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Today's societies need a sustainable supply of energy more than ever, whereas unseen events challenge the electric power supply. The coordinated operation of a power‐gas‐transportation system can decrease the effects of such faults in the distribution level. This paper proposes a model predictive control approach for dynamic load restoration in an integrated energy system. The coordination of electric and gas networks besides the mobile energy storage (MES) units provides a novel resilient alternative to serve active and reactive loads. First, the location and time of drastic events are identified as the initialization phase in this paper using a vulnerability analysis by a master–slave problem to find the weak points of the electric grid. Then, a rolling horizon model predictive control‐based approach is proposed to make corrective decisions to serve loads. Meanwhile, a new linearization approach for the Weymouth equation has been proposed based on the binary expansion method. The proposed linear resiliency‐oriented scheduling problem is tested on IEEE 33‐bus and IEEE 69‐bus integrated with a seven‐node gas distribution grid and a six‐station transportation railway. The analysis revealed that the coordination between electric and gas resources minimizes the not‐supplied load; MES units act as certain emergency tools to serve the critical loads. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel's maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods. [ABSTRACT FROM AUTHOR]

This paper presents the feasibility analysis and study of integrated renewable energy (IRE) using solar photovoltaic (PV) and wind turbine (WT) system in a hypothetical study of rural health clinic in Borno State, Nigeria. Electrical power consumption and metrology data (such as solar radiation and wind speed) were used for designing and analyzing the integrated renewable energy system. The health clinic facility energy consumption is 19 kWh/day with a 3.4 kW peak demand load. The metrological data was collected from National Aeronautics and Space Administration (NASA) website and used to analyze the performance of electrical generation system using HOMER program. The simulation and optimization results show that the optimal integrated renewable energy system configuration consists of 5 kW PV array, BWC Excel‐R 7.5 kW DC wind turbine, 24 unit Surrette 6CS25P battery cycle charging, and a 19 kW AC/DC converter and that the PV power can generate electricity at 9,138 kWh/year while the wind turbine system can generate electricity at 7,490 kWh/year, giving the total electrical generation of the system as 16,628 kWh/year. This would be suitable for deployment of 100% clean energy for uninterruptable power performance in the health clinic. The economics analysis result found that the integrated renewable system has total NPC of 137,139 US Dollar. The results of this research show that, with a low energy health facility, it is possible to meet the entire annual energy demand of a health clinic solely through a stand‐alone integrated renewable PV/wind energy supply. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China's electricity consumption, this paper analyzes the data characteristics of China's electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China's power demand from 2004 to 2019, the ARMA time series model is used to analyze China's future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China's electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China's power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China's power. [ABSTRACT FROM AUTHOR]

Nowadays, power electronic technology is widely affecting people's daily work and life. However, there are still many problems in the current power supply research. When the fault information of power transformer is not complete or there is some ambiguity or even the information is lost, it will largely lead to the conclusion and correct conclusion of fault diagnosis. In this case, the fuzzy theory is applied to the fault diagnosis of shunt capacitor, and the fuzzy fault diagnosis system of shunt capacitor is studied. At the same time, a map-based fault diagnosis system is proposed. In this paper, the cloud computing technology is introduced into the deep learning and compared with SVM and DBN algorithm. The research results of this paper show that the accuracy of fuzzy diagnosis results is 94%, 84%, 90%, 80%, 83%, and 70%, respectively, which shows that the model diagnosis reliability is relatively high. Among the three algorithms, MR-DBN overall detection rate is higher and the time-consuming is lower than the other two methods. The diagnostic accuracy and misjudgment rate of DBN are as follows: 96.33% and 3.90%. The diagnosis accuracy and misjudgment rate of SVM are as follows: 96.40% and 3.83%. The diagnostic accuracy and misjudgment rate of MR-DBN are, respectively, 99.52% and 0.57%. Compared with the other two methods, MR-DBN has the highest diagnostic accuracy and the lowest error rate, which to a large extent indicates that MR-DBN algorithm has higher diagnostic accuracy and has greater advantages and reliability in power supply diagnosis and identification. It not only improves the accuracy of power capacitor fault diagnosis and identification but also provides a new method for the application of power capacitor fault research and development. [ABSTRACT FROM AUTHOR]

At present, multirotor drones are restricted by the control accuracy and cannot position accurately according to the accuracy of point cloud data. Also, track planning in three-dimensional space is much more complicated than that in two-dimensional space, which means that existing track planning methods cannot achieve fast planning. Meanwhile, most existing researches were implemented in quasi-three-dimensional space with the shortest route length as the objective function and omitted environmental impacts. To overcome these, this paper uses the grid method to segment point cloud data of the flying space via ArcGIS software according to the drone's controlling accuracy. It also extracts the grid coordinate information and maps it to a three-dimensional matrix to build the model accurately. This paper sets the minimal energy consumption as the objective function and builds a track planning model based on the drone's performance and natural wind constraints. The improved ant colony optimization and A ∗ (ACO- A ∗ ) algorithm are utilized to design this algorithm for a faster solution. That is, we use the improved ant colony optimization to quickly find a near-optimal track covering all viewpoints with the minimal energy consumption. The improved A ∗ algorithm will be used for local planning for adjacent tracks passing through obstacles. In the designed simulation environment, the simulation results show that, to ensure that the same components are shot, the improved algorithm in this paper can save 62.88% energy compared to that of the Shooting Manual of Drone Inspection Images for Overhead Transmission Lines. Also, it can save 9.33% energy compared to a track with the shortest route length. Besides, the ACO- A ∗ algorithm saves 96.6% time than the A ∗ algorithm. [ABSTRACT FROM AUTHOR]

