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• Customize a formula for sensitivity analysis to screen characteristic parameters. • Use an improved hybrid neural network with high fitting exactness and great prediction effect to establish efficiency regression prediction of SRM. • Propose improved northern goshawk optimization with strong search ability and fast convergence to optimize the objective function of the model, achieving an increase of 2.975% in efficiency. Six-degrees of freedom (6-DOF) parallel mechanisms driven by switched reluctance motors (SRMs) can realize flexible control with high precision. Efficiency is an important indicator to measure the speed control system of SRMs. There are many characteristic factors affecting efficiency and strong nonlinear relationships between different characteristic parameters, which makes it difficult for analytical models and traditional neural network models to express their spatial correlation. For this reason, a convolutional neural network (CNN)-bidirectional long short-term memory network (BiLSTM) efficiency regression prediction model (CNN-BiLSTM-SENet) that integrates the attention mechanism (SENet) is proposed. Firstly, customize a formula for sensitivity analysis to screen characteristic parameters of efficiency. Secondly, build the CNN-BiLSTM-SENet model and use sparrow search algorithm (SSA) for hyperparameter optimization, input data to CNN to extract high-dimensional feature vectors that reflect complex changing relationships between features and efficiency while establishing feature channels. Embed the SENet to adaptively perceive and assign different weights to the feature channels, enhancing the influence of key features. Input the feature vectors outputted by the front-end network to BiLSTM to bidirectionally learn coupling relationships between sequences and complete regression prediction. Finally, propose improved northern goshawk optimization (MNGO) to solve the regression model to obtain the maximum efficiency and corresponding characteristic parameters. The results proved that the SSA-optimized CNN-BiLSTM-SENet model has higher fitting exactness and better prediction effect for efficiency regression prediction, and the MNGO also has stronger search ability and faster convergence. [ABSTRACT FROM AUTHOR]

The building space cooling is accounting for a significant portion of global energy use, and it is essential to enhance chiller efficiency for energy reduction and climate change mitigation. Chiller systems with multiple compressors provide the flexibility to meet varying cooling demands. The load-sharing strategy controls how the cooling load is distributed among the compressors. The load-sharing strategy optimization can significantly affect the chiller overall power consumption. This paper presents a mathematical analysis of the power consumption of centrifugal compressors under specific ambient temperatures. The influence of the inlet guide vane and the variable frequency drive efficiency on the compressor power consumption are considered and discussed briefly. An optimal load-sharing strategy for commonly used systems with identical compressors is proposed. Additionally, the scenarios involving a mix of different compressors are investigated. To validate the proposed strategies, a case study using the established performance data of a commercial centrifugal compressor is conducted. The case study results align with the mathematical analysis and the proposed strategy. This study provides valuable insights for designing and managing efficient chiller systems. • A mathematical study on the load-sharing strategy for chillers with multiple centrifugal compressors is presented. • Equal load-sharing strategy is found to be the most energy-efficient for chiller with identical compressors. • A simple and practical method, named DTPCOP, is proposed to determine the optimal number of active compressors. [ABSTRACT FROM AUTHOR]

Moving image recognition has become a well-explored problem in computer vision. However, it is difficult for the traditional convolutional neural network (CNN) model to effectively capture timing information in motion. For better use of video sequence features and to improve the accuracy of action recognition, Therefore, this paper proposes a Three-dimensional CNN (3DCNN) model based on Gated Recurrent Unit (GRU) with an attention mechanism. The model leverages 3DCNN for deep feature extraction from video frames, employs GRU to capture the temporal dynamics of feature sequences and incorporates an attention mechanism to emphasize key frames, which improves moving image recognition. Demonstrating superior accuracy in'Cross-Subject' and'Cross-View' evaluations, our model surpasses standard benchmarks with accuracies of 83.2% and 87.3% respectively. • We combined 3 DCNN and GRU to classify the sequences of the motion images. • The framework adds attention mechanisms to improve recognition capabilities. • Experimental results show that the action recognition accuracy is increased by 6%. [ABSTRACT FROM AUTHOR]

This paper addresses the critical task of hacker identification within the cyber traceability system. While the latest hacker group identification method based on the heterogeneous graph attention network (HGHAN) holds promise in discovering hacker groups, its potential is hindered by the underutilization of node information and poor training efficiency. Particularly, attribute information dilution during node feature extraction and lengthy training for node embedding vector reassignment when new nodes are added have been observed. To rectify these shortcomings, the paper presents an improved model for hacker group identification. This novel approach leverages dynamic heterogeneous graph node updating to significantly boost efficiency without compromising the original model's classification accuracy. The key aspects of the method involve pre-learning for node attribute training vectors, LSTM (Long Short-Term Memory) and attention mechanisms for node feature vector refinement, and introducing a sparse matrix and dynamic node update scheme. The experimental results demonstrate marked improvements in training efficiency and graph update processes while maintaining classification accuracy. This advancement signifies the improved HGHAN model's capacity to adeptly navigate real-world network dynamics, assisting researchers in pinpointing malicious attackers amid cyber incidents. [Display omitted] • Implement heterogeneous graph node embedding vector updates in dynamic scenarios to replace retraining. • Adopt pre-training in the node feature extraction process to enhance feature utilization. • Introduce a triplet sparse matrix in the node embedding process to save space and improve efficiency. • The experiments show that the proposed model can greatly reduce the time consumption without affecting the identification effect of the basic model. [ABSTRACT FROM AUTHOR]

This paper proposes a novel Redundant Cooperative Control (RCC) strategy to address the pollination sequence planning problem for a mobile pollination robot in the greenhouse. Firstly, the RCC strategy divides the robot's workspace into subspaces based on the distribution of flowers through clustering. Subsequently, the RCC strategy plans the traveling salesman problem within the visual field of these subspaces, seeking a compromise solution for an optimal path. Finally, the RCC strategy utilizes the redundant motion capabilities of the mobile chassis and robotic arm to accomplish the pollination task during the movement. The RCC strategy exploits the available redundancy in both the agricultural robot's mobile platform and end-effector, carefully balancing computational complexity and path quality. To validate the effectiveness of the RCC strategy, we designed a series of experiments conducted on our pollination robot platform, measuring different strategies. The results demonstrate that the RCC strategy achieves an average pollination rate of 7.5 s per flower, representing a 36.4% improvement compared to the most common intermittence strategy. Furthermore, the RCC strategy can be extended to tasks such as harvesting and pruning, significantly enhancing the efficiency of robot task execution even in industrial and service sectors. • Proposed a redundant cooperative control strategy (RCC). • Designed a tomato pollination robot with redundant motion capability. • The RCC strategy can be applied to pollination in motion. • The pollination robot can achieve a pollination rate of 7.5 s per flower. [ABSTRACT FROM AUTHOR]

