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The COVID-19 pandemic has caused fluctuations in electricity demand, altering people's lifestyles and electricity usage patterns, thereby affecting the accuracy of demand predictions. However, existing studies on electricity forecasting have not adequately considered the incorporation of COVID-19-related features and the analysis of electricity usage characteristics across different regions of the UK. Therefore, this paper, based on data of the UK's national electricity demand, conducts an analysis around the scenario of a large-scale health emergency in society. We explore the changing patterns and regional characteristics of electricity consumption during the COVID-19 pandemic, comparing the forecast results before and during the pandemic to illustrate its impact on the UK's electricity demand. By introducing COVID-19-related features into the models, we compare the forecast results before and after their inclusion. The results indicate that the COVID-19 pandemic has had a certain impact on the electricity prediction in the UK, leading to a 22.8% decrease in prediction accuracy. However, the models' correlation improved with the inclusion of COVID-19-related features, resulting in a 13.2% enhancement in prediction accuracy compared to the previous models. Additionally, the study summarizes other factors influencing electricity demand, such as power imports/exports and clean energy usage, as considerations for electricity distribution planning. This contributes to improving the accuracy of predicting the UK's electricity demand during COVID-19 pandemic, enabling the government to adjust power dispatching plans reasonably based on relevant factors, achieving rational distribution and efficient scheduling of power resources. [ABSTRACT FROM AUTHOR]

Objective: This study's objective was to estimate hearing loss prevalence for noise-exposed US Utilities workers. Methods: In this cross-sectional study of a retrospective cohort, audiograms were examined for 1.3 million workers (13,595 within utilities) from 2010-2019. Hearing loss prevalence and adjusted risk as compared with a reference industry were estimated. Results: The hearing loss prevalence for noise-exposed Utilities workers (25%) was higher than for noise-exposed workers in all industries combined (20%). Some subsectors surpassed the prevalence for all industries combined and/or had adjusted risks significantly higher than the reference industry. The highest prevalence subsectors were Hydroelectric Power Generation (37%) and steam and Air-Conditioning Supply (29%). Conclusions: While often overlooked, noise-exposed workers in this sector have among the highest prevalences of hearing loss and significantly higher risks. Increased attention and better hearing conservation strategies are needed. [ABSTRACT FROM AUTHOR]

The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and the port loads with large fluctuations and fast changes. These factors can easily lead to the problem of the state of charge exceeding the limit of the energy storage system. To distribute the fluctuating power in the green port multi-energy microgrid system reasonably and maintain the state of charge (SOC) of the hybrid energy storage system in an moderate range, an energy management strategy (EMS) based on dual-stage fuzzy control with a low pass-filter algorithm is proposed in this paper. First, the mathematical model of a green port multi-energy microgrid system is established. Then, fuzzy rules are designed, and the dual-stage fuzzy controller is used to change the time constant of the low-pass filter (LPF) and modify the initial power distribution by an LPF algorithm. Finally, simulation models are built in Matlab 2016a/Simulink. The simulation results demonstrate that, compared with other algorithms under the control of the EMS proposed in this paper, the high-frequency component in the flywheel power is smaller, and the SOC of the supercapacitor is maintained in a reasonable range of 34–78%, which extends the lifespan of the flywheel and supercapacitor. Additionally, it has a faster automatic adjustment ability for the state of charge of the energy storage system, which is conducive to better maintaining the stable operation of green port multi-energy microgrid systems. [ABSTRACT FROM AUTHOR]

We introduce a novel technique for producing several families of distributions: the alpha-log-power transformed method. The novelty of our new approach lies in the fact that it adds one new shape parameter and was not derived from any established parent model. Some examples of the new family are presented. Also, some important statistical properties of the new family are studied. The maximum likelihood estimation approach is utilized to estimate the model parameters of the new family. To evaluate the performance of the estimators, Monte Carlo simulation is conducted using some arbitrary baseline distributions namely the Weibull, Burr-XII and Pareto distribution. Two real datasets are used to empirically show the potential significance and applicability of the alpha log power transformed Weibull. The alpha log power transformed Weibull is a very competitive model for characterizing observations in survival analysis. [ABSTRACT FROM AUTHOR]