This paper explores the feasibility of using the strut-braced wing (SBW) configuration to improve the flight endurance of the new energy unmanned aerial vehicle (UAV). A conceptual scheme of a new energy UAV with SBW configuration was designed, and the influence of the SBW on the aerodynamic and structural performance was analyzed. The results show that the SBW can improve the structural performance of the wing and increase the solar laying area of the wing, but the aerodynamic performance did not improve significantly. From the perspective of UAV energy consumption in level flight, the subtraction between electric output power and solar input power is selected as the evaluation index of the increasing effect of the flight endurance. A multidisciplinary design optimization (MDO) model was established considering the coupling of aerodynamics, structure, energy, and weight. Surrogate model technology and multiobjective genetic algorithm are used to optimize the SBW configuration. Compared with the conventional configuration, the optimal design result of the SBW configuration can reduce the level-flight output power and increase the solar input power, thus effectively increasing the flight endurance of the UAV. [ABSTRACT FROM AUTHOR]

The global demand of electrical power has increased enormously due to various reasons such as fast-changing and challenging technologies, climatic change, economic growth, and lifestyle of mankind. Due to global warming issues and the depletion of conventional sources of power generation, the utilization of renewable energy sources has drastically increased. So, many challenges exist in integrating the microgrid with AC grid and load. The alternative arm converter (AAC) is among the most innovative converter topologies used in high voltage direct current (HVDC) applications. This research work presents a new control strategy to generate pulses to trigger the switches in the AAC in a proper sequence to obtain a smooth output waveform. The AAC output is controlled by implementing various controllers such as the proportional-integral-derivative (PID) controller, fractional order PID (FOPID) controller, and FOPID controller tuned by metaheuristic algorithm-bacterial foraging optimization technique (BFOT). Also, a comparative analysis is performed based on the spectral analysis of the output voltage obtained. In comparison to other controllers, the FOPID controller optimized by the bacterial foraging optimization technique (BFOT) produced the least total harmonic distortion (THD) of the AAC output voltage. In addition, this paper also discusses about the performance and analysis on the design of an energy management system (EMS) to optimally utilize the energy sources such as PV system, wind system, and battery based on their availability which feed the AAC. The energy management system controls the entire integrated system in association with an integrated CUK-SEPIC converter to fulfil the load demand at the point of common coupling, either from the microgrid or the AC grid. A nine-level AAC model is designed integrating the microgrid, grid, and industrial loads with an energy management system using MATLAB/Simulink. The performance parameters of the entire model are analysed at every stage to provide stabilized output to meet the load demand. [ABSTRACT FROM AUTHOR]

In this paper, an intelligent integrated approach is proposed to control the reactive power and restore the voltage balance in a three-phase power system using particle swarm optimization (PSO), Gaussian process regression (GPR), and support vector machine (SVM). The PSO algorithm is used in offline mode to determine the optimal set of firing angles for the thyristor-controlled-reactor (TCR) compensator according to the smallest fitness value required for voltage balancing. The optimum firing angles are then used to train the GPR and SVM regression models. The GPR and SVM models are finally used as a real-time controller to retrieve the voltage balance in online mode. A simulation model and experimental setup of the electrical power system are built. The modeled system consists of a 500 km long transmission line. The line is divided into three-pi sections to guarantee a real system response. Several simulation and practical case studies have been conducted to test and validate the capability of the proposed integrated approach in solving the voltage unbalance problem. The results have revealed the supreme ability of the proposed integrated approach to restore the voltage balance quickly (within 20 ms) and for a wide range of voltage unbalance factors (VUFs) (3.90–8.42%). [ABSTRACT FROM AUTHOR]

With the rapid development of the city, shared bicycle travel has also entered a stage of rapid development. In order to ensure the happiness of citizens traveling, in view of the current supply and demand resources and bicycle scheduling problems, a model of supply and demand resource forecasting and multisite and multivehicle scheduling are established. Supply and demand resource prediction uses characteristic variables based on the graph structure itself as input variables of the prediction model XGBoost (extreme gradient boosting). Combined with the actual situation, the improved ant colony algorithm is used to design a reasonable scheduling for the multisite and multivehicle routing problem (VRP). Using Xiamen City shared bicycle data for simulation training, the results show that the shared bicycle scheduling method proposed in this paper has strong robustness and rationality. [ABSTRACT FROM AUTHOR]

Knowledge graph is a kind of semantic network for information retrieval. How to construct a knowledge graph that can serve the power system based on the behavior data of dispatchers is a hot research topic in the area of electric power artificial intelligence. In this paper, we propose a method to construct the dispatch knowledge graph for the power grid. By leveraging on dispatch data from the power domain, this method first extracts entities and then identifies dispatching behavior relationship patterns. More specifically, the method includes three steps. First, we construct a corpus of power dispatching behaviors by semi-automated labeling. And then, we propose a model, called the BiLSTM-CRF model, to extract entities and identify the dispatching behavior relationship patterns. Finally, we construct a knowledge graph of power dispatching data. The knowledge graph provides an underlying knowledge model for automated power dispatching and related services and helps dispatchers perform better power dispatch knowledge retrieval and other operations during the dispatch process. [ABSTRACT FROM AUTHOR]

The increased electricity demand amidst inadequate electricity generation in South Africa has plunged the country into frequent power outages and load shedding. However, the country still has the lowest electricity transmission and distribution losses in sub-Saharan Africa. Despite low losses, there is still an opportunity to reduce losses further and reduce power outages and load shedding. This study examines the determinants of electricity transmission and distribution losses in South Africa. The results will inform policymakers on avoiding higher electricity transmission losses to alleviate the current electricity shortfall. Using the time-series data from 1971–2020 and the autoregressive distributed-lag (ARDL) bounds testing approach to cointegration, the study confirmed a long-run relationship between electricity transmission, distribution losses, and income, price, investment, political regime, and economic integration. Regression analysis from the ARDL methods revealed that investments, political administration, and economic integration positively influence electricity transmission and distribution losses. At the same time, income reduces electricity transmission and distribution losses in the long run. However, income, price, and economic integration minimize electricity transmission losses in the short run while the remaining variables maintained their positive effects. The implication is that without proper checks in place, an expansion in South Africa's economic integration, investment, and democracy may negatively affect the electricity sector of the country through an increase in electric power losses, while higher income will help the industry via lower electric power losses. The paper, among other things, recommends building a robust economy to ensure lower levels of electricity transmission and distribution losses. [ABSTRACT FROM AUTHOR]