Continuous developments in Proton Exchange Membrane Fuel Cells (PEMFC) make them a promising technology to achieve zero emissions in multiple applications including mobility. Incremental advancements in fuel cells materials and manufacture processes make them now suitable for commercialization. However, the complex operation of fuel cell systems in automotive applications has some open issues yet. This work develops and compares three different controllers for PEMFC systems in automotive applications. All the controllers have a cascade control structure, where a generator of setpoints sends references to the subsystems controllers with the objective to maximize operational efficiency. To develop the setpoints generators, two techniques are evaluated: off-line optimization and Model Predictive Control (MPC). With the first technique, the optimal setpoints are given by a map, obtained off-line, of the optimal steady state conditions and corresponding setpoints. With the second technique, the setpoints time profiles that maximize the efficiency in an incoming time horizon are continuously computed. The proposed MPC architecture divides the fast and slow dynamics in order to reduce the computational cost. Two different MPC solutions have been implemented to deal with this fast/slow dynamics separation. After the integration of the setpoints generators with the subsystems controllers, the different control systems are tested and compared using a dynamic detailed model of the automotive system in the INN-BALANCE project running under the New European Driving Cycle. • The control structure of a PEM fuel cell system in an automotive application is described. • An off-line optimal setpoint generator is compared to MPC techniques. • Slow and fast dynamics are split in the MPC design for computational burden reduction. • Simulations are based on a model tuned using experimental data from a real automotive fuel cell system. [ABSTRACT FROM AUTHOR]

• An improved cascade method for compression-absorption heat pump is proposed. • The improved cascade heat pump can output temperature 110 °C at inlet source 10 °C. • The energy performance of improved cascade method is 16.2% higher than existing mode. • The exergy performance of novel cascade method is raised by 19.2% than existing mode. • The novel cascade method can increase the available heat capacity by 238.4%. Air is a readily available and renewable source, but its efficient utilization for industrial heating is hindered by the significant temperature mismatch between the low-grade air source and the high-temperature industrial demand. Heat pumps can elevate the source temperature from low to high levels. However, there is still a significant knowledge gap in achieving output temperature exceeding 90 °C when the input source is below 30 °C. While there are some preliminary studies on air-source heat pumps operating in the mentioned temperature range, they have yet to distinguish the respective coupling temperatures required for different cascaded components. Therefore, the optimal cascade configuration between various sub-cycles has not been established, and the full efficiency potential remains untapped. To address the identified limitations, in this work, an advanced cascade method is proposed and applied to the compression-absorption heat pump (CAHP). The novel cascade method allows independent control of the coupling temperature in different branches as needed, facilitating an optimal cascade configuration between various subloops. Consequently, the operating efficiency of CAHP is optimized. Simulation results show that the proposed cascade method reduces the exergy destruction of CAHP by 6.3% compared to the existing mode. Moreover, it always achieves higher efficiencies in the studied conditions, with a maximum increase in the coefficient of performance and exergy coefficient of performance by 16.2% and 19.2%, respectively. Under ambient temperature of 10 °C to –30 °C and an output temperature of 100 °C, the improved cascade CAHP exhibits an increase in heating capacity, ranging from 57.2% to 238.4% higher than the existing mode. These advantageous features contribute to achieving cleaner industrial heating with air source heat pumps. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), spectrum efficiency and energy efficiency are two challenging issues to be addressed due to the scarcity of spectrum and its limited energy. In this paper, we study efficient parallel scheduling with power control and successive interference cancellation (SIC) aimed at maximizing spectrum and energy efficiency, and formulate the efficiency maximization scheduling (EMS) problem as a mixed integer nonlinear programming (MINIP) problem. Given the high complexity caused by mixed variables, we first analyze the critical variables affecting efficiency to transform the MINIP problem into a combinatorial linear programming (LP) problem, which is further decomposed into two linear minimization problems. Then, a recursive relationship between the optimization variables is explored, through which we propose a two-stage scheme that solves the minimization problems with lower complexity. Finally, distributed implementation of the scheduling scheme is provided to iteratively explore the maximum feasible concurrent links in the networks. Extensive results demonstrate the superior performance of our proposed scheme in improving spectrum and energy efficiency. Specifically, our scheme achieves 12.16% to 66.15% higher spectrum efficiency and 18.84% to 88.20% higher energy efficiency than the existing schemes. [ABSTRACT FROM AUTHOR]

Liquid air energy storage (LAES) technology is a promising large-scale energy storage solution due to its high capacity, scalability, and lack of geographical constraints, making it effective for integrating renewable energy sources. The core unit of the LAES system is the cold energy storage (CES) unit, which significantly influences its overall efficiency. However, the current mainstream liquid-phase and solid-phase CES methods have inherent drawbacks, including safety, environmental issues, and the dynamic effect of the thermocline. Moreover, previous research has often over-idealized the CES unit and neglected the actual heat transfer processes during the CES and cold energy release (CER) processes. In the innovative study, a gravity-driven moving packed bed (MPB) based LAES system (MPB-LAES) adopting quartz sand as the CES medium is proposed. A thermodynamic model for the LAES system is constructed, and the gas-solid counterflow coupling heat transfer model for the MPB is developed based on the continuous solid-phase model and finite difference method. The accuracy of the model is validated through experimentation using the constructed test apparatus. The research findings reveal the gas-solid coupling heat transfer characteristics in the low-temperature region of −180 ° C to 30 ° C , particularly the asymmetry during the CES and CER processes. The cold energy transfer mechanism within the CES unit is also uncovered, and the analysis of exergy destruction within various components is carried on. Through design parameter analysis and optimization of the MPB-LAES system, an impressive round-trip efficiency of 57.0% is achieved. This marks a significant breakthrough as it is the first report that a LAES system based on solid-phase CES has attained a round-trip efficiency (RTE) of over 55.0% while considering the actual heat transfer processes. • The LAES system utilizing moving packed beds is proposed. • The gas-solid coupling heat transfer model is established and verified. • The cold energy transfer mechanism in the CES is uncovered. • Irreversible analyses are performed in the CES and CER processes. • An RTE of 57.0% is achieved considering actual heat transfer for the first time. [ABSTRACT FROM AUTHOR]

• The length ratio of the TPCT can significantly affect its heat transfer efficiency. • There exists the best length ratio for the TPCT with specific inclination angle. • The best length ratio changes with the inclination angle and inner diameter. Two-phase closed thermosyphons (TPCTs) have been widely used in solar energy utilization. The work presents an optimization of the TPCT used in cooling foundation in permafrost regions. A series of experiments under negative temperature conditions were conducted to investigate the effect of length ratios (LRs, length ratio of the evaporator section to the condenser section) on the cooling performance of the TPCT. Experimental results show that there exists a best LR for each angle, and it varies with the inclination angle. As an example, for the TPCT with 5.0-cm inner diameter, the maximum efficiency can be decreased by 17.3% for the TPCT with the LR of 1.00 compared with the TPCT with the best LR of 1.65. Under the best LR, the efficiency can be raised by 30.2% for the TPCT with the inclination angle of 20° compared with that of 90°. Besides, the best LR also changes with the pipe inner diameter, e.g. the best LR varies from 1.65 to 1.27 when the inner diameter changed from 5.0 cm to 8.1 cm. The results suggest that the equivalent length of the evaporator section should be appropriately lengthened to enhance the cooling performance of TPCTs in permafrost engineering. [ABSTRACT FROM AUTHOR]