Urban air mobility (UAM) represents a promising solution for alleviating contemporary ground traffic congestion challenges. Consequently, a comprehensive analysis of power system operational characteristics within typical flight mission profiles for flying cars is of utmost importance. Due to constraints associated with battery energy density and the limited range of all-electric flying cars, the adoption of an oil-electric hybrid power system for flying cars is a more pragmatic choice. An overview of pertinent research concerning the operational performance of hybrid systems in vertical takeoff and landing ( VTOL) vehicles was provided. Utilizing MATLAB Simulink, a hybrid power coordination method was proposed that accounted for both operational modes. Distinct operational modes were predefined in accordance with actual operational conditions, encompassing vertical take-off and landing as well as level flight scenarios. Building upon this foundation, the coordination of the battery was explored, serving as the primary power source, to regulate power flow and enhance the efficiency of the range extender. The DC bus voltage was subject to regulation through a DC/ DC converter. To promote the overall longevity of the battery pack, power sharing mechanisms were introduced during both charging and discharging phases. Simulation results underscore the proficient control of the DC bus voltage, and power distribution between the range extender and the battery aligns with the predetermined design parameters. [ABSTRACT FROM AUTHOR]

This paper introduces a novel metaheuristic technique, a COOT‐based algorithm, to determine the optimal Distributed Generation (DG) allocation within a loop‐configured network. This method significantly narrows the optimization gap by leveraging a COOT‐based algorithm, ensuring accelerated convergence and resultant global optima. The core incentive for employing this technique is to substantially mitigate power loss, curtail voltage deviation, and bolster system stability in a loop distribution network. To attain optimal outcomes, the elaborated COOT and improved grey wolf optimization improved grey wolf optimization (IGWO) algorithms were executed on IEEE bus‐33 and 69 mesh distribution networks (MDNs) under varying power factors. The derived mathematical results effectively underscore accomplishing the stipulated objectives: a marked reduction in voltage deviation and power loss coupled with an augmentation in system stability. Notably, at unity, incorporating DGs resulted in a paramount reduction in power loss, attaining a decrease of 78% and 85% for bus‐33 and 69 MDNs, respectively. Moreover, an impressive decrease in power loss by 94% and 98% was observed at the optimal power factor for both MDNs. A comparative evaluation of the results accentuates that the proposed COOT and IGWO algorithms eclipse other documented research in performance, showcasing superior efficiency on a techno‐economic basis. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates the reliability of commonly utilized digital spiking neurons and the potential side-channel vulnerabilities in neuromorphic systems that employ them. Through our experiments, we have successfully decoded the parametric information of Izhikevich and leaky integrate-and-fire (LIF) neuron-based spiking neural networks (SNNs) using differential power analysis. Furthermore, we have demonstrated the practical application of extracted information from the 92% accurate pretrained standard spiking convolution neural network classifier on the FashionMNIST dataset. These findings highlight the potential dangers of utilizing internal information for side-channel and denial-of-service attacks, even when using the usual input as the attack vector. [ABSTRACT FROM AUTHOR]

Abstract This paper introduces a novel metaheuristic technique, a COOT‐based algorithm, to determine the optimal Distributed Generation (DG) allocation within a loop‐configured network. This method significantly narrows the optimization gap by leveraging a COOT‐based algorithm, ensuring accelerated convergence and resultant global optima. The core incentive for employing this technique is to substantially mitigate power loss, curtail voltage deviation, and bolster system stability in a loop distribution network. To attain optimal outcomes, the elaborated COOT and improved grey wolf optimization improved grey wolf optimization (IGWO) algorithms were executed on IEEE bus‐33 and 69 mesh distribution networks (MDNs) under varying power factors. The derived mathematical results effectively underscore accomplishing the stipulated objectives: a marked reduction in voltage deviation and power loss coupled with an augmentation in system stability. Notably, at unity, incorporating DGs resulted in a paramount reduction in power loss, attaining a decrease of 78% and 85% for bus‐33 and 69 MDNs, respectively. Moreover, an impressive decrease in power loss by 94% and 98% was observed at the optimal power factor for both MDNs. A comparative evaluation of the results accentuates that the proposed COOT and IGWO algorithms eclipse other documented research in performance, showcasing superior efficiency on a techno‐economic basis.

Abstract Cyber–physical distribution systems with renewable energy should have high resilience under extreme conditions. However, in a distribution system with deep cyber–physical coupling, the propagation of information risk impairs the resilience of the system. This paper proposes a strategy to improve the resilience of cyber–physical distribution systems that considers cross‐space propagation of information risk. First, the mechanism for interaction between the cyber space and physical space is analyzed, and an information risk cross‐space propagation model is proposed. Second, the risk status of key device nodes is quantified according to the risk propagation model, and an optimization strategy for information risk control is obtained, whose objective function is the minimum risk of the coupling network. Third, a fault restoration strategy that considers cyber space risk is proposed. Finally, the paper reports experiments using the modified IEEE 33‐node and 123‐node distribution networks to simulate the proposed strategy and verify its effectiveness.