Traditionally, all working modes of a perfect electric conductor are classified into capacitive modes, resonant modes, and inductive modes, and the resonant modes are further classified into internal resonant modes and external resonant modes. In this paper, the capacitive modes are further classified into intrinsically capacitive modes and nonintrinsically capacitive modes; the resonant modes are alternatively classified into intrinsically resonant modes, which are further classified into nonradiative intrinsically resonant modes and radiative intrinsically resonant modes, and nonintrinsically resonant modes; the inductive modes are further classified into intrinsically inductive modes and nonintrinsically inductive modes. Based on the modal expansion corresponding to these new modal classifications, an alternative modal decomposition method is proposed. In addition, it is also proved that all intrinsically resonant modes and all nonradiative intrinsically resonant modes constitute linear spaces, respectively, but other kinds of resonant modes cannot constitute linear spaces; by including the mode 0 into the intrinsically capacitive mode set and the intrinsically inductive mode set, these two modal sets become linear spaces, respectively, but other kinds of capacitive modes and inductive modes cannot constitute linear spaces. [ABSTRACT FROM AUTHOR]

Increasing contingency issues result in inevitable bus voltage violations and force the system to operate around its limit. This situation creates strains that are faced by the security of the Ethiopian Electric Power (EEP) 400 kV system. In this paper, the static security assessment (SSA) of the system under the base and N-1 contingency scenarios was examined by using Newton-Raphson (NR) method. The Bus and line loading-based composite severity indices (CSI) were utilized to determine the state of the system and to get an optimal location for interline power flow controller (IPFC) placement. In this research, the optimal sizing of IPFC was done by using Grey Wolf Optimization (GWO) algorithm. From N-1 contingency analysis, Gelan to Sebeta and Gelan to Holeta branches were found as optimal places for IPFC placement. The IPFC optimal parameters were the series voltage and angle injection found as Vse1 = 0.1101pu, Vse2=0.1096pu, δse1=-0.1848rad, and δse2=2.7682rad with the optimal size of 50 MVA for each IPFC. The average bus voltage severity index (BVSI) without and with IPFC cases was found as 217.243% and 2.641% respectively. The average line severity index (LSI) without and with IPFC cases were found as 39.448% and 15.283% respectively. Moreover, the total line loss under severe N-1 contingency scenarios without and with IPFC integration was 437.783 MW and 63.136 MW respectively. From analysis, it was observed and concluded that the static security of the EEP 400 kV system under N-1 contingency conditions is effectively improved by the integration of IPFC. [ABSTRACT FROM AUTHOR]

An electrical “Grid” is a network that carries electricity from power plants to customer premises. Smart Grid is an assimilation of electrical and communication infrastructure. Smart Grid is characterized by bidirectional flow of electricity and information. Smart Grid is a complex network with hierarchical architecture. Realization of complete Smart Grid architecture necessitates diverse set of communication standards and protocols. Communication network protocols are engineered and established on the basis of layered approach. Each layer is designed to produce an explicit functionality in association with other layers. Layered approach can be modified with cross layer approach for performance enhancement. Complex and heterogeneous architecture of Smart Grid demands a deviation from primitive approach and reworking of an innovative approach. This paper describes a joint or cross layer optimization of Smart Grid home/building area network based on IEEE 802.11 standard using RIVERBED OPNET network design and simulation tool. The network performance can be improved by selecting various parameters pertaining to different layers. Simulation results are obtained for various parameters such as WLAN throughput, delay, media access delay, and retransmission attempts. The graphical results show that various parameters have divergent effects on network performance. For example, frame aggregation decreases overall delay but the network throughput is also reduced. To prevail over this effect, frame aggregation is used in combination with RTS and fragmentation mechanisms. The results show that this combination notably improves network performance. Higher value of buffer size considerably increases throughput but the delay is also greater and thus the choice of optimum value of buffer size is inevitable for network performance optimization. Parameter optimization significantly enhances the performance of a designed network. This paper is expected to serve as a comprehensive analysis and performance enhancement of communication standard suitable for Smart Grid HAN applications. [ABSTRACT FROM AUTHOR]

Not only mathematical statistics, differential equations, and mathematical models were used to analyze and reduce data, but a rough set model is also employed in medical, engineering, and other fields to analyze and reduce them. The goal of this paper is to introduce a minimal structure concept to produce new rough set models and show that it is suitable for analyzing most real-life problems, reduction of attributes, and decision making. We examine the effectiveness of the following method in the problem of electric power generators and decision making. We also offer a comparison of our method and Pawlak's method. Finally, the variable precision model improves the accuracy of decision making. [ABSTRACT FROM AUTHOR]

With the improvement of the intelligence level of the power network and the gradual improvement of the information and communication of the power system, the application of power big data to the corporate credit market is not only an important supplement to the national social credit system but also an important strategic goal for the State Grid to expand profitability. This paper constructs a benefit evaluation model for power data credit investigation products based on the utility of the products that financial institutions experience when they purchase and use financial risk control products. Based on the theory of customer value, comprehensively considering the characteristics of power credit reporting products, and taking profit maximization as the corporate goal, the pricing of a single power credit reporting product is studied, and the method is verified using example products. This article gives the pricing strategy of power credit investigation, which can be used as a reference for enterprises to further develop market strategies. [ABSTRACT FROM AUTHOR]