Since trains usually have long travel mileage requirements, designing an optimal energy management strategy has great potential for reducing energy consumption. First, a hybrid train power component model was developed, and the train operating efficiency, as well as a map of the optimal integrated efficiency of the entire vehicle operation, was derived for each mode from simulation calculations by analyzing the power flows in different operating modes. Next, the overall optimal efficiency of the entire vehicle was used to determine the mode division rules, and proportional integral control was used to ensure that the engine and motor operated at the target speed under the target torque. Finally, with the optimization objectives of reducing the fuel consumption of the entire vehicle and maintaining a balanced battery state of charge, a forward simulation model for the overall efficiency optimization of the entire vehicle was built in the MATLAB/Simulink software. Then, the trajectories of the engine and motor operating points, the fuel consumption, and the battery SOC were obtained for certain operating conditions. The effectiveness of the energy management strategy based on integrated efficiency optimization was verified by comparing the simulation results for the hybrid train with those of a conventional internal combustion engine train. [Display omitted] • Models are created for the hybrid train's dynamics and power components. • A comprehensive efficiency optimization diagram for hybrid trains is constructed. • Optimization of power and torque distribution based on optimal efficiency • The suggested energy management approach can enhance dynamics and the economics. [ABSTRACT FROM AUTHOR]

Heat pipe cooled reactors with closed Brayton cycle (CBC) have the potential of achieving both high efficiency and high safety. However, the coupled characteristics and performance of CBC coupled with heat pipe reactors have not been well studied. Few works consider both the neutron dynamics in heat pipe cooled reactors and the dynamic heat and mass transfer in CBC. In this paper, a novel nuclear power system configuration, heat pipe cooled reactor with CBC, is proposed and comprehensively analyzed. A dynamic model is built based on the modular modeling idea, and verified using a Brayton cycle test bench. The proposed system has load following capability within certain motor speed, and its maximum thermal-electric energy conversion efficiency exceeds 20%. The dynamic charge amount control strategy is further proposed to improve efficiency. The maximum efficiency improvement is about 5% at 2kWe. The self-power-regulation and inherent passive safety of the reactor are verified through dynamic simulation. The power and temperature overshoots of the dynamic responses are selected as quantitative indicators of system dynamic performance. MAPs of the temperature and power overshoots for unit changes in output power are obtained, and can be used to evaluate the system safety during dynamic operations. • Coupled dynamic model of heat pipe cooled reactor and closed Brayton cycle. • Considering both the neutron dynamics and dynamic heat and mass transfer. • Dynamic charge amount control strategy for higher energy conversion efficiency. • MAPs for evaluating the efficiency and safety of the system. [ABSTRACT FROM AUTHOR]

• The work and efficiency of advanced gas turbine cycles are analytically optimized. • Polytropic efficiencies are used for the compression and expansion processes. • The overall and intermediate pressure ratios which maximise the net-work are given. • The ranges of the pressure ratios yielding a benefit in the efficiency are found. • The maximum-efficiency point is analytically given for the intercooled & reheat cycle. The paper presents a theoretical analysis of advanced gas-turbine cycles. Specifically, three cycles are investigated, that is the intercooled, the reheat, and the intercooled and reheat cycles. The internal irreversibilities, which characterise the compression and expansion processes, are taken into account through the polytropic efficiencies of the compressors and turbines. New analytical formulations for the overall and intermediate pressure-ratios which maximise the net work of the three aforementioned cycles are proposed along with an order relation between these optimum pressure-ratios. Moreover, the thermal efficiency of these cycles is also analysed providing, among other findings, the ranges of the intermediate pressure-ratios returning a benefit in the thermal efficiency in comparison with the simple cycle. Finally, for the sole intercooled and reheat cycle, a novel analytical expression for the maximum point of the thermal efficiency is given. It is also shown that, for the intercooled and reheat cycle, there is a unique value of the overall pressure-ratio which simultaneously maximises the net work and the thermal efficiency. To give some quantitative information, consider a maximum to minimum cycle-temperature ratio equal to 1573/300 and a compressor (resp. turbine) polytropic-efficiency equal to 0.8 (resp. 0.88). The net work and the thermal efficiency are maximised by a set of overall pressure-ratios obeying an order relation. The simple, the reheat, the intercooled, and the intercooled and reheat cycles reach the maximum net-work (resp. thermal efficiency) for increasing values of the overall pressure-ratio, that is 8.550 (resp. 18.260), 14.950 (resp. 25.039), 20.846 (resp. 39.984), and 73.109 (resp. 73.109). The reheat cycle achieves a 34.899% (resp. 6.077%) gain in the net work (resp. thermal efficiency), while the intercooled cycle returns a 31.477% (resp. 15.970%) increment. The maximum net-work of the intercooled and reheat cycle exactly doubles that of the simple cycle. Finally, the maximum thermal efficiency of the intercooled and reheat cycle yields a 24.966% improvement in comparison with the simple one. [ABSTRACT FROM AUTHOR]

Abstract Energy efficiency improvement of electrical motor drives has recently become a very interesting subject. Several methods have been proposed in the literature to improve the efficiency of permanent magnet synchronous machine (PMSM) with sinusoidal back-EMF. These methods are not precise and appropriate for brushless DC machine (BLDCM) with trapezoidal back-EMF. As a unique solution, this work introduces a flux controlled based loss minimization algorithm suitable for BLDCM that considers iron loss as well as influence of back-EMF harmonics; consequently promotes efficiency of machine. In this regard, the loss model of PMSM is extended based on multiple reference frame analysis to include back-EMF harmonics of BLDCM. As an advantage, proposed modified loss model does not require any additional data about the dimensions of machine that makes it suitable for industrial motor drive applications. The Proposed loss model is validated through experimental tests in different operating conditions. Afterward, by applying direct torque and indirect flux control of BLDCM as the control technique, d-axis current in the rotor reference frame is controlled to reduce the air gap flux and consequently iron loss of the machine. Finally, a procedure is presented to determine the optimum d-axis current which maximizes the efficiency. Effectiveness of proposed control system is evaluated using simulation results in MATLAB/Simulink and experimental results on a practical prototype. It is indicated that depending on the operating conditions, about 2% to 11% of efficiency improvement would be achieved in the proposed method. Highlights • An accurate loss model is developed for BLDCM considering iron loss and harmonics. • Extra iron loss due to unrequired flux at the air gap is reduced. • Proposed method determines optimum flux corresponding to minimum loss condition. • Model based loss minimization algorithm of BLDCM is experimentally implemented. [ABSTRACT FROM AUTHOR]

In the steel industry, the blast furnace (BF) is a core piece of equipment along the route from iron ore to steel, with the largest energy consumption and CO 2 emissions. The stable, efficient, and economically viable thermal control of blast furnaces is still a challenging task, and fully automatic solutions are not applied industrially. The process exhibits multi-phase and multi-scale physio-chemical phenomena, in the presence of fast and very slow dynamics with latency periods of 6-8 h. Direct online measurements of key inner variables are missing, and unknown disturbances are strongly influencing the process; in particular, the quality of solid raw materials that are fed at the top of the furnace. Partial automation is the state-of-the-art strategy in the operation and control of industrial blast furnaces, and the experience and the dedication of the operators have a direct impact on the stability and efficiency of the operation. Model-based optimizing control schemes, which can be deployed either in closed-loop or as a guidance system to achieve a smooth, efficient, and reliable operation of blast furnaces, are promising. In this work, we propose a hybrid dynamic model based optimizing control scheme for the stable, energetically efficient, and economically optimal thermal control of blast furnaces. The underlying optimization problem is formulated as a combined tracking and performance optimizing control problem, where the goal is the tight control of the hot metal silicon content ([ S i ]) and the slag basicity (S B), while simultaneously maximizing the CO -efficiency of the furnace. These two variables are key product quality indices, and [ S i ] is an indicator of the internal thermal state of the BF process. Simulation results using real operational data of a large-scale industrial blast furnace are presented to demonstrate the potential of the approach for an improved operation of blast furnaces. [ABSTRACT FROM AUTHOR]