Abstract Mixture distributions are naturally extra attractive to model the heterogeneous environment of processes in reliability analysis than simple probability models. This focus of the study is to develop and Bayesian inference on the 3-component mixture of power distributions. Under symmetric and asymmetric loss functions, the Bayes estimators and posterior risk using priors are derived. The presentation of Bayes estimators for various sample sizes and test termination time (a fact of time after that test is terminated) is examined in this article. To assess the performance of Bayes estimators in terms of posterior risks, a Monte Carlo simulation along with real data study is presented.

Abstract This study proposes an optimal approach for enhancing the quality of a weak electrical power distribution system by utilizing thyristor‐controlled series capacitors (TCSC). The proposed approach considers various system components, including shunt capacitors and distributed generators that rely on renewable energy sources, which are characterized by uncertainty due to changing weather conditions. The proposed system maximizes the benefits of these components by updating its parameters to improve the distribution power system's quality under all operating conditions, which change due to the varying energy generated by the distributed generators and load changes. The optimal TCSC values are calculated for all operating conditions using the Hyper‐Spherical Search with graded objective functions management strategy (HSSA‐GOFMS) algorithm. The GOFMS converts all restrictions into objective functions with limits and prioritizes the search for objectives according to a sequential system of priorities. This strategy prevents the possibility of non‐convergence. The results demonstrate the effectiveness of the proposed approach in improving the performance quality of a weak electrical distribution system. The proposed strategy achieves the target voltage level limits within nominal values, even with the interference of the system with generators distributed at variable power levels. Furthermore, the proposed approach enhances the performance quality of the system under a wide range of load changes.

Cyber–physical distribution systems with renewable energy should have high resilience under extreme conditions. However, in a distribution system with deep cyber–physical coupling, the propagation of information risk impairs the resilience of the system. This paper proposes a strategy to improve the resilience of cyber–physical distribution systems that considers cross‐space propagation of information risk. First, the mechanism for interaction between the cyber space and physical space is analyzed, and an information risk cross‐space propagation model is proposed. Second, the risk status of key device nodes is quantified according to the risk propagation model, and an optimization strategy for information risk control is obtained, whose objective function is the minimum risk of the coupling network. Third, a fault restoration strategy that considers cyber space risk is proposed. Finally, the paper reports experiments using the modified IEEE 33‐node and 123‐node distribution networks to simulate the proposed strategy and verify its effectiveness. [ABSTRACT FROM AUTHOR]

Wireless and power line communication hybrid relay technology can realize complementary advantages and comprehensively improve the communication coverage and performance of power Internet of Things. In order to study the mechanism of the physical layer and Media Access Control (MAC) layer algorithm that affects the performance of hybrid relay systems, the cross-layer performance modeling, optimization, and simulation analysis are carried out for the non-orthogonal multiple access (NOMA) technology. Firstly, a two-hop NOMA media access control protocol is designed based on the CSMA algorithm. Considering the effects of non-ideal channel transmission at the physical layer and competitive access at the MAC layer on the system performance, a cross-layer performance analysis model of hybrid wireless and power line communication relay system under NOMA is established. Finally, a cross-layer optimization model based on multi-objective programming is established for the hybrid relay system. By analyzing the relationship between transmitting power and performance index, the joint optimization of transmitting power and power distribution factor between users is realized. Simulation results verify the validity and reliability of the proposed cross-layer model. The results show that the hybrid relay algorithm combined with NOMA and CSMA can effectively improve the performance of the system throughput, packet loss probability, and delay. [ABSTRACT FROM AUTHOR]