The electricity in Gaza, Palestine, is limited and scheduled for 4-10 hours per day due to political reasons. This status represents a real problem for different sectors. This paper presents an effective solution especially for the energy supply problem in the residential sector by using an unconventional PV system which operates in stand-alone and grid-connected modes. The system includes a storage battery block with a proper capacity to secure for continuous power supply of a residential house with a daily energy load of 10 kWh. It was found that an unconventional PV system of 3.2 kWp and a storage battery block of 19.2 kWh will be able to cover the total daily energy demands of the house including the outlined electricity cutoff hours. The design of this system and specifics of its components are presented in this paper. The system was simulated by Matlab software, where the daily load curve, grid cutoff hours, and the monthly solar radiation are considered. The obtained simulation results show that the produced PV energy exceeds the load demands during nine months of the year, and thereby, a high battery state of charge (SOC) in the range of 73-84% is achieved. During the three months of the lowest solar radiation (Dec.-Feb.), the produced PV energy is equal to the load demand while the battery state of charge varies in the range of 40-49% which verifies the appropriateness of the proposed PV system. The daily energy yield of the PV system varies between 2.6 and 5.4 kWh/kWp in January and July, respectively, which corresponds to a performance ratio of 90% and 66.25%, respectively. [ABSTRACT FROM AUTHOR]

Smart interference management methods are required to enhance the throughput, coverage, and energy efficiency of a dense small cell network. In this paper, we propose a transmit power control for energy efficient operation of a dense small cell network. We cast the power control problem as a noncooperative game to satisfy the design requirement that small cells do not need any information exchange among them. We analyze the sufficient condition for the existence of a Nash equilibrium (NE) state of the proposed game. We also analyze that the NE state is unique by transforming the original nonlinear fractional programming problem into a nonlinear parametric programming problem. Through simulation studies, we verify our analysis results. In addition, we show that the proposed method achieves higher energy efficiency of a network and balances the energy efficiency among cells more evenly than the methods based on the AIMD (additive increase and multiplicative decrease) algorithm. [ABSTRACT FROM AUTHOR]

Hydrogen fuel cell technology is identified as one option for allowing efficient vehicular propulsion with the least environmental impact on the path to a carbon-free society. Since more than 20 years, IHI is providing charging systems for stationary fuel cell applications and since 2004 for mobile fuel cell applications. The power density of fuel cells substantially increases if the system is pressurized. However, contaminants from fuel cell system components like structural materials, lubricants, adhesives, sealants, and hoses have been shown to affect the performance and durability of fuel cells. Therefore, the charging system that increases the pressure and the power density of the stacks inevitably needs to be oil-free. For this reason, gas bearings are applied to support the rotor of a fuel cell turbocharger. It furthermore comprises a turbine, a compressor, and, on the same shaft, an electric motor. The turbine utilizes the exhaust energy of the stack to support the compressor and hence lower the required electric power of the air supply system. The presented paper provides an overview of the fuel cell turbocharger technology. Detailed performance investigations show that a single-stage compressor with turbine is more efficient compared to a two-stage compressor system with intercooler. The turbine can provide more than 30% of the required compressor power. Hence, it substantially increases the system efficiency. It is also shown that a fixed geometry turbine design is appropriate for most applications. The compressor is of a low specific speed type with a vaneless diffuser. It is optimized for operating conditions of fuel cell systems, which typically require pressure ratios in the range of 3.0. [ABSTRACT FROM AUTHOR]

It is of great significance to accurately provide electric field information for electric power operators and electric power inspection equipment to ensure the safety of live working robots and electric power workers. In this paper, the principle of parallel plate charge induction is used to detect electric field signals and the influence of the inherent capacitance of the parallel plate on the back-end circuit is considered. An equipotential ring is used as the structure of the sensing unit to eliminate the uncertainty generated by the edge electric field. The parameters of the sensor probe are determined by the principle of differential-integration, and its structure is analyzed and designed. The consistency of the designed sensor probe was analyzed, and the results show that the consistency of the sensor is better. We have measured the sensitivity coefficients of the six probes, and the average absolute deviation reached 0.031556. The fits were all above 0.9995. In addition, a three-dimensional power frequency electric field measurement system that is easy to manufacture is designed using the hexahedral structure, which solves the problem of inaccurate electric field measurement caused by the parallel plate probe and the field source being not perpendicular, and the combined field strength formula of nonuniform electric field was obtained. In the laboratory environment, the three-dimensional power frequency electric field measurement system produced in this paper is compared with the electric field simulated by an electric field simulation tool. The test results show that the deviation between the measurement system and simulation is within ±0.55%, the measurement range is 1 kV/m–200 kV/m, the resolution is ≥1 V/m, and the maximum electric field can be measured at 200 kV/m. The nonlinear error is 2.15%, and the sensitivity coefficient is 19.10 mV / kV · m − 1 , which meets the measurement requirements of the power frequency electric field and can be applied to the actual power frequency electric field measurement. [ABSTRACT FROM AUTHOR]

This paper focuses on the fault-tolerant control (FTC) problem for an electric power steering (EPS) system subjected to stochastic sensor failures, and a novel fault-tolerant controller is proposed based on the genetic algorithm (GA). A mathematical model of the EPS system with sensor failures is first established, and the state feedback control law is solved by using linear quadratic regulator techniques to stabilize the closed-loop control system. Then, the dynamic response errors of the EPS system with and without sensor faults are chosen as the optimization objective function. Furthermore, the appropriate weighting matrices are evaluated to obtain the optimal fault control law by using GA. Finally, simulation results are presented to illustrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