The Allam cycle is an innovative clean power cycle that reduces environmental pollution associated with fossil fuel-based power production by capturing the generated carbon dioxide. Numerical simulation of the cycle performance has been reported in past studies. This article develops a new method to predict and optimize the thermal efficiency of the cycle. Optimization of the cycle efficiency is performed with a thermodynamic model with respect to the turbine inlet and exhaust pressures at a fixed turbine inlet temperature (TIT). A criterion is established for the maximum efficiency which subsequently relates the turbine inlet and outlet pressures, exit pressure of the CO 2 compressor, and minimum cycle temperature. Using a previously developed process model, it is shown that the turbine cooling flow rate has a negligible impact on the optimum turbine pressures although it reduces the cycle efficiency by 2–3%. The process model is also used to assess the accuracy of the present method over a wide range of turbine inlet pressures and a CO 2 compressor exhaust pressure (p C O 2 e) of 60 and 80 bar. The average percentage error is found to be −1.6 ± 0.3% for TIT = 1431 K, p C O 2 e = 80 bar and 1.3 ± 0.3% for TIT = 1331 K, p C O 2 e = 60 bar. The methodology developed in this paper improves the understanding of relationships between the key process parameters of the Allam cycle at the condition of maximum efficiency. [ABSTRACT FROM AUTHOR]

Systems with reversible solid oxide cells (rSOCs) can potentially overcome the spatio-temporal mismatch between intermittent generation from renewables and continuous electricity demand by operating bi-directionally. Achieving high energy conversion efficiency is one of the critical design objectives for a typical rSOC system. However, only a few papers discuss the effect of parameters and system processes on efficiency, and thermal management designs considering gas flow rates of the fuel and air loops are not yet seen. This work presents a novel rSOC-based system that employs a heat recovery unit for absorbing thermal energy as parasitic power gain and a water-gas heat exchanger instead of the electric evaporator to utilize the stack off-gas secondarily. Modeling and efficiency analysis of such a system is performed using a physically finite element method-based rSOC stack model coupled with extra auxiliary component models. Results indicate that efficiencies of 92%, 71.1%, and 62.4% can be achieved at 1,023 K and 1.23 bar in electrolysis, discharge, and the round-trip, respectively. The parasitic gain can significantly improve system efficiency and output performance and reduce the power loss in regulating the temperature uniformity of the stack with increased airflow. The outcomes can serve as guidelines for the thermal management design of real rSOC systems and control strategies optimization. [ABSTRACT FROM AUTHOR]

Nowadays environmental concerns call for a transition towards an economy based on fossil fuels to a low carbon one. In order to achieve this goal, efficiency optimization of existing energy systems through waste heat to power conversion units based on bottoming Organic Rankine Cycles (ORC) is one of the actions that appears to be suitable and effective both from cost and environmental perspectives. Indeed, these units are able to increase the overall efficiency of production processes, existing facilities and renewable power plants with a limited payback time. However, despite the increasing number of ORC installations at megawatt scale, the waste heat rejected by industrial processes has rather a widespread nature. Hence, ORC units with a power output in the range of kilowatts should be developed to address this opportunity for heat recovery and for business. In the current research activity, a dynamic model of an ORC system was developed in a commercial 1D Computer Aided Engineering software platform. Sub-models of the two plate heat exchangers and of the multi-stage centrifugal pump were developed and calibrated using performance data of industrial components at design and off-design conditions. On the other hand, the R245fa radial turbine design was accomplished using a design procedure that provided geometrical and performance data for the mapping of the device by means of a 1D tool. A steady-state off-design analysis at different operating conditions at the evaporator was further carried out optimizing pump and turbine speeds to maximize the net power output. Furthermore, the thermal inertial effects at the evaporator were assessed with reference to a sample heat load profile of the water hot source and at different time scales. [ABSTRACT FROM AUTHOR]

This paper presents a space vector modulation (SVM) based Direct Torque Control strategy (DTC) for induction motor (IM) in order to overcome the drawbacks of the classical DTC. SVM can reduce the high torque and flux ripples by preserving a fixed switching frequency. This technique is known by the closed loop torque SVM-DTC. Moreover, the control scheme performance is improved by inserting a second order sliding mode super twisting controller in the outer loop for speed regulation. This nonlinear technique ensures a good dynamic and high robustness against external disturbance. Furthermore, the IM energy optimization is treated in the second objective of this paper. A proposed model based loss minimization strategy is presented for efficiency optimization. This strategy chooses an optimal flux magnitude for each applied load torque. The proposed optimized SVM-DTC algorithm will be investigated by simulation and real time implementation using Matlab/Simulink with real time interface based on dSpace 1104 signal card. [ABSTRACT FROM AUTHOR]

High-rise building construction is highly complex and involves many different disciplines. Such projects can only be accomplished efficiently and with appropriate quality by means of an overall optimized construction process. However, the understanding of the term “quality” among involved participants is not always equivalent. E.g. providing required tolerances of elevator shaft walls constantly throughout the concrete works is often a challenging task during the execution of in-situ concrete works. This paper is based on the scientific research project “Efficiency optimization and quality control of engineering geodesy processes in civil engineering” (Effizienzoptimierung und Qualitätssicherung ingenieurgeodätischer Prozesse im Bauwesen - EQuiP), which aimed at developing a method for instant quality assurance in construction based on geodetic surveying techniques, and at the same time optimizing the efficiency of the process, e.g. with respect to time. This paper shows how hierarchical and modular modeling of construction and geodetic processes using high-level Petri nets delivers a base for a real time quality evaluation and re-planning on construction site. As an example, this modeling approach is simulated for the construction of concrete stairs and elevators core of a characteristic high-rise structure. The concrete works were considered to be carried out using climbing formwork. Three different scenarios are shown in this paper. The first scenario is simulated with deterministic durations and validates the developed Petri net. The second scenario uses stochastic process durations to show the robustness of the construction process. Finally, disturbances and delays are integrated and an automated rescheduling based on prioritized alternative paths is used. [ABSTRACT FROM AUTHOR]

—Intending to enhance the efficiency of dual-active-bridge (DAB) converters, this paper presents a four degree-of-freedom (DF) efficiency optimization method based on the comprehensive loss model. Besides the traditional triple-phase-shift modulation, the switching frequency is added as another control DF to minimize the core loss of the high-frequency transformer (HFT). Considering the nonlinear characteristics of the switching devices and the HFT, the comprehensive loss model is established first to reflect the converter's overall loss directly. Then the algorithm-based efficiency optimization solution is proposed to investigate the 4-DF modulation variables, which are subject to the minimal overall loss of the DAB converter in a given operating condition. A neural network (NN) is then adopted to model the mapping relationship between the ideal 4-DF variables and the working conditions. On this basis, a closed-loop controller that combines the traditional PI regulator and the NN module is suggested to realize both the output target control and the efficiency optimization. Finally, the performance of the proposed control strategy is fully verified through a 1.2 kW experimental prototype. The experimental results show that the converter's efficiency is significantly improved with the NN-aided 4-DF control strategy. • An accurate comprehensive loss model of the DAB converter is established. • Frequency modulation is an effective scheme for optimizing core loss of HFT. • The frequency-adjustable TPS modulation enhances the converter efficiency. • The average efficiency increased by 0.95% compared with the existing methods. • An NN-aided controller performs target control and efficiency improvement. [ABSTRACT FROM AUTHOR]

