, spatiotemporal multi-network deep ensemble model, which employs multi-network deep ensemble method, is proposed to deal with the probabilistic spatiotemporal wind speed forecasting problems. In the model, three advanced convolutional recurrent neural networks are integrated to capture spatiotemporal information from the underlying meteorological variables. Intelligent optimization algorithm is used to assign weights to each network in the ensemble. In addition, an uncertainty quantification method, which quantify the uncertainty by adjusting the network structure and optimize the uncertainty by utilizing the truncated negative log-likelihood scoring rule, is introduced to provide reliable probability forecasts. The proposed model is applied to a real-world case in the United States. The test results demonstrate that spatiotemporal multi-network deep ensemble model can not only provide high-precision point prediction results, but also provide suitable interval predictions and reliable probability prediction results. Moreover, the impact of input features on model prediction results is also evaluated. [ABSTRACT FROM AUTHOR]

In the ongoing efforts to reduce CO2 and pollutant emissions, hydrogen combustion engine can provide immediately available mature technology for carbon-free transportation. Hydrogen combustion does not produce on-site CO2 emissions, the principal pollutant is NOx (which can be minimized using appropriate combustion control and aftertreatment), and the available ICE technology can be readily modified to accommodate for hydrogen use. The paper provides a prediction of the performance of a hydrogen combustion engine in passenger vehicles, aiming at extending or updating the available research with the current powertrain trends, namely downsizing, turbocharging, and hybridization. Data gathered from a single-cylinder engine fueled by a lean hydrogen mixture are used as input into a mild hybrid vehicle model, which is used for quasi-static drive cycle simulations. The results show NOx emission around the EURO VI limit without the use of any aftertreatment and fuel consumption as low as 1.1 kgH2/100 km in WLTC. • Experimental H2 engine data used for drive cycle simulation of mild hybrid vehicles. • Peak power 80 kW @ 4000 RPM was achieved with 1.5l turbocharged hydrogen engine. • Peak efficiency (BTE) of 42% is obtained, with 38% in most of the engine map. • Very low NOx emissions of 0.1 g/kWh were observed in most of the operating range. • Drive cycle simulation consumption of 1.1kgH2/100 km and 0.02gNOx/km in WLTC. [ABSTRACT FROM AUTHOR]

Two variants of a four-blade axial impeller with diagonally rounded large-surface blades have been developed in order to reach two goals. First, the impeller should be hydrodynamically optimized for coagulation and flocculation processes (wastewater treatment), and second, the manufacturing severity and costs should be low (easily manufacturable impeller). The main process characteristics (power characteristics, blending characteristics, and hydrodynamic characteristics) of both variants of the impeller have been performed in various vessel-to-impeller configurations and the results are presented in the paper. The obtained values were compared with other standard impellers and TECHMIX hydrofoil impellers, and it was found that one of the proposed variants (4TR10) seems to be a perspective hydrofoil impeller for blending processes in the chemical, pharmaceutical, or mining industry. The coagulation/flocculation performance of the impeller has been tested and the results proved that the impeller produces the highest ratio of macroaggregates and the lowest ratio of non-aggregated particles compared to standard impellers. • The new impeller design is applicable for coagulation / flocculation processes. • Process characteristics are determined for various impeller-vessel configurations. • The impeller exhibits a very low energy demand for blending. • The impeller is easy to manufacture. [ABSTRACT FROM AUTHOR]