The article presents the issues related to load-power sharing in direct-current grid and a novel control method has advantages over known solutions. Unlike many similar-sounding papers, this article shows an attempt at creating fully controllable non-isolated system that allows for load-power sharing between a permanent magnet alternator equipped with machine-side converter (MSC) and a dual active bridge (DAB) tied to batteries or supercapacitor. The current-based load-power sharing is an essential feature of parallel-connected direct-current generators, and all types of voltage sources, in this way are contributing power to the system. To keep the optimal efficiency of the alternator, the rotational speed changes rely on proper mapping of the driving combustion engine. System components include a self-excited synchronous generator (SESG), operating at variable shaft speed, as well as batteries and supercapacitors that provide electricity for sudden electrical-load changes on the distribution grid. The core of the presented system is in a power-distribution method that consists of a programmed-controller structure allowing precise current distribution. A novelty of the proposed method is the use of a cascaded system of current and DC voltage regulators that allows for precise power-distribution control. In contrast with previously presented solutions, the proposed system allows for fast and accurate control of currents, loading parallel-connected DC voltage sources for wide-range generator speed changes. In the presented solution, both converters have been equipped with Schottky diodes, preventing the flow of equalizing currents between closed transistors in the parallel mode of operation. An experimental test-stand of the described system is presented with its theoretical basis and experimental results. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In response to the challenges posed by the low energy utilization of single-power pure electric vehicles and the limited lifespan of power batteries, this study focuses on the development of a compound power system. This study constructs a composite power system, analyzes the coupling characteristics of multiple systems, and investigates the energy management and optimal control mechanisms. Firstly, a power transmission scheme is designed for a hybrid electric vehicle. Then, a multi-state model is established to assess the electric vehicle's performance under complex working conditions and explore how these conditions impact system coupling. Next, load power is redistributed using the Haar wavelet theory. The super capacitor is employed to stabilize chaotic and transient components in the required power, with low-frequency components serving as input variables for the controller. Further, power distribution is determined through the application of fuzzy logic theory. Input parameters include the system's power requirements, power battery status, and super capacitor state of charge. The result is the output of a composite power supply distribution factor. To fully exploit the composite power supply's potential and optimize the overall system performance, a global optimization control strategy using the dynamic programming algorithm is explored. The optimization objective is to minimize power loss within the composite power system, and the optimal control is calculated through interpolation using the interp function. Finally, a comparative simulation experiment is conducted under UDDS cycle conditions. The results show that the composite power system improved the battery discharge efficiency and reduced the number of discharge cycles and discharge current of the power battery. Under the cyclic working condition of 1369 s, the state of charge of the power battery in the hybrid power system decreases from 0.9 to 0.69, representing a 12.5% increase compared to the single power system. The peak current of the power battery in the hybrid power system decreases by approximately 20 A compared with that in the single power system. Based on dynamic programming optimization, the state of charge of the power battery decreases from 0.9 to 0.724. Compared with that of the single power system, the power consumption of the proposed system increases by 25%, that of the hybrid power fuzzy control system increases by 14.2%, and that of the vehicle decreases by 14.7% after dynamic programming optimization. The multimode energy shunt relationship is solved through efficient and reasonable energy management and optimization strategies. The performance and advantages of the composite energy storage system are fully utilized. This approach provides a new idea for the energy storage scheme of new energy vehicles. [ABSTRACT FROM AUTHOR]

As the quick advancement of urban rail transit, the power supply safety is gradually receiving attention. In the direct-current traction power supply system, the abnormal increase in rail potential is very significant, seriously affecting the regular working of the system. Therefore, to address the above issues, the mechanism of abnormal increase in rail potential is explored, and genetic algorithms are applied to optimize the power distribution of the system. The simulation results show that when the starting threshold is 1600 V, the highest value of the rail potential is only about 40 V, which is reduced by about 70 V compared to the other thresholds of 1800 V. When two trains are running in the system, as the travel time of Train 2 increases, the cross-zone transmission current gradually increases to around 1100 A. And the rail potential first decreases and then increases to over 90 V. It can be seen that the power distribution situation has a significant impact on the rail potential. After genetic algorithm optimization, the peak potential of the rail is only 66.2 V, with a decrease of 40.3%. The regenerative braking power allocated by the upstream regenerative braking train Cs1 to the accelerating train Cs2 decreases to 2703.5 kW, with a decrease of 35.6%. In addition, the regenerative braking power allocated by the Cx 1 regenerative train to the accelerated train Cx 2 is 2738.7 kW, which is at least 35.6% lower than before optimization. The above results indicate that the power distribution situation has a significant impact on the abnormal increase of rail potential. And optimizing the power distribution situation through genetic algorithm can effectively avoid the abnormal increase of rail potential.