Bioelectrochemical systems (BESs) are integrated water treatment technologies that generate electricity using organic matter in wastewater. In situ use of bioelectricity can direct the migration of ionic substances in a BES, thereby enabling water desalination, resource recovery, and valuable substance production. Recently, much attention has been placed on the microbial desalination cells in BESs to drive water desalination, and various configurations have optimized electricity generation and desalination performance and also coupled hydrogen production, heavy metal reduction, and other reactions. In addition, directional transport of other types of charged ions can remediate polluted groundwater, recover nutrient, and produce valuable substances. To better promote the practical application, the use of BESs as directional drivers of ionic substances requires further optimization to improve energy use efficiency and treatment efficacy. This article reviews existing researches on BES-driven directional ion transport to treat wastewater and identifies a few key factors involved in efficiency optimization. [ABSTRACT FROM AUTHOR]

This paper conducts research on the fuel accommodation control of a fuel-flexible engine. Blended fuels from gasoline and diesel are tested on a compression ignition engine. Two problems with the fuel-flexible engine are studied. One problem is that the engine brake torque output is different with different fuels, and the other problem is that the thermal efficiency deteriorates without recalibration. One open-loop control method and one closed-loop control method based on cylinder pressure sensor are proposed to deal with the fuel accommodation control problems. The open-loop control method features fuel blend ratio detection, which is a new dimension of input for the conventional MAP based engine management system. Gasoline and diesel blend ratio detection methods are studied, and the result also provides information for the closed loop control method as a feedforward controller. An indicated mean effective pressure based method is proposed for the engine brake torque difference problem, and a feedback controller with indicated mean effective pressure maximum seeking algorithm is used to optimize engine efficiency. The fuel injection amount and timing will be adjusted according to the fuel estimation result and the feedback control algorithms. Results show that the methods proposed could identify fuel blend ratio quite accurately, the engine brake torque output could follow the target value well, and the engine thermal efficiency could be optimized. [ABSTRACT FROM AUTHOR]

In beam geometries where a directed γ -ray beam hits the surface of a coaxial high purity germanium detector (HPGe), the detector efficiency is sensitive to the position where γ -rays initially hit the detector surface because the structure of the detector is nonuniform. This may cause inaccuracy of the detector efficiency when measured using standard sources that are point-like sources emitting γ -rays isotropically. Obtaining a precise estimation of the full energy peak efficiency of the coaxial HPGe detector in the beam geometry for on-axis and off-axis measurements requires a Monte Carlo simulation. We performed Monte Carlo simulations that calculate the detector efficiency in the beam geometry. The effects of the off-axis distance and γ -ray beam size on the efficiency are quantitatively analyzed. We found that the intrinsic efficiency in the beam geometry is maximized when the beam hits the detector at specific off-axis distances. Our Monte Carlo calculations have been supported by nuclear resonance fluorescence experiments using laser Compton scattering γ -ray beams. • Calculating efficiency of coaxial HPGe detector for directed γ-ray beams by Geant4. • Revealing the sensitivity of efficiency to γ-ray beam size and off-axis distance. • Off-axis efficiency is higher than on-axis efficiency, depending on γ-ray energy. • Maximizing efficiency by selecting the optimum off-axis distance. • LCS γ-ray beams up to 3 MeV validate calculations experimentally. [ABSTRACT FROM AUTHOR]

Accurate modeling of ocean wave energy converters is limited mainly due to the reciprocating nature of the exciting force and consequent complications, particularly in the fluid domain. Direct simulation is usually computationally expensive, and experiments are constrained by scaling rules that cannot be satisfied simultaneously, and of course, by the costs. Many modeling problems, including several in ocean wave energy, can be divided into sub-domains that for each, one modeling scheme (e.g. numerical simulation or experiment) is practical and preferred. The idea behind hybrid simulation is to solve each sub-domain using the preferred method, while sub-domains communicate with each other at their common boundaries via sensors and actuators, with the prime objective of solving the main problem as a whole. We are particularly interested in the set of problems in which the subdomains are strongly coupled and hence significantly influence each other. The challenge is when one of the subproblems is to be modeled experimentally and therefore as a result the entire hybrid simulation modeling has to be carried out in real time. We review here the background and details of the real time hybrid simulation scheme with the specific focus on the modeling of ocean wave energy devices. We elaborate major challenges via a case study of a newly proposed seabed mounted pressure-differential wave energy converter called “Wave Carpet”. We find the optimum parameters of the power takeoff units as well as their optimal positioning in order to achieve the highest overall efficiency of the Wave Carpet. [ABSTRACT FROM AUTHOR]

This paper revises the design process for closed-loop combustion control based on in-cycle feedback. Methods for the necessary observers, detectors and virtual sensors are also discussed. The control problem tackles the indicated efficiency optimization, following two approaches, direct and indirect optimization. The argumentation provides a comprehensive overview on how to specify and integrate different methods available at the literature. The results presented are based on previous experimental and simulation work on a Scania D13 engine by the authors. A pilot and main injection scheme is used to increase the degrees of freedom and achieve a higher nominal indicated efficiency. An in-cycle controllability study indicated that the pilot mass is the most significant parameter to monitor for the in-cycle disturbance rejection. Based on the heat release analysis, feedback is obtained from the pilot mass estimation, with a real-time accuracy of ± 0. 5 mg/st. Still, to overcome the inherent delay between feedback and control action, predictive models are necessary. The required accuracy can be obtained by the multi-cylinder adaptation of the model parameters. The paper presents two approaches for the design of in-cycle controllers to improve the indicated efficiency under hardware and emission constraints. In the direct efficiency optimization, a model predicts the indicated efficiency change from the in-cycle pilot estimations to optimize the main fuel injection. Compared to in-cycle open-loop operation, the in-cycle controller increases the indicated efficiency by + 0. 42 %unit. In the indirect efficiency optimization, the controller is designed to reduced the cyclic dispersion of the pilot SOC (down to ± 0. 4 C A D), the pilot burnt mass (down to ± 0. 6 mg), the main SOC (down to ± 0. 3 C A D) and the IMEP (down to ± 0. 2 bar). In case pilot misfire is detected, the CA50 shift of + 2. 6 C A D is compensated and reduced to + 0. 5 C A D. The indicated efficiency is maximized by the set-point optimization in a Monte Carlo simulation of a stochastic combustion model that captures the reduced cyclic dispersion of the controller. This approach increased the indicated efficiency by +0.6% unit under constraints on the maximum pressure, the maximum pressure rise rate, the maximum and the minimum exhaust temperature. Despite the controller effectiveness was quantified experimentally, the simulation results must be validated experimentally as well. Further investigations can focus on including constraints on emissions, how to handle the constraints on-line, the inclusion of additional injection pulses in the optimization, as well as variable valve timing actuation or injection of emissions reductants. [Display omitted] • Direct efficiency optimization controller increases efficiency by +0.42%. • Indirect efficiency constrained optimization controller increases efficiency by +0.6%. • In-cycle feedback by pilot combustion detection and combusted mass estimation. • Direct optimization based on an equivalent mixed-cycle simplification. • Indirect efficiency improvement by the 25% to 75% reduced cyclic dispersion by MPC. [ABSTRACT FROM AUTHOR]