In this paper, we consider the vehicle routing problem with load-dependent drones (VRPLD), in which the energy consumption of drones is load-dependent and represented by a nonlinear function. To strengthen the collaboration between trucks and drones, a kind of facility called the docking hub is introduced to extend the service coverage of drones. When a truck visits the hub, a part number of parcels are transferred to the drones departing from the hub to serve the designated customers. We propose a mixed-integer model for the problem, which is nonlinear due to the load-dependent energy consumption. To solve the model, we develop a branch-and-price-and-cut algorithm based on the Danzig–Wolfe decomposition framework, and propose a series of acceleration strategies, including two valid inequalities, to expedite the convergence of the exact algorithm. Computational results on a set of randomly generated instances reflect that the proposed algorithm outperforms Gurobi in terms of both efficiency and effectiveness. Compared with VRPLD, the vehicle routing problem with drones (VRPD) which ignores the load-dependent constraints underestimates the total travel cost by 6.83%. Another drawback of VRPD is that some results may become infeasible when considering the load-dependent energy consumption. The results under VRPLD further reveal that a more accurate description of the energy consumption makes the drones rely more on services from auxiliary facilities. We also conduct sensitivity analysis to draw some managerial insights that setting the hub at a reasonable location can significantly reduce the delivery cost and improve truck and drone cooperation efficiency. • The load-dependent energy consumption of drones is introduced as a nonlinear function in VRPLD. • The operation processes of docking hubs are designed differently than Wang & Sheu (2019). • The exact branch-and-price-and-cut algorithm is proposed and verified. • Sensitive analyses are carried out to deduce managerial insights. [ABSTRACT FROM AUTHOR]

This paper presents the development of a fuzzy control implemented in a domestic refrigerator in which the thermal load (food) is included as an input variable and a novel aspect of the control. The fuzzy control regulates the speed of the fan attached to the evaporator and the airflow to the fresh food compartment of the refrigerator according to a set of rules that incorporate the amount of thermal load and the temperature conditions of the compartments. The fuzzy control was evaluated in an empty refrigerator (without food) and with three thermal load conditions. Thus, resulting in a fuzzy control capable of maintaining thermal conditions similar to those obtained with the factory ON/OFF refrigerator controller. In addition, the total energy consumption is reduced by 1.7% when the refrigerator is empty and by a maximum of 9.53% in the presence of a low thermal load. Finally, the coefficient of performance shows increases in all the cases studied with the implementation of the fuzzy control. [ABSTRACT FROM AUTHOR]

In the present paper, a new extractive-azeotropic dividing wall column configuration is designed to recover acetonitrile from wastewater instead of the conventional two-column process. Although the performance of energetic and economic savings is enhanced in the dividing wall column, it is still characterised by high energy consumption. To this end, a methodical framework for designing energy-efficient intensified dividing wall columns is developed to gradually reduce the need for utilities. Results indicate that the reboilers of the extractive-azeotropic dividing wall column can be entirely replaced by the applications of vapour recompressed heat pump and heat exchanger network, which comprehensively improves the energy-saving performance. A multi-criteria evaluation of process sustainability, including energy consumption, total cost, environmental performance, energy efficiency, and inherent safety analysis, is performed among the designs. Results show that the heat-integrated extractive-azeotropic dividing wall column process is inherently safer than the conventional two-column process and reduces at most 51.95%, 89.96%, and 63.58% in total annual cost, CO 2 emissions, and total energy consumption, respectively. [ABSTRACT FROM AUTHOR]

The roundtrip electrochemical energy efficiency is improved from 63% to 76% at a current density of 200 mA cm −2 in an all-vanadium redox flow battery (VRFB) by utilizing modified carbon paper electrodes in the high-performance no-gap design. Heat treatment of the carbon paper electrodes in a 42% oxygen/58% nitrogen atmosphere increases the electrochemically wetted surface area from 0.24 to 51.22 m 2 g −1 , resulting in a 100–140 mV decrease in activation overpotential at operationally relevant current densities. An enriched oxygen environment decreases the amount of treatment time required to achieve high surface area. The increased efficiency and greater depth of discharge doubles the total usable energy stored in a fixed amount of electrolyte during operation at 200 mA cm −2 . [ABSTRACT FROM AUTHOR]