For electric power steering system (EPS), road interference, noise of the sensor, and the uncertainty of the steering system may make EPS control effect and the driver's road sense worse. EPS system which takes advantage of good current tracking ability, good anti-interference ability, and good operation stability is becoming more and more important in automotive research. The traditional H∞ control algorithm can solve the system uncertainty theoretically, but it cannot solve the contradiction between robustness and performance without considering the performance of the system. Therefore, this paper proposes a EPS current tracking method based on the hybrid sensitivity H∞ control algorithm, which takes the current tracking performance as one of the control objectives, so that the system can maximize the robustness and performance. Firstly, the dynamic model of EPS is established. Then, the two-degree-of-freedom vehicle model and tire model are introduced. The state space equation of the system is constructed on the basis of the system state space with random disturbance signals, the hybrid sensitivity H∞ controller is designed in the sensitivity index design, and the proposed algorithm can use weighting function to minimize the performance of the current tracking error as well as the robustness of the yaw rate error in response to robustness. Simulation analysis and experimental verification of EPS system are also carried out. The results show that the control method of the hybrid sensitivity H∞ can better achieve EPS target current tracking, effectively suppress the effect of external interference and noise, improve the system performance and robustness, ensure the driver get good road sense, and improve the system of steering stability. [ABSTRACT FROM AUTHOR]

In current large-scale supply chain networks, unexpected disruptions degrade the supply availability and network connectivity for modern enterprises. How to improve the robustness of supply chain networks is very important for modern enterprises. In this paper, we explore how to improve the robustness of supply chain networks from a topological perspective. Firstly, through the empirical data-driven study, we show that the directed betweenness metric is more suitable than the other topological metrics in evaluating the robustness of supply chain networks. Then, we propose a rewiring algorithm based on directed betweenness to improve network robustness under the impact of disruptions. The experimental results in the large-scale supply chain network show that the rewiring algorithm based on directed betweenness effectively improves the network robustness. [ABSTRACT FROM AUTHOR]

Aiming at the high demand for the torque response speed and torque pulsation of the all-terrain vehicle (ATV) Electric Power Steering (EPS) system, this paper proposes to apply the Model Predictive Current Control to the all-terrain vehicle EPS system. A Novel Three-Vector Model Predictive Current Control (N3V-MPCC) is proposed in this paper to reduce the current ripple and reduce the calculation load. Two effective voltage vectors and a zero vector are selected in the control period through only six times of prediction and application of the Sector Vector Selection method. The duration of each voltage is calculated and output to the Voltage Source Inverter (VSI). Simulation and experimental results show that, compared with PID cascade Field Oriented Control (PI-FOC), N3C-MPCC can effectively reduce the ripple current of the d-axis and the q-axis. In the simulated electric power mode, the q-axis current ripple of the N3V-MPCC is reduced by 66.67%. Experimental results show that the current ripple of the motor is reduced by 60%, and the torque pulsation is reduced by 62.5%. Therefore, N3V-MPCC has a faster current response speed and smooth steering torque. [ABSTRACT FROM AUTHOR]

With the trend of low emissions and sustainable development, the demand for hybrid electric vehicles (HEVs) has increased rapidly. By combining a conventional internal combustion engine with one or more electric motors powered by a battery, HEVs have the advantages over traditional vehicles in better fuel economy and lower tailpipe emissions. Nevertheless, the power management strategies (PMSs) for conventional vehicles which mainly focus on the efficiency of internal combustion engine are no longer applicable due to the complex internal structure of HEVs. Hence, a large number of novel strategies appropriate for HEVs have been surveyed, but most of the researches concentrate on discussing the classifications of PMSs and comparing their cons and pros. This paper presents a comprehensive review of power management strategies adopted in HEVs aiming at specific challenges for the first time. The categories of the existing PMSs are presented based on the different algorithms, followed by a brief study of each type including the analysis of its pros and cons. Afterwards, the implementation and optimization of power management strategies aiming at proposed challenges are introduced in detail with the description of their optimization objectives and optimized results. Finally, future directions and open issues of PMSs in HEVs are discussed. [ABSTRACT FROM AUTHOR]

This paper presents two new general threshold gate (GTG) structures which are based on the monostable-bistable element (MOBILE) as their main part. These new GTGs eliminate an RTD from the structure compared to old structures and lead to less elements count and better performance in terms of power consumption, maximum frequency, and power-delay product (PDP). In the paper also two new single gate three-input XOR logic gates based on the old GTGs and two ones based on the new GTGs are presented and simulated in HSPICE simulator. [ABSTRACT FROM AUTHOR]

The electric power generated from different electricity sources are not used efficiently by end users in the world. This is due to the loss of power supplied in the case of electricity transmission and distribution to residential, commercial, and industrial loads. Even if the loss of power in the power system cannot be avoided 100%, it should be reduced to the minimum optimal value. The loss of power in the radial feeders can be minimized using an optimally allocated photovoltaic (PV) generation system by considering the information of geography, solar irradiance of the site, and space availability, which should not have shadow from large buildings and trees. The PV generation system eliminates the problem of power demand by enhancing the capacity of the power network as well as by reducing the depletion and consumption of fossil fuel resources. To reduce power loss and improve system loading capacity for demand response, the integration and finding the optimal place of photovoltaic generation take high concern from power system operators and technicians. The optimal allocation of PV has been done using the Genetic Algorithm (GA) for optimization of a multiobjective function with different constraints. The main objective of this paper is to minimize the power loss of the radial distribution networks by maintaining the phase voltage of the load in balance and improving the drop in voltage along the phase. So, GA is used to determine the best location and capacity of PV generation that can reduce the loss of power in the system. The IEEE-33 bus system is used to test the proposed method. Generally, using the GA and GIS methods results in a high accuracy for optimal placement of PV generation in the IEEE-33 bus radial feeder and enables to reduce the loss of power during transmission and distribution by maintaining the power quality for consumers. [ABSTRACT FROM AUTHOR]