When a diesel engine operates at non constant power output, it not only has low fuel efficiency but may also generate significant mechanical stress, leading to wear and damage of mechanical components. In order to ensure the efficient operation of diesels within diesel multiple units (DMU), this paper proposes a proportional-integral (PI) control approach based on the operational mode of the diesel generator sets featuring constant power output. This method was devised to steadily synchronize power of the traction systems on the load side with the target output power of the diesel generator sets. In turn, constant power operation on the load side guarantees a constant power output from the generator sets, thereby improving the fuel economy of the diesels. Through simulation and experimental tests, steady state fluctuations in load power were maintained within ±2%, demonstrating the effective constant power operation and the real-time alignment of load power with the target value.

Electric power distribution is a crucial element in meeting the needs of the community, especially in the workshop and electronic equipment repair sector. The transmission process aims to optimize efficiency and reduce power losses. PT PLN (Persero) UP2D SUMBAR has a high commitment in responding to the needs of the community, related to the distribution of electricity, especially in the 20 KV distribution network. Although it already uses two Early Warning Systems connected to SMART VU SCADA, the DCC room alarm sound is disabled to minimize noise. Therefore, this research focuses on implementing an additional Early Warning System with LED warning lights. The research methodology includes literature study, initial testing (Experimental Method), system design, hardware design, second testing (successful/unsuccessful), direct testing in the DCC room, and analysis of results. It is expected that this research can improve alarm notifications, speed up dispatcher response time, and increase vigilance in handling disturbances in the 20 KV distribution network.

Preventive tree pruning is an efficient way to reduce the risks of outages in the electrical network, such as cable rupture, short circuits, and fires, which may occur due to interferences between vegetation and urban electrical distribution lines. These interferences are listed as one of the main causes of power supply interruptions by distribution companies and, consequently, generate significant financial losses due to the decline in quality indicators and the need for maintenance. Vegetation management inspection is essential to maintain the reliability and continuity of the power distribution, but manual monitoring is expensive, time-consuming, and subjective. This paper proposes a new method based on Deep Learning (DL) and high-resolution sensors for automated vegetation inspection in urban power distribution lines. The method combines Light Detection and Ranging (LiDAR) and spherical images and overcomes the limitations of aerial images using vehicle-borne sensors. The dataset was obtained using the proposed capture system in four Brazilian cities. The results demonstrated the suitability of the proposed method in an innovative way through a proof of concept. Among the main contributions, the functional evaluation of the system for Artificial Intelligence-based real-time vegetation inspection in power line distribution is highlighted. The proposed method achieved high rates of interference identification using a web platform and mobile application (achieving a precision of over 94%). The results demonstrate the potential of the proposed approach for automated vegetation inspection in real-world scenarios and open up opportunities for the deployment and evaluation of large-scale applications.

In this paper, a method for power distribution control in communication-free multiple-input and multiple-output (MIMO) wireless power transfer (WPT) through load impedance and mutual inductance estimation is proposed. The proposed method intentionally adjusts the resonant frequency of the secondary side to introduce a reactance, utilizing this information to estimate the load impedance and mutual inductance for power distribution control without the need for communication. The principle of the power transmission algorithm proposed in this paper is designed to be effective regardless of whether the power or frequency is high or low. Therefore, the experimental setup is not designed by specifying the coil size, system frequency, or separation distance between the transmitting (Tx) and receiving (Rx) coils to match specific real applications. To verify the proposed method, four Tx coils and two Rx coils of arbitrary sizes are fabricated, and a MIMO-WPT environment is implemented using LC matching. In the experiment, since the circuit designed for the Tx is not capable of withstanding high currents, power is intentionally transmitted at a low range of less than 1 W to validate the feasibility of the method. Because the transmission power range is set low, the distance between the Tx and Rx coils is set close to approximately 2 cm. Consequently, it is verified that the algorithm for parameter estimation and power transmission to multiple Rx coils is effective as long as the environment allows for the current flowing through the Tx coil to change due to the presence of the Rx coils. All experiments for uniform and non-uniform power distribution to two Rx coils showed good agreement between the desired power and the actual received power.