Improving technological innovation efficiency and eco-efficiency is the key to achieving a high-quality, sustainable mining industry in China. In order to explore the internal process of technological innovation to promote economic and environmental benefits and to clarify the optimization path to improve the overall efficiency of the mining industry. A two-stage DEA model is used to construct indicators to measure Chinese 30 provinces mining technological innovation efficiency (MTIE), mining eco-efficiency (MEE), and mining comprehensive efficiency (MCE). Because of the lag in innovation, the study period was divided into nine periods from 2008 to 2018 into three-year time slices, and the dynamic evolution of time and space was analyzed. It was found that: (i) MCE and MTIE maintained the same changing trends, with the MCE being generally higher in areas with higher levels of mining economic development; (ii) the MTIE and MEE in the western area were higher than in the other regions, of which Qinghai was the only province that had efficiencies of more than 1 in both stages; (iii) most provinces belonged to type II regions with high MEE-low MTIE or type III regions with low MEE-low MTIE. The scientific achievements output in the first stage was generally insufficient, and the inputs and outputs in the second stage were redundant. There are three paths to optimize efficiency: unilateral optimization, gradual optimization, and jumping optimization. Finally, based on the above findings, policy recommendations are given from three aspects; reducing excess capacity, increasing investment, and building a platform, all of which can provide optimized plans and references for realizing the high-quality development of the Chinese mining industry. • A two-stage DEA model for measuring Chinese MTIE, MEE, and MCE from 2008 to 2018. • The MTIE and MEE in the western area were higher than in the other regions. • Most provinces belonged to type II or type III. • Three optimization paths are proposed to improve MCE. [ABSTRACT FROM AUTHOR]

Abstract: In this work, the authors present a 7.5% efficient hybrid tandem solar cell with the bottom cell made of amorphous silicon and a Si-PCPDTBT:PC70BM bulk heterojunction top cell. Loss-free recombination contacts were realized by combing Al-doped ZnO with either the conducting polymer composite PEDOT:PSS or with a bilayer of ultrathin Al and MoO3. Optimization of these contacts results in tandem cells with high fill factors of 70% and an open circuit voltage close to the sum of those of the sub-cells. This is the best efficiency reported for this type of hybrid tandem cell so far. Optical and electrical device modeling suggests that the efficiency can be increased to ~12% on combining a donor polymer with suitable absorption onset with PCBM. We also describe proof-of-principle studies employing light trapping in hybrid tandem solar cells, suggesting that this device architecture has the potential to achieve efficiencies well above 12%. [Copyright &y& Elsevier]

Abstract: The design of a new controller for the variator in a pushbelt continuously variable transmission (CVT) is investigated. A conventional variator controller is typically based on a variator model with large uncertainties, which results in a limited variator efficiency. The proposed controller simultaneously optimizes the variator efficiency and tracks a transmission ratio reference, for which a detailed variator model is not required. The controller, a combination of extremum seeking control and tracking control, only uses measurements from standard sensors. Experiments on the basis of a driving cycle show that a conventional variator controller is outperformed. [Copyright &y& Elsevier]

Abstract: Hybrid power systems with dc distribution are being considered for commercial marine vessels to comply with new stringent environmental regulations, and to achieve higher fuel economy. In this paper, detailed efficiency analysis of a shipboard dc hybrid power system is carried out. An optimization algorithm is proposed to minimize fuel consumption under various loading conditions. The studied system includes diesel engines, synchronous generator–rectifier units, a full-bridge bidirectional converter, and a Li-Ion battery bank as energy storage. In order to evaluate potential fuel saving provided by such a system, an online optimization strategy for fuel consumption is implemented. An Offshore Support Vessel (OSV) is simulated over different operating modes using the online control strategy. The resulted consumed fuel in the simulation is compared to that of a conventional ac power system, and also a dc power system without energy storage. The results show that while the dc system without energy storage provides noticeable fuel saving compared to the conventional ac system, optimal utilization of the energy storage in the dc system results in twice as much fuel saving. [Copyright &y& Elsevier]

Abstract: Production planning is an elementary aspect of supply chain management and requires appropriate and effective tools. The purpose of this paper is to present the concept, design, and implementation of a software prototype for production planning that incorporates aspects of the Constant Work-In-Process (ConWIP) manufacturing system. In introductory sections, essential knowledge about fundamental strategies of production planning and the concept of ConWIP are subsumed. After a brief illustration of the manufacturing process in the company for which this work has been conducted, various aspects of the actual software implementation are presented. The paper concludes with a discussion about potentials and limitations of the solution. [Copyright &y& Elsevier]

Abstract: The growing demand of energy coupled with an increasing attention to the environmental impact have forced, in the last decades, toward the study and the development of new strategies in order to reduce primary energy consumptions. The cogeneration (CHP) and the on-site generation (also known as distributed generation) could be the key strategy to achieve this goal; CHP systems allow to reduce the fuel consumption and pollutant emissions (in particular the greenhouse gases) compared to separate generation; moreover on-site-generation contributes to the reduction of the energy which is lost in electricity transmission, and increases the security in the energy supply. In this scenario the Thermo–Photo–Voltaic generation (TPV) is obtaining an increasing attention; TPV is a system to convert into electrical energy the radiation emitted from an artificial heat source (i.e. the combustion of fuel) by the use of photovoltaic cells. A domestic gas furnace based on this technology can provide the entire thermal need of an apartment and can also contributes to satisfy the electrical demand. In this paper, the main research activities on thermophotovoltaic generation developed in the last years at Institute of Materials for Electronics and Magnetism (IMEM) of Italian National Research Council (CNR), of will be presented and discussed. [Copyright &y& Elsevier]

Abstract: This paper presents an automatic calibration procedure that permits to industrial or domestic microwaves ovens working at optimal energetic efficiency conditions. This method is based on a low-power iterative measurement of the microwave oven scattering parameters for several sample locations to find the most efficient position by measuring energy reflections at feeding ports and the coupling between them for each sample position. These low-power measurements have been validated through high-power microwave-heating tests showing that, at the optimal estimated position, microwave absorption and therefore temperature increment is maximum. The method provides good matching levels independently of the sample geometry and permittivity without the need of any external matching device. [Copyright &y& Elsevier]