The power load prediction is significant in a sustainable power system, which is the key to the energy system's economic operation. An accurate prediction of the power load can provide a reliable decision for power system planning. However, it is challenging to predict the power load with a single model, especially for multistep prediction, because the time series load data have multiple periods. This paper presents a deep hybrid model with a serial two‐level decomposition structure. First, the power load data are decomposed into components; then, the gated recurrent unit (GRU) network, with the Bayesian optimization parameters, is used as the subpredictor for each component. Last, the predictions of different components are fused to achieve the final predictions. The power load data of American Electric Power (AEP) were used to verify the proposed predictor. The results showed that the proposed prediction method could effectively improve the accuracy of power load prediction. [ABSTRACT FROM AUTHOR]

The renewable energy plays an increasingly important role in many fields such as lighting, automobile, and electric power. In order to make full use of the renewable energy, various smart Internet of Thing (IoT) devices are deployed. However, in the field of energy management, the two-way mismatch between the demand and the supply of the renewable energy will greatly affect the efficiency of the renewable energy. In addition, the security threat of the energy data and the privacy leakage of the user may hinder the further development of smart IoT devices. Therefore, how to achieve consistency and balance between the demand and the renewable energy supply and how to guarantee the security and privacy of smart IoT devices become the key problems of the energy-efficient smart environment. In this paper, a secure and intelligent energy data management scheme for smart IoT devices is proposed. It is worth noting that, with the help of artificial intelligence (AI) technologies and secure cryptography primitives, the proposed scheme realizes high-efficient and secure energy utilization in a smart environment. Specifically, the proposed scheme aims at improving the efficiency of the energy utilization in the multidimensions of a smart environment. In order to realize the fine-grain energy management of smart IoT devices, strategies of three different dimensions are considered and realized in the proposed scheme. Moreover, technologies in AI are applied and integrated into the energy management scheme. The analysis shows that the proposed scheme can make full use of the renewable energy in smart IoT devices. [ABSTRACT FROM AUTHOR]

Energy is the backbone of the economic development of a country. Ethiopia has bulk energy resource potential, and the effect of energy poverty on well-being, physical health, agriculture automation, education system, industries, and ability to prosper is valuable. A large proportion of the population living in Ethiopia has no electricity access. Among more than 110 million people living in Ethiopia, 46% only use electric energy for day-to-day activities like food preparation and other tasks. In the rural area of the country, where 80% of the population lives, people have no sustainable energy supply. The rural electrification needs special mechanisms to enhance the living standards of the people by opening opportunities for electric power infrastructures. The sustainable development of the country will be achieved when citizens are enabled to live up to the standard of living as humans. This paper investigates energy poverty in Ethiopia and its impact on the living standards of the people, like human resource development, health of individuals, and automation of agriculture, for the purpose of upgrading individual's lifestyle in the country. [ABSTRACT FROM AUTHOR]

The electrical infrastructure around the globe is expanding at a rapid rate for the sake of fulfilling power demands in the domestic, commercial and entertainment industries aiming to boost the living standards. In this regard, renewable energy sources (RES) are globally accepted potential candidates for maintaining inexhaustible, clean, and reliable electricity with a supplementary feature of economic prospect. The efficiency of power distribution at reduced cost to the consumers can be further enhanced by introducing a two-way billing system so-called net-metering which has the potential to overcome issues such as voltage regulation, power blackouts, overstressed grid and need for expensive storage systems thereby making it beneficial for the grid and the end user. This envisioning has encouraged the Government of Pakistan to install net-metering infrastructure at places which accommodate surplus renewable energy reserves. According to the Electric Power Act 1997, the National Electric Power Regulatory Authority (NEPRA) issued the net-metering rules and regulations in September 2015 by the endorsement of Federal Government which allowed the distribution companies in Pakistan to buy surplus electricity units generated by the consumers in order to partly reimburse the units imported from the utility grid. The aim behind this research work is to promote renewable energy utilization through net-metering mechanism in order to achieve maximum power. The export of units from consumer side to utility grid and vice versa can be made through bidirectional energy meter. In this paper, a solar net-metering analysis has been carried out on ETAP software to determine its benefits in a distribution network. Different scenarios have been investigated, and it is concluded that solar net-metering technique has multiple influential benefits, e.g., improvement in voltage regulation, reduction in transmission and distribution losses, increase in power availability, less billing to consumers, and reduction of loading on utility grid. [ABSTRACT FROM AUTHOR]

Triboelectric nanogenerators (TENGs) are advanced energy harvesters that convert mechanical energy in diverse environments into electrical energy via static electrification and electrostatic induction. However, their performance needs to be improved to expand their area of use and become more practical. In this study, we introduced molybdenum disulfide (MoS2) and tungsten disulfide (WS2) as separate additives into polyacrylonitrile (PAN) to produce composite nanofibers via electrospinning, aiming to increase the electrical output of the TENGs. This method increased contact area by narrowing the nanofiber diameters, which is a key factor in enhancing the triboelectric effect. The incorporation of MoS2 or WS2, characterized by high specific surface area, interface polarization, quantum confinement effects, and strong electron acceptance and trapping capabilities, led to a significant increase in the dielectric constant and overall electrical performance of the TENGs. Experimental evaluations, connecting the TENGs to circuits with various resistive loads, determined optimal performance at a load resistance of 4.7 MΩ. In particular, the 5 wt% WS2@PAN & polyvinylbutral (PVB) and 5 wt% MoS2@PAN & PVB TENGs exhibited a remarkable peak power output of 40.5 mW, corresponding to a power density of 25.3 W/m2 and provided open circuit voltage of 1,026 V. The integration of 5 wt% MoS2 or 5 wt% WS2 led to more than a twofold increase in electrical power density compared to pristine PAN. These outcomes demonstrate the significant impact of transition metal dichalcogenides in enhancing the energy conversion efficiency of contact–separation mode TENGs, thereby contributing to the advancement of energy harvesting technology. [ABSTRACT FROM AUTHOR]