Power distribution systems consist of critical infrastructure with various categories of assets that require rigorous maintenance programs to ensure their reliability and performance for all stakeholders. Maintenance program prioritization is essential, considering asset significance, failure likelihood, and consequences. This research presents a pioneering methodology for functional failure criticality assessment and control in power distribution systems. It uniquely combines NORSOK Z008 guidelines for functional failure identification of all types of assets and a multiple criteria decision-making tool named analytic hierarchy process (AHP) for prioritization of resources, and yearly budgets for the identified critical assets using asset failure analysis. This innovative approach addresses the shortcomings of existing methods by comprehensively enhancing cost-effectiveness, efficiency, and stakeholder decision-making, while adhering to industrial standards. The rationale stems from the necessity to bridge the gap between the theoretical frameworks and practical decision-making in infrastructure maintenance. By conducting a case study in a densely populated area of a developing nation, the study validates the effectiveness of the proposed approach in mitigating risks and improving system performance. The overarching goal of the research is to equip power distribution utilities with a robust toolset to optimize resource allocation, enhance system reliability, and ensure regulatory compliance. This strategic initiative aims to empower stakeholders with informed decision-making capabilities, ultimately fostering a safer, more reliable power distribution infrastructure that benefits both utilities and communities they serve.

A VVER-1000 reactor model using the Monte Carlo Serpent 2 code for core power distribution calculation is presented. The core and zones located near to the core were modeled in detail, without simplification. The assembly power distribution and axial power profiles were calculated for fresh core of the X2 VVER-1000 benchmark, namely the core of the KhNPP2 first loading for the hot zero power. The results were compared with the data obtained by specialists from Helmholtz-Zentrum Dresden-Rossendorf.

In order to achieve the Paris climate targets, the German government has developed phased plans and anchored these in an amendment to the Renewable Energy Sources Act (EEG). This not only defines expansion targets for renewable energy producers, but also the additional amounts of energy that must be available in the electricity grid in future if it is to supply the mobility and building heating sectors, which are currently still powered by fossil fuels. While the lack of grid transport capacities is recognized and discussed in the public debate, another known and critical hurdle is rarely presented here. This is the temporal distribution of power from renewable energies and its effects on the processes involved in controlling the grid balance. By analyzing a target scenario specified in the EEG for 2030 and another for 2040+, which a German economic research institute recommends to policymakers, the aim is to investigate whether their targets can be achieved under the conditions of the natural fluctuations occurring in Germany and the quantities of renewable energy that can be harvested with a reasonable use of resources. The focus is on simulating future generation curves using historical data in such a way that they show the typical weather-driven behaviour to be expected in Germany. Unavoidable Surplus generation is used as efficiently as possible with electricity and hydrogen storage systems. Both scenarios fall considerably short of their targets. CO2-free coverage of the demand specified for the long-term future is only possible with a quantity of generators that is at the limit of what is feasible. The reason for this is that the current plans are obviously based on an unrealistic picture of the temporal distribution of renewable energy output. Achieving the transformation goals in Germany could be much more complex than politicians currently believe and may require a change in strategy sooner or later. [ABSTRACT FROM AUTHOR]

In this article, we propose a new class of distributions defined by a quantile function, which is the sum of the quantile functions of the Power and Weibull distributions. Various distributional properties and reliability characteristics of the class are discussed. To examine the usefulness of the model, the model is applied to a real life datasets. Parameters are estimated using maximum likelihood estimation technique. [ABSTRACT FROM AUTHOR]

The power peaking factor (PPF) is an important parameter that needs to be considered to maintain the reactor's stability, safety and efficiency. The present study discusses the power density distribution in the reactor core by calculating the PPF to increase the reactor safety margin and minimize the possibility of a high power density at a certain point causing core failure in the Molten Salt Reactor (MSR), which is one of the Generation-IV reactors with fuel and coolant dissolved in molten salt. Important parameters discussed in the present study are the distribution of the reactor core region and the fuel composition in each region during the reactor operation time of 2,000 days. Analysis was performed for 3 different thermal power: 150, 450 and 1,000 MWth as a representative to determine the behavior of PPF at small to large power by taking the reference design of the FUJI U3 reactor developed by ITMSF (International Thorium Molten-Salt Forum) Japan. FliBe (Lithium and Beryllium Fluoride) is used as the coolant, and the fuel mixture is 233UF4-ThF4. The calculation was conducted using SRAC2006 with PIJ and CITATION modules that solve the neutron diffusion equation providing power distribution values and effective multiplication factors. As a result, the MSR with 4 core regions produces a more balanced power distribution, a better PPF value, and a good effective multiplication factor for 2,000 days of operation time compared to the reference design. [ABSTRACT FROM AUTHOR]