In this study, the continuous microwave production of (Pr, Zr)SiO 2 and (Ti, Sb, Cr)O 2 pigments was modelled. The mathematical model includes a two-way coupling between the Maxwell's equations and the heat equation as well as the coupling between the thermal and the chemical interfaces. The COMSOL Multiphysics software was used together with a specially designed MATLAB controller developed to automatically manage the input power and the cavity impedance. A single-mode cavity operating at 2.45 GHz, together with a rectangular waveguide, was used. A chemical model using experimental data was implemented using a model-fitting approach to predict the chemical conversion with time. Results show that the model-fitting method yields a good agreement with the experimental data. Attenuation occurs significantly within the material as the dielectric properties have high values. As such, prohibitive temperatures can be attained easily, although this was taken into account by the developed controller to manage the input power properly. The electromagnetic efficiency is highly dependent on the thermal field, making the boundary convection coefficient the parameter that affects the most the electromagnetic heating performance. A parametric study, that includes the variation of velocity and convection coefficient, was performed to access the impact of these variables in the efficiency of the process. The results show that increasing the velocity leads to a reduction of the maximum temperature, improving the electromagnetic efficiency. Moreover, the green-house gas specific emissions are lower when compared to the conventional process. The thermal conductivity is also a crucial parameter that can contribute to the electric field attenuation and the superficial heating. [Display omitted] • Multi-physics model solves chemical, energy and electromagnetic equations. • Exothermic chemical models are validated for two specific ceramic pigments. • The developed control algorithm adjusts the plunger position for the highest energy efficiency. • Automatic procedure obtains converged solutions with a complete chemical conversion. • With microwave technology GHG emissions can be reduced 75% in France and 98% in Sweden. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with an on-line optimum-efficiency control of a synchronous reluctance motor drive. The input power minimization control is implemented with a search controller using Fibonacci search algorithm. It searches the optimal reference value of the d-axis stator current for which the input power is minimum. The input power is calculated from the measured dc-bus current and dc-bus voltage of the inverter. A rotor-oriented vector control of the synchronous reluctance machine with the optimization efficiency controller is achieved with a DSP board (TMS302C31). Experimental results are presented to validate the proposed control methods. It is shown that stability problems can appear during the search process. [Copyright &y& Elsevier]

Abstract: The influence of the thermal heterogeneity of HPLC columns on retention data was investigated. The retention factor of the retained compound phenol was measured at 24 increasing values of the flow rate, from 0.025 to 4.9 mL/min, on six different packing materials prepared with the same batch of silica particles (5  m diameter, 90 Å pore size). One column was packed with the neat silica particles, another with the silica endcapped with trimethylchlorosilane (TMS)(C1, 3.92  mol/m2), and the other four with silica first derivatized with octadecyl-dimethyl-chlorosilane (C18, 0.42, 1.01, 2.03, and 3.15  mol/m2), and second endcapped with TMS. Four different sources of heat contributing to raise the column temperature were considered: (1) the heat supplied by the hot high-pressure pump chamber to the solvent; (2) the adiabatic () compression of the solvent in the high-pressure pump; (3) the isenthalpic () decompression of the solvent during its migration along the porous chromatographic bed; and (4) the heat released by the friction of the solvent percolating through the column bed. The main contributions appear to be the heat supplied to the solvent by the HP pump and the friction heat. The average column temperature (ACT) was indirectly derived from the measurements of the first moment, , of phenol peak, of the column pressure drop, , and of the retention factors of the phenol peak apices as a function of the flow rate applied. If the column is placed in a still-air bath at 298 K (and its temperature is not externally controlled), a longitudinal temperature gradient is established along the column and the average column temperature is about 6 K higher when this column is operated at 4.9 mL/min than when the flow rate is only 0.025 mL/min. If the column is placed in a heated air bath (temperature controlled at 316 or 338 K), the ACT changes by less than 3 K over the whole flow rate range applied. [Copyright &y& Elsevier]

A simplified model has been formulated in order to easily and adequately determines the efficiency of a solid oxide fuel cell (SOFC) stack system, independently on the fuel choice. Simple analytical formulas for the calculation of electromotive force (emf) generated in a SOFC system as well as for the estimation of its efficiency are proposed. It was found that both emf and efficiency are functions of the amount of carbon atoms of the fuel (oxygenated or not) as well as of the operational temperature. The steam to fuel molar ratio, defined as reforming factor, m, for each fuel and temperature has been adjusted to be low enough so as to ensure optimal conditions in the SOFC operation but high enough to avoid carbon formation within the cell. It has been also demonstrated that the efficiency values predicted by the model are of low relative difference compared with the numerical ones and, therefore, the approach presented here can be considered as sufficient enough for practical use. [Copyright &y& Elsevier]

In this work, we propose the use of a genetic algorithm (GA) for the determination of the optimal fraction of mass flow rate to be extracted from each stage of the turbines of a typical pressurized-water reactor (PWR) secondary side, in order to increase cycle efficiency. Here, we show some preliminary results obtained in a case study in which the PEPSE® system was used as simulation tool. [Copyright &y& Elsevier]

The condition of optimal efficiency in the energy transformation of a massive Brownian particle, moving in an asymmetric potential and subject to an external driving force, is studied by direct simulation of the stochastic differential equations. We analyze the behavior of the stationary averaged current and, at the same time, the energetic efficiency is evaluated. We found that the current exhibits several reversals when plotted as a function of the mass, and that it can be optimized at a particular value of the temperature. The condition to achieve an optimal efficiency is found, relating the mass, temperature and friction to the properties of the ratchet potential. [Copyright &y& Elsevier]

The fundamental requirement of carbon abatement is to complete the carbon abatement task set, at the lowest cost. In this paper, the non-radial distance function method is used to calculate the marginal carbon abatement costs of each unit, and the statistical method is used to estimate the carbon abatement efficiency of each unit. Based on the sum of dynamic carbon abatement costs in each province, the carbon abatement task allocation is optimized, and the data before and after optimization is compared and analyzed. The main conclusions are as follows: (1) The function of carbon abatement efficiency can be estimated using the marginal cost of carbon abatement, by which, the carbon abatement cost of each province can be calculated. (2) The correlation between carbon emissions and carbon abatement efficiency of each province is weak, so the overall carbon abatement efficiency of China is low. (3) Optimizing the allocation of provincial carbon abatement tasks can significantly reduce the total carbon abatement cost and improve the carbon abatement efficiency. This study has significant theoretical and practical value for improving China's overall carbon abatement efficiency, and establishing the provincial initial carbon emission quota. [Display omitted] • We estimate carbon abatement efficiency of China and its provinces. • We improve the method for carbon abatement efficiency using the dynamic data. • We fill a gap in research on carbon abatement efficiency based task allocation method. [ABSTRACT FROM AUTHOR]

• Highly efficient operation with multiple energy buffer devices. • A minimum loss model proposed for multiple energy storage units. • An efficient strategy achieving the minimum loss in real-time scale. • A power allocation strategy for better extending the lifetime of battery. Energy router with energy buffer will significantly facilitate performance improvement such as loss compensation, and instruction implementation of dispatching center in Energy Internet. To achieve high power density, high energy density, and high reliability, the energy buffer is implemented via a hybrid energy storage system and paralleled multiple modules. A minimum loss model of energy buffer devices is constructed to optimize the operating efficiency and energy management of multiple energy storage units. Based on the minimum loss model, a rule-based energy buffer strategy for the energy router is proposed to achieve minimum loss and energy management in real-time control. A novel power allocation method for different types of storage units is designed to better eliminate over-limit power in energy-type storage units in peak periods, thus extending their lifetime. Simulation results demonstrate the effectiveness of the proposed rule-based energy buffer strategy for energy routers in achieving highly efficient and seamless operation and energy management of energy storage units. [ABSTRACT FROM AUTHOR]