• This paper analysed the thermal, spectral and colour characteristics of PDLC glazing in warm and humid climates using a test cell of 0.3*0.4 m size. • This paper also analysed the Visual characteristics, including daylight glare and circadian entrainment, in a test room with a PDLC sheet on a west-oriented window of 1.3 m * 1.3 m. • This study provides references for installing PDLC glazing in a warm and humid climate. This paper detailed the experimental investigation of the Polymer Dispersed Liquid Crystal (PDLC) glazing over visual comfort, thermal performance, circadian entrainment, and energy consumption of an office room in a warm and humid climate. In addition, an elaborated study was carried out on the PDLC glazing's spectral, visual, thermal, and circadian characteristics. The thermal evaluation was carried out with a test cell of size 0.3*0.4 m. It was observed that the internal glass surface temperature was comparatively higher than the external glass temperature. It indicates the high solar gain of PDLC glazing. Under opaque and transparent states, the Correlated Colour Temperature (CCT) and a Colour Rendering Index (CRI, R a) were almost identical. For an ultraviolet (UV) lamp source, PDLC film reflects most of the radiation under an opaque condition. Circadian Stimulus is 10–20 % more under clear states than the opaque state. A real-time experiment was performed in a test room at Manipal, where the PDLC sheet was pasted on the west-oriented window. Colour rendering and circadian effectiveness were satisfactory. CS was always above 0.3, the minimum requirement for circadian entrainment. Due to the milky appearance of the opaque state, a low solar elevation angle induces more reflection on the workspace, and hence more daylight comes into the interior. Under these conditions, uniformity is less. It is observed that PDLC is most suitable in the south and the north orientation windows for the southern tropical climate. The energy consumption was observed as 0.5 kWh /day. [ABSTRACT FROM AUTHOR]

A 50 kW p photovoltaic (PV) power plant installed in a hospital had its efficiencies analyzed in this work. Two emergency services of the hospital have been chosen to be fed with produced energy. In the present paper, easy sizing up means were used. The PV system is synchronized to the electrical grid to ensure the solar energy production and the batteries charging in priority. In case of electric grid perturbation, the batteries provide with the stored energy. For the studied system, the month of May is the better energy production month among the eight studied months with almost perfect efficiency in terms of meeting the needs of the two connected services. However, this month is one of the heat wave months in the sahelian strip. The batteries energy is very requested to ensure the energy supply in the two emergency services of the hospital. The best operation month is May. However to find the optimum operation, it well be better to install off-grid system. The temperature and local dust are also degradation factors to take into account. This paper shows that the PV off-grid can be used to improve the resilient of the population in areas with high security challenges. The failure of the PV plant is estimated at 0%. Indeed, once the SONABEL grid is desynchronized, the grid inverters use the energy in batteries to continue the injection. The environmental constraints such as low illumination, high temperature, dust, etc. must be added in the perturbation factors of the solar energy production. • New way to improve the population resilience in areas with high security challenges. • In the Sahel the optimum operation of PV power plant is found in the month of May. • The PV plant failure is brought near 0%. • The environmental constraints are the degradation factors to take into account. [ABSTRACT FROM AUTHOR]

Global warming is one of the most important environmental problems in the world. One might state that the most potential considerable cause of global warming is the increase in greenhouse gas emissions in the atmosphere. The commonly suggested method used to struggle with this potential problem is to consume renewable energy sources instead of fossil fuels. In today's World, where the rate of urbanization is very high, the research on the effect of the energy demand of the residential sector on global warming has become a crucial research topic in the energy and climatic literature. Among different solar sectors, the residential sector is a major energy consumer. Considering the residential, commercial, and industrial solar sectors, the residential solar sector has become a major component of total solar energy. It accounts for approximately 43% of total solar. On the other hand, to the best of my knowledge, there exists no empirical study in the literature considering the influence of residential solar consumption on environmental quality. Thus, determining the effect of the most used energy source, residential solar, energy consumption on the environmental quality has arisen the key research problem of this paper. This research analyzes the effects of residential solar energy usage on CO 2 emissions for the period 1989:1–2020:1 in the USA. It has been observed throughout Morlet wavelet analyses that the use of residential solar energy has a strong effect on mitigating CO 2 emissions in the 1–2 year frequency. Eventually, this paper provides relevant potential energy policies that can enhance the efficiency of residential solar energy consumption. Partial wavelet coherence (RSolar-CO 2 || Coal, Hydro, IP), 1989:1–2020:1. [Display omitted] • Considers the impact of residential solar consumption (RSolar) on CO 2 emissions. • Follows the data for the USA for the monthly period 1989:1–2020:1. • Launches wavelet models in which RSolar, CO 2 , Coal, Hydro, and IP are employed. • Reaches the negative impact of RSolar on CO 2 in the USA for the period 1989:1–2020:1 at 1-2 year-cycle period. • Through potential energy policies, residential solar energy consumption efficiency should be increased. [ABSTRACT FROM AUTHOR]