In order to meet the navigation and positioning requirements of force inspection robot, a new technology based on improved VMD- + ACO algorithm is proposed. The main content of this technology is based on the research of improved VMD algorithm and ACO algorithm, through the comparison of VMD algorithm and improved VMD algorithm. By using ACO parameter optimization design and so on, the research means of improving VMD- + ACO algorithm navigation and positioning technology of electric inspection robot is finally established through experiments and analysis. The experiment result shows the following. The minimum iteration number of the improved ACO is 112, which is 24.32% less than that of the basic ACO. The mean value of the worst value and the optimal value of the function are equal to 0. It shows that the improved ACO has higher convergence precision and the number of iterations is significantly reduced. Conclusion. Based on the improved VMD- + ACO algorithm, it can meet the navigation and positioning requirements of electric inspection robot. [ABSTRACT FROM AUTHOR]

The role of nuclear energy is to supply electric power on a stable basis to meet increasing demands, reduce carbon dioxide emissions, and maintain stable electric power costs while ensuring safety. The Fukushima accident taught us many lessons for creating safer nuclear power plants. Considering the design of systems, the areas of weakness at the Fukushima nuclear power plants can be divided into three categories: plant protection, electricity supply, and cooling of the nuclear fuel. In this paper, focusing on these three areas, the lessons learned are proposed and applied for pressurized heavy water reactors. Firstly, hard protection against external risks ensures the integrity of components and systems such that they can perform their original functions. Secondly, additional emergency power supply systems for electrical redundancy and diversity can improve the response capabilities for an accident by increasing the availability of active components. Thirdly, cooling for removing decay heat can be augmented by adopting diverse safety systems derived from other types of reactors. This study is expected to contribute to the safety enhancement of pressurized heavy water reactors by applying design changes based on the lessons learned from the Fukushima accident. [ABSTRACT FROM AUTHOR]

To help the government manage waste lead-acid batteries in a more targeted and sustainable way, accurately forecasting the number of waste lead-acid batteries and analyzing their recovery potential play a key role. In China, electric bicycles are one of the most common means of transportation. As of the end of 2017, the social holding quantity of electric bicycles in China was over 250 million and that of electric tricycles was over 50 million. The quantity is equal to the total number of electric bicycles manufactured between 2011 and 2017. Currently, 90% of electric bicycles adopt lead-acid batteries as their power batteries. However, there are a few studies on the lead-acid batteries used in electric bicycles as power batteries. In this paper, we have selected lead-acid batteries used in electric bicycles as the subject of research as such kind of batteries enjoys the widest user base, the most single-battery consumption volume, and the strongest mobility. Based on the output and sales of electric bicycles, we have obtained the quantity of power lead-acid batteries. We have then estimated the annual waste quantity of lead-acid batteries used in electric bicycles in 2000-2022 using the “market supply A model” and the “Stanford Model”, respectively, and based on the proportion of raw materials contained in lead-acid batteries and the proportion between reclaimed and discarded lead-acid batteries, we have estimated the recovery potential of discarded lead-acid batteries in 2000-2022. We estimate that the lead-acid batteries used in electric bicycles only have great recovery potential and there are abundant potential resources for recovery. The research data and results can help decision-makers make more effective and more accurate management measures and policies. [ABSTRACT FROM AUTHOR]

Management of electric equipment has a direct impact on companies’ performance and profitability. Considering the critical role that electric power materials play in supporting maintenance operations and preventing equipment failure, it is essential to maintain an inventory to a reasonable level. However, a majority of these electric power materials exhibit an intermittent demand pattern characterized by random arrivals interspersed with time periods with no demand at all. These characteristics cause additional difficulty for companies in managing these electric power material inventories. In response to the above problem, this paper, based on the electric power material demand data of Shanghai Electric Power Company, develops a new method to determine the optimal order quantity Q⁎ in a cost-oriented periodic review (T,Q) system, whereby unsatisfied demands are backordered and demand follows a compound Erlang distribution. Q⁎corresponds to the value of Q that gives the minimum expected total inventory holding and backordering cost. Subsequently, an empirical investigation is conducted to compare this method with the Newsvendor model. Results verify its superiority in cost savings. Ultimately, considering the complicated calculation and low efficiency of that algorithm, this paper proposes an approximation and a heuristic algorithm which have a higher level of utility in a real industrial context. The approximation algorithm simplifies the calculation process by reducing iterative times while the heuristic algorithm achieves it by generalizing the relationship between the optimal order quantity Q⁎ and mean demand interarrival rate λ. [ABSTRACT FROM AUTHOR]

The continuous development of microgrid's technology creates favorable conditions for the access of distributed energy. Firstly, in order to consider the interests of the demand side and the power side, this paper presents a dual-layer optimal dispatching model of microgrid based on demand response. The objective of the first-layer optimization is to obtain the maximum load satisfaction and to optimize the load curve. The objective of the second-layer optimization is to make the microgrid system economical and environmentally friendly and to optimize the power utilization ratio. And a microsource control strategy based on the isolated microgrid is proposed, which can optimize the operation state of battery and improve the economy of the system. Finally, the Nondominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to solve the optimal scheduling problem of the isolated microgrid. The simulation results indicate that the microsource scheduling strategy proposed in this paper can improve the operation economy and environmental conservation of the system. It can improve the reliability ofmicrogrid power supply and reduce energy waste. [ABSTRACT FROM AUTHOR]