Agricultural machinery and equipment are indispensable to realize resource utilization for high efficiency in sustainable production. It is also required for the efficient, intelligent, and environmentally friendly agricultural power machinery, due to the greenhouse gas emissions and the drastic reduction in the extraction of non-renewable resources. Fuel cell distributed drive electric tractors (FCDET) can provide a new approach to developing green agricultural machinery. However, the great challenge has posed on the traction efficiency, short range, and high hydrogen consumption. A reasonable and effective power allocation can be expected to reduce energy consumption for the high efficiency of the fuel cell system. In this study, an allocation strategy of plowing drive power was proposed for FCDET using adaptive multi-resolution analysis (AMRA). The effective decoupling between the various energy sources was also realized to reduce the frequent start-stop and the large power fluctuations of the hydrogen fuel cell. Firstly, two models were established for the fuel cell system and the total efficiency solver. The first-time reconstruction was to obtain the subsequence that effectively responded to the oscillation characteristics of the power signal using the tunable Q-factor wavelet transform (TQWT). The second reconstruction was to decompose the low-frequency subseries into several discrete sub-signals with special sparse properties using variational mode decomposition (VMD). Then, the sparrow search algorithm (SSA) was used to obtain the optimal combination of modal decomposition layers and quadratic penalty factors for VMD in real time. Finally, the second-time decomposed subsequence and sub-signals were reconstructed, according to the frequency characteristics. The reconstructed power signal was redistributed among the various energy sources. A test was carried out to verify the power allocation. The power demand information of the drive motor was acquired for FCDET plowing conditions at the China YTO Mengjin test base, taking the ET504-H prototype as the object. The plowing condition included a 0-8.7 s starting stage and an 8.7-18.0 s stable plowing stage. The demand power signal shared a large rate of change in the starting stage and a large high-frequency characteristic in the stable plowing stage. In addition, another experiment was carried out on the transmission bench in the New Energy Key Laboratory of Henan Province, in order to test the cooperative operation of permanent magnet synchronous motors (PMSM) under three power allocations. The results showed that the FCDET drive power allocation using AMRA effectively improved the energy utilization of the fuel cell system and the economy of the whole vehicle in plowing condition. The fuel cell system efficiency was improved by 8.30% and 1.82%, respectively, compared with the power-following and the first-time reconstruction. The equivalent hydrogen consumption was reduced by 35.60% and 11.86%, respectively. Meanwhile, the drive motor efficiency was improved by 2.06% and 1.27% on average; the energy consumption was reduced by 3.73% and 2.60%, respectively. This finding can provide a novel theoretical and technical approach for the development of the FCDET control system. [ABSTRACT FROM AUTHOR]

Under low-voltage microgrid conditions, when virtual synchronous generators (VSG) are connected in parallel with loads, there is power coupling between the output active and reactive power due to the resistive characteristic of the equivalent transmission impedance, and the output power suppression effect cannot be accurately distributed with poor current circulation, which seriously affects the steady-state performance of the system; Secondly, the line impedance of each inverter control system often does not match the capacity ratio, making the traditional virtual impedance decoupling strategy somewhat limited. The paper proposes a power decoupling strategy based on improved virtual impedance to address this problem by using a fuzzy algorithm to monitor the VSG power angle to adjust the virtual impedance in real time and still meet the requirements of VSG parallel operation power equalization and circulating current suppression during sudden load changes. Finally, a VSG simulation model is constructed in MATLAB/Simulink to verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A thermoelectric system should be designed in such a way that it harvests as large water heat as possible while using the least modules. To seek an optimal module number, the present study investigates the effect of source temperature, mass flow rate, turbulator, module number and layout on performance of a thermoelectric generator (TEG) system. The experimental results show the optimal module number isn't a fixed value and turbulator has a significant influence on the whole performance of the thermoelectric system. For compact configuration of TEG, using six modules is the best choice without a turbulator, while using eight modules has the best performance with turbulator. The study shows that module layout has a great effect on the thermoelectric system performance. Compared to compact configurations, all separate ones can harvest more power from the hot air except for 32 modules, enhancing by 10–50% whether the turbulator exists or not. In this situation, eight modules are optimal number. The net output power achieves a maximum value of 16.93W and the maximum net efficiency is 3.85% under present experimental parameters. Meanwhile, a new index called power uniformity coefficient is introduced to assess the distribution of output power among TEGs.