This paper proposes a sensor network information fusion based distributed state estimation algorithm for tracking non-cooperative maneuvering target. In order to lower the communication burden and energy consumption, an event-triggered mechanism is introduced. The distributed state estimation algorithm for maneuvering target tracking is designed by two stages, namely, local filtering stage and consensus fusion stage. The algorithm proposed in this paper can be used to obtain the high accurate state estimation of the target by introducing a multiple suboptimal fading factor even when the target makes big maneuvering. Moreover, a contribution factor is designed in the information fusion stage to improve the accuracy of maneuvering target state estimation and reduce the consensus iteration times. Besides, the stochastic boundedness of the event-triggered distributed estimation algorithm is proved by introducing a stochastic process. Finally, Monte Carlo numerical simulation example is designed to illustrate the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

The dispatch-down of excess wind energy is a growing concern, especially for countries integrating high levels of variable renewable energy. Demand flexibility presents an opportunity to move consumers loads to periods of excess wind energy, which could provide numerous values to the system. While previous research has focused on managing wind energy curtailment (a system-wide issue), much wind energy is rejected due to constraint (a local issue) and hence can only be resolved by local load-on-demand. This paper provides a framework to assess the value of demand flexibility for managing wind energy constraint and curtailment. A methodology to determine the optimal number of subscribers to yield sufficient reduction in excess wind energy while ensuring reasonable cost savings for the subscribers is developed. Analysis shows that this optimal number of subscribers could provide a 67% reduction in constraint and a 74% reduction in curtailment. Consumers can save up to £220 per year, depending on their priority in the dispatch process. A 10-MW wind farm could earn £19,400 annually from avoided curtailments. System operators could save up to 78% on constraint payments. The paper also assesses the network impact of flexible loads and provides a methodology for calculating the heat-pump hosting capacity of the grid. • A framework for utilizing wasted wind energy for heating homes is investigated. • Currently wasted wind energy could save fuel poor households up to £220 per year. • A 10 MW wind farm could earn about £20,000 annually from avoided curtailment. • System Operators could save up to 78% on constraint payments. • Mathematical model to determine heat pump hosting capacity of a grid is developed. [ABSTRACT FROM AUTHOR]

Abstract The thin-film electrode has been regarded as one of the desirable options for the vanadium redox flow battery. However, most of the thin-film electrodes developed to date suffer from high mass transport resistance and deliver unsatisfactory performance. In this work, we proposed a dual-layer thin-film electrode, consisting of a backing layer and a catalyst layer, for flow batteries. The backing layer with larger pores is adapted to improve the concentration distribution as well as to provide mechanical support while the catalyst layer with smaller pores provides sufficient active sites. The electrospun fiber mat is adopted as catalyst layer and backing layers in the study include carbon paper, carbon cloth and graphite felt. It is showed that carbon cloth supported electrospun fiber mat electrode demonstrates an energy efficiency of 76.1% at the current density of 240 mA cm−2, which is much higher that achieved by conventional electrospun fiber mat electrodes (61.9%). After optimizations of flow field designs and key operational parameters, the energy efficiency of battery with dual-layer structured electrodes can reach as high as 80.2% at a current density of 240 mA cm−2. In addition, the present battery can stably operate for more than 800 cycles without obvious decay. Highlights • A dual-layer thin-film electrode was proposed for VRFBs. • The battery performance was much improved with the dual-layer electrode. • The roles of backing layer and catalyst layer were identified. • The effects of backing layer, flow field and flow rates were disclosed. • The battery can operate stably over 800 cycles at 240 mA cm−2. [ABSTRACT FROM AUTHOR]