• Modelling the overall system efficiency of PEM water electrolyzers. • PEM water electrolysis efficiency can be significantly improved by temperature optimization. • Optimal temperature depends on the applied cell voltage. • Safety issue caused by hydrogen crossover is prevented by temperature optimization. Most of the hydrogen produced today is made using fossil fuels, making a significant contribution to global CO 2 emissions. Although polymer electrolyte membrane water-electrolyzers can produce green hydrogen by means of excess electricity generated from renewable energy sources, their operation is still not economical. According to industry experts, the necessary cost reductions can be achieved by 2030 if system efficiency can be improved. The commonly stated idea is to improve efficiency by increasing the stack temperature, which requires the development of more resistant materials. This study investigates not only the efficiency of an electrolysis cell, but of the entire electrolysis process, including gas compression of hydrogen. The results indicate that an optimal stack temperature exists for every operating point. It is shown that the optimal temperature depends solely on the electrode pressure and cell voltage and can be analytically calculated. In addition, the temperature optimization leads to significantly reduced hydrogen permeation at low current densities. In combination with the pressure optimization, the challenging safety issues of pressurized electrolysis can be eliminated for the entire load range and, at the same time, the efficiency of the overall system be maximized. [ABSTRACT FROM AUTHOR]

Intermediate-band solar cells, IBSCs, with single IB provide better utilization of the solar spectrum than single junction solar cells. In this study, Model − B IBSC was proposed, investigated and compared with previously used two models named here as Model − A and Model − C respectively. Detailed Balance Model was applied to satisfy Current Balance Equations with the optimum photo filling of IB states in Model − B. Optimum design parameters were obtained using 104 cm−1 of band-to-band absorption coefficient, α , in the wide range of band gap materials, overlapping absorption, photo filling, f , of IB states, capture cross-section ratio of carriers, concentration of IB states, and IB layer thickness, w , under 1–46,000 sun concentration, X. Maximum limiting efficiency value of 63.2% has been obtained with 1.95 eV of band gap, for f α w ≥ 5 and 46,000 X , under non-overlapping absorption. The peak efficiency of Model − B was 16% over the Model − A and 8% over the Model − C , for equal capture cross sections under large overlapping. The peak efficiency of Model − B was 35% over Model − A , at large non-equal capture cross-sections and large overlapping. Results predicted that the materials in the wide range of band gaps could be good candidates for fabricating IBSCs using Model − B with an efficiency of 50% or above at lower sun concentration, 10,000 X , even under large overlapping. [ABSTRACT FROM AUTHOR]

• Optimization of power, durability, and performance of PV modules for desert areas. • 9.58% gain in efficiency by proper choice of materials and module design. • Encapsulant suggestions to reduce UV degradation on front and rear side of PV cells. • Reduction of cell movement due to the temperature cycles and risk of tab breakage. • Up to 35% reduced soiling losses by using a new anti-soiling coating. The global share of photovoltaic plants in desert locations increases continuously due to inexpensive land and higher yield due to higher irradiation levels. However, PV modules suffer from harsh environmental conditions that influence their lifetime and, consequently, the levelized cost of electricity. Environmental factors such as high temperature differences between nights and days, high ultraviolet doses, high ambient temperatures, and high airborne dust lead to durability and performance issues such as delamination, discoloration, fatigue of interconnection, breakage of solar cells, hot-spots, and power loss due to the soiling. In this work, different bills of materials and module designs are evaluated, targeting optimum PV output power while increasing the service life and performance of the PV modules in desert climates. A stepwise optimization of module components (solar cells, glass coating and polymers/encapsulation) and module design (full vs. half cells, tab widths) are performed by simulation and experimental approaches. Simulations results analyzes the loss mechanisms and electricity production of PV modules by considering the impact of module material and design Experimentally, ultraviolet stress tests and thermal cycling tests are performed for polymer durability and interconnection fatigue analysis. The soiling reduction potential of a newly developed glass coating is investigated by outdoor exposure tests in Saudi-Arabia. It is shown by proper choice of materials and optimized interconnection design, the efficiency of the module is increased by 9.58% rel. relative to the reference module. Furthermore, the choice of encapsulant and module design strongly affect the expected service-life, and soiling losses could be reduced up to 35%. [ABSTRACT FROM AUTHOR]

• A model has been developed to simulate CO 2 reforming of methane in reactors. • Our model is more accurate than the laminar finite-rate model in the reference. • A 10% increase in the energy efficiency is achieved with an optimization study. In CO 2 reforming of methane solar thermochemical energy storage, much research has been conducted to enhance the thermochemical performance of the reactor. However, there has been little research conducted to investigate the effects of dimensions on the reactor thermochemical performance. Moreover, little innovation has occurred on optimizing reactor dimensions and operating conditions simultaneously. In this paper, a model has been developed to simulate CO 2 reforming of methane reaction in a tubular packed reactor. By comparing with experimental and simulation data from another publication, the model is validated to be more accurate. A parametric study has been performed to investigate the effects of dimensions and operating conditions on the reactor thermochemical conversion and energy storage efficiency. The result shows that there is a trade-off between achieving a higher energy storage efficiency and decreasing the conversion by having smaller reactor with larger gas flow rate. An optimization study of all the design parameters, based on the reaction model coupled with a multistart optimization algorithm, is performed to find the maximum energy storage efficiency for a fixed required conversion. Without sacrificing the conversion, an energy storage efficiency of 0.77, which is 10% higher than the highest established experimental data, is obtained through optimization. The study provides a baseline for further thermodynamic analysis of the entire system. [ABSTRACT FROM AUTHOR]

This paper presents a novel control technique to efficiently supply a wide range of output load current in a buck converter using an adaptive pass device at the output stage. The adaptive pass device segment size control technique is based on equalization of capacitive power loss and resistive power loss terms by taking into account load current, input supply voltage, temperature, process, and aging conditions; thus, leading to optimum efficiency at the output stage in a broad operating region. Power calculations are done in analog domain using a novel arithmetic cell called the adaptive g m stage. The additional power consumption introduced by the power calculation blocks is less than 1.4 μA, which enables high efficiency operation even in low load currents. The circuit and layout are designed in a standard 130 nm CMOS technology and simulation results show 5–35% efficiency increase for mid/low load currents compared to a fixed output stage buck converter. Compared to other reported adaptive pass device buck converters, 4% increase in peak power efficiency with 3× broader load current range has been achieved. [ABSTRACT FROM AUTHOR]

This paper aims to improve the performances of a self-rectifying radial impulse turbine used in wave energy conversion. The turbine design involves blades of circular profiles. The Design of Experiments method has been implemented for the efficiency optimization. The objective function aims to maximize the average turbine efficiency between the inhalation and the exhalation modes. A 3D viscous flow modelling has been performed with the ANSYS Fluent code. Simulations allow the turbine efficiency computation accordingly to the changes in the turbine geometry. Influence of ten geometrical parameters has been considered in the optimization process. According to a confidence degree of 95%, it has been found that only four of them have significant influence on the turbine efficiency. The rotor geometry admits the highest influence, particularly the blade angle. Additional analysis has been conducted by considering the rotor blade stagger angle. It has been found that the efficiency can be kept high in the both modes with a stagger angle of 4°. Efficiencies more than 50% have been reached. The present turbine efficiency has been compared to that of a turbine of elliptical profiles. An increase of about 19% in the efficiency has been reached with the present turbine. • Efficiency improvement of a self-rectifying impulse turbine used in OWC system. • Use of a circular profile in the design of a self-rectifying impulse turbine. • Design of Experiments (DOE) method in the turbine geometry optimization. • Effect of the rotor stagger angle on the turbine efficiency. • Comparison of performances between turbines designed with circular and elliptical profiles. [ABSTRACT FROM AUTHOR]