In the sparsely populated areas without electricity, the hydro photovoltaic power station is a feasible solution for electricity supply. The strategy of distributing the power among the inverters is critical to the efficiency of them. The conventional distributing strategies result in low efficiency of the inverters. In order to improve the efficiency, this paper analysed the loss and efficiency characteristics of the inverter and expressed the power distributing problem as an optimal control problem minimizing the total loss for the inverters. The optimal control problem was solved with particle swarm optimization and the efficiency optimum power distribution strategies in three operation scenarios were obtained. The quantitative analysis method was adopted to evaluate the effect of the efficiency optimum power distribution strategies. The total efficiency of the inverters with the optimal strategies and the conventional strategies were calculated respectively. The optimal distribution strategies were compared quantitatively with conventional power distribution strategies on the basis of the efficiency. The results demonstrated the validity of the strategies obtained in this paper in improving the total efficiency of the inverters.

The green port multi-energy microgrid, featuring renewable energy generation, hydrogen energy, and energy storage systems, is an important gateway to achieve the net-zero emission goal. But there are many forms of energy in green port multi-energy microgrid systems, the power fluctuates frequently, and the port loads with large fluctuations and fast changes. These factors can easily lead to the problem of the state of charge exceeding the limit of the energy storage system. To distribute the fluctuating power in the green port multi-energy microgrid system reasonably and maintain the state of charge (SOC) of the hybrid energy storage system in an moderate range, an energy management strategy (EMS) based on dual-stage fuzzy control with a low pass-filter algorithm is proposed in this paper. First, the mathematical model of a green port multi-energy microgrid system is established. Then, fuzzy rules are designed, and the dual-stage fuzzy controller is used to change the time constant of the low-pass filter (LPF) and modify the initial power distribution by an LPF algorithm. Finally, simulation models are built in Matlab 2016a/Simulink. The simulation results demonstrate that, compared with other algorithms under the control of the EMS proposed in this paper, the high-frequency component in the flywheel power is smaller, and the SOC of the supercapacitor is maintained in a reasonable range of 34–78%, which extends the lifespan of the flywheel and supercapacitor. Additionally, it has a faster automatic adjustment ability for the state of charge of the energy storage system, which is conducive to better maintaining the stable operation of green port multi-energy microgrid systems.

The recent developments in the design, planning, and operation of distribution systems indicate the need for a modern integrated infrastructure in which participants are managed through the perceptions of a utility company in an economic network (e.g., energy loss reduction, restoration, etc.). The penetration of distributed generation units in power systems are growing due to their significant influence on the key attributes of power systems. As a result, the placement, type, and size of distributed generations have an essential role in reducing power loss and lowering costs. Power loss minimization, investment and cost reduction, and voltage profile improvement combine to form a conceivable goal function for distributed generation allocation in a constrained optimization problem, and they require a complex procedure to control them in the most appropriate way while satisfying network constraints. Such a complex decision-making procedure can be solved by adjusting the dynamic optimal power flow problem to the associated network. The purpose of the present work is to handle the distributed generation allocation problem for photovoltaic units, attempting to reduce energy and investment costs while accounting for generation unpredictability as well as load fluctuation. The problem is analyzed under various scenarios of solar radiation through a stochastic programming technique because of the intense uncertainty of solar energy resources. The formulation of photovoltaic distributed generation allocation is represented as a mixed-integer second-order conic programming problem. The IEEE 33-bus and real-world 136-bus distribution systems are tested. The findings illustrate the efficacy of the proposed mathematical model and the role of appropriate distributed generation allocation. [ABSTRACT FROM AUTHOR]

A VVER-1000 reactor model using the Monte Carlo Serpent 2 code for core power distribution calculation is presented. The core and zones located near to the core were modeled in detail, without simplification. The assembly power distribution and axial power profiles were calculated for fresh core of the X2 VVER-1000 benchmark, namely the core of the KhNPP2 first loading for the hot zero power. The results were compared with the data obtained by specialists from Helmholtz-Zentrum Dresden-Rossendorf. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic power distribution strategy for the hybrid energy storage systems (HESSs) in electric vehicles (EVs). First, the power loss of a HESS is analyzed based on its structure and model. Second, the optimal objectives for EV range extension, battery degradation mitigation, and HESS energy loss reduction are set, and the corresponding optimization variables are determined. Then, a multi-objective collaborative optimization (MOCO) function is established. It is further transformed into a linear programming problem with the battery current as the control variable. Finally, the dynamic power distribution scheme is obtained by analyzing the MOCO problem. The dynamic power distribution strategy using the MOCO is studies through simulations and experiments under the worldwide harmonized light vehicles test cycle. The obtained results indicate that the performances of the three optimal objectives are collaboratively improved. [ABSTRACT FROM AUTHOR]