Abstract Long term electricity consumption forecasting has been extensively investigated in recent years in different countries due to its economic and social importance. In this context, the long term electricity consumption projections of a country or region are highly relevant for decision-making of companies and organizations operating in any energy system. In this paper, it is proposed a methodology that combines the bottom-up approach with hierarchical linear models for long term electricity consumption forecasting of a particular industrial sector considering energy efficiency scenarios. In addition, the Bayesian inference is used for model parameter estimation and, enabling the inclusion of uncertainty in the forecasts produced by the model. The model was applied to the Brazilian pulp and paper industry and it was able to capture the trajectory of the real consumption observed during the 2008–2014 period. The model was also used to generate long term point and probability distribution forecasts for the period ranging from 2015 until 2050. Highlights • Bottom-up Bayesian extension for the long-term electricity consumption forecasting. • The proposed model combines the bottom-up approach with hierarchical linear models. • The proposed model considers energy efficiency scenarios. [ABSTRACT FROM AUTHOR]

In this paper, a real-time chemi-thermomechanical pulping (CTMP) process was investigated, where opportunities were explored to increase energy consumption efficiency with a guarantee of expected pulp properties as a priority. Due to the process instrumentation limitations, such as the lack of advanced regulatory controllers and optimization units, the advanced process controllers and real-time optimization strategies can hardly be implemented in the existing CTMP processes. Therefore, a novel visualization-based process evaluation methodology is proposed to aid the mill operators in making further decisions to improve the process operations. Additionally, to determine the desirable pulp properties for production, an inferential sensor model is developed that estimates the handsheet properties from pulp properties. Also, to assess the model prediction accuracy in real-time, a reliability index model is designed. The proposed methodologies have been validated on a practical CTMP process, and the results show the satisfactory performance of the system. • Developed a strategy to evaluate the CTMP performance using visualization methodology. • A novel inferential sensor model is implemented to determine the desirable pulp properties. • A reliability index model classifying reliability levels and assessing model accuracy is developed. • The proposed model adapts to model updates, uncertainties, and computation resource limitations. [ABSTRACT FROM AUTHOR]

Solid fuel use is harmful to the health of human beings and hinders the sustainable development of society. Although a considerable literature has sufficiently researched the negative consequences of solid fuel use, fewer studies have explored the determinants of residential polluted energy use in the framework of culture and socioeconomics by focusing on ethnic diversity groups. This paper fills this gap by investigating the impact of religion on the decision to use solid fuel for rural households in ethnic minority regions of China. In particular, we argue that to a large extent, religion provides spiritual support in ethnic minority regions, and it is positively associated with solid fuel use. We examine the issue by employing a large-scale dataset, namely, the China Household Ethnic Survey. Furthermore, this paper identifies two channels of the above finding. First, a pension is regarded as a living support that has a moderate effect in shifting towards clean energy adoption. Second, households located in less remote regions are able to counteract the sole spiritual support of religion, which also mitigates solid fuel use. The results are robust after addressing endogeneity and applying recent developments of alternative models. This paper further confirms that households with various religious activities turn out fewer working hours and have larger related expenditures, which results in less disposable income for energy use. In terms of policy implications, this article suggests the importance of recognizing the role of substantial living support and social inclusion in mitigating the negative impact of religion on clean energy use among rural households of ethnic minority regions. [ABSTRACT FROM AUTHOR]

Given the role that renewable energy consumption plays in transitioning to a low-carbon economy, it is critical for policymakers to understand its determinants. Although uncertainty has increased significantly since the early 2000s, little is known about its effect. To fill this gap, the paper provides novel evidence of the effect of policy-induced uncertainty on renewable energy consumption after controlling for income, institutions and innovation in G7 countries over the period 1997–2019. Using the nonlinear autoregressive distributed lag model, the paper reveals its asymmetric effects in the long run, implying that both a negative and a positive shock in lagged uncertainty reduce renewable energy consumption. The effect of uncertainty proved to be significant in the same direction, but not asymmetric in the short run. However, the effect of all other variables remained insignificant in the short run, which is not the case in the long run. Indeed, the results confirm that income and investment in research and development drive renewables, while it is hindered by more economic freedom in the long run. Therefore, consistent, clear and well-communicated energy and economic policies are called for, along with technological advances, as they can help minimize policy uncertainty and promote renewable energy use. [ABSTRACT FROM AUTHOR]

The continuous increase in global energy consumption as a result of rapid population growth, combined with the detrimental impact of fossil fuels on the atmosphere, has made it critical to extract renewable energy through various technologies and turn it into electricity. A hybrid photovoltaic-thermal collector can be an innovative alternative to harness renewable energy. The utilization of hybrid photovoltaic-thermal solar collectors is increasing day by day due to its advantages. This type of collector can generate both heat and electricity at the same time and convert absorbed solar radiation more efficiently than a solar thermal collector or a typical photovoltaic module. In order to improve the performance of the hybrid photovoltaic-thermal (PV/T) solar collector, nanofluid can be an effective solution. It has been found that serpentine, rectangular, microchannel, sheet and tube, etc., are some categories of geometries utilized in the PV/T system. Both experimental and computational studies were conducted related to nanofluids application in PV/T collectors in recent years. Most of the studies were done utilizing some common nanofluids, e.g., Al 2 O 3 , CuO, ZnO, and SiO 2. It has been noticed that utilizing nanofluids significantly enhances overall performance, thermal and electrical efficiency, heat transfer characteristics, and exergy. This paper comprehensively reviewed various aspects of using nanofluids, including energy efficiency, exergy efficiency, overall efficiency, heat transfer coefficient, daily yield, power generation, entropy production, exergy loss, and temperature drop in hybrid PV/T collectors in a systematic way. Besides, the paper incorporated all recent findings and included experimental, numerical, and combined studies in the review. • MWCNT nanoparticle provides more efficiency compared to oxide-based nanoparticles. • Ag–H 2 O can enhance thermal output up to 13% than the water-cooled system. • SWCNT nanoparticles improve daily yield and have a relatively cheap production cost. • Energetic and exegetic performance can be increased by utilizing nanoparticles. • Using nanoparticles notably enhance power generation rate, and heat transfer ability. [ABSTRACT FROM AUTHOR]

The use of hydrogen energy and the associated technologies is expected to increase in the coming years. The success of hydrogen energy technology (HET) is, however, dependent on public acceptance of the technology. Developing this new industry in a socially responsible way will require an understanding of the psychology factors that may facilitate or impede its public acceptance. This paper reviews 27 quantitative studies that have explored the relationship between psychological factors and HET acceptance. The findings from the review suggest that the perceived effects of the technology (i.e., the perceived benefits, costs and risks), and the associated emotions, are strong drivers of HET acceptance. This paper does, though, highlight some limitations with past research that make it difficult to make strong conclusions about the factors that influence HET acceptance. The review also reveals that few studies have investigated acceptance of different types of HET beyond a couple of applications. The paper ends with a discussion about directions for future research and highlights some practical implications for messaging and policy. • Perceived effects, and associated emotions, are strong predictors of acceptance. • Unclear what context-specific beliefs underpin attitudes towards hydrogen. • Most studies focused on acceptance of hydrogen fuel stations and hydrogen cars. • A dearth of research investigating acceptance of the whole hydrogen value chain. • Identified inconsistencies in the measurement of psychological constructs. [ABSTRACT FROM AUTHOR]