Nowadays, parabolic trough solar thermal plants are prevalent around the world. In different areas concerning the amount of solar radiation, their standard size is approximately between 20 and 100 MWe. Certainly, the right size of the solar field is the first selection with regard to nominal electrical power. A vast area will be economically unreasonable whereas a small area will mainly cause the power plant to operate at the part-load condition. This paper presents an economic modeling of a solar parabolic trough plant, operating at 25 MWe in Yazd, Iran. The varying types of collector dimensions have been investigated; then, by selecting autumnal equinox (22 September) at 12:00 PM as the design point, thermal performance of the solar power plant has been featured annually, in all conditions. The total operating time of the power plant is about 1726 hours (1248 hours in full-load condition). In the end, the effect of thermal storage tanks has been analyzed to save extra solar heat and use it at nights in hot months. By implementing a storage system, the total operating time will be increased to 3169 hours (2785 in full-load condition). Moreover, 7974 GJ useful thermal energy can be obtained from the solar field and storage system. [ABSTRACT FROM AUTHOR]

Significant disadvantages in power quality especially the unbalance problem and neutral sections restrict the evolution of conventional traction power supply system. A new traction power supply system based on three-phase to single-phase converter is studied, which can transfer active power from three-phase grid to single-phase catenary. One catenary section could be utilized in the new traction power supply system instead of the multiple split sections in conventional system. Three-phase to single-phase converter is the core equipment of new traction power system. MMC (modular multilevel converter) structure of AC-DC-AC substation is proposed in this paper. To solve the problem of the capacitor voltage balancing in MMC, a parallel sorting algorithm based on field programmable gate array (FPGA) is studied. And the correctness and effectiveness of the algorithm are verified by experiments. In addition, it is inevitable that the AC grid voltage will be unbalanced caused by the fault in the new system. Therefore, this paper focuses on the analysis of the effect of the unbalanced grid voltage on the operating characteristics of the MMC system. Finally, the correctness of the theoretical analysis is verified by simulation. [ABSTRACT FROM AUTHOR]

This paper presents a stability analysis of train converters in order to evaluate how the controller parameters affect the absorbed current. The new dynamic model presented in this paper is capable of considering the time-variant nature of the system for the correct tuning of the feedback proportional-integral PI controller, applying a current controlled modulation technique never used in high-power traction converters. The reduction of the harmonic content of the current absorbed by a converter employed at the input stage onboard high-speed trains is really important, considering the interaction with the signaling system set up for traffic control. A computer model of the converter, considering both the power and the control structure, has also been implemented in order to deliver a validated tool for the developed theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper, carbon fiber/carbon nanofiber strengthening nonmass concrete slab was designed, and ohmic heating (OH) curing was used to promote the strength formation of the slab under −20°C. COMSOL multiphysical field coupling program has been used to simulate the heating process of nonmass concrete slabs under different conditions. COMSOL analysis results showed that the optimal loading power density of OH cured sample under −20°C was 1000 W/m2∼1200 W/m2. Moreover, numerical analysis results were experimentally validated by the multipoint temperature measurement method. Furthermore, the mechanical properties showed that the compressive strength of the sample cured by 2 days OH curing at −20°C reached up to 48.2 MPa. SEM analysis exhibited that OH curing could improve the interfacial transition zone (ITZ) between the fiber and the matrix, leading to a denser microstructure. This study proved that COMSOL program could provide good theoretical guidance for OH cured nonmass cement concrete under subzero temperature. This work establishes an accurate guideline for electric power supplementation, laying a solid foundation of winter construction with high efficiency and low energy consumption. [ABSTRACT FROM AUTHOR]

With the continuous advancement of social economy, electric power, as an essential resource, plays an important supporting role for the development of industry and the lives of residents. As electric power itself is dangerous to a certain level, it is crucial to use the electric power rationally and ensure the safe application of electrical equipment. In this paper, AI image recognition technology is introduced to establish a comprehensive monitoring system for power transmission lines. Through the control of the potential risks of the transmission lines, emergency treatment of power transmission lines is implemented, which has provided an application support for the safe use of power equipment. Simulation experiments have verified that the image recognition technology based on AI can support omnidirectional monitoring of power transmission lines effectively. [ABSTRACT FROM AUTHOR]

This paper establishes the kinematic model of the automatic parking system and analyzes the kinematic constraints of the vehicle. Furthermore, it solves the problem where the traditional automatic parking system model fails to take into account the time delay. Firstly, based on simulating calculation, the influence of time delay on the dynamic trajectory of a vehicle in the automatic parking system is analyzed under the transverse distance Dlateral between different target spaces. Secondly, on the basis of cloud model, this paper utilizes the tracking control of an intelligent path closer to human intelligent behavior to further study the Cloud Generator-based parking path tracking control method and construct a vehicle path tracking control model. Moreover, tracking and steering control effects of the model are verified through simulation analysis. Finally, the effectiveness and timeliness of automatic parking controller in the aspect of path tracking are tested through a real vehicle experiment. [ABSTRACT FROM AUTHOR]

Piezoelectric cantilever beams, which have simple structures and excellent mechanical/electrical coupling characteristics, are widely applied in energy harvesting. When the piezoelectric cantilever beam is in a wind field, we should consider not only the influence of the wind field on piezoelectric beam but also the electromechanical coupling effect on it. In this paper, we design and test a wind-induced flag-swing piezoelectric energy harvester (PEH). The piezoelectric cantilever beam may vibrate in the wind field by affixing a flexible ribbon to the free end as the windward structure. To fulfill the goal of producing electricity, the flexible ribbon can swing the piezoelectric cantilever in a wind-induced unstable condition. The experimental findings demonstrate that the flag-swing PEH performs well in energy harvesting when the wind field is excited. When the wind speed is 15 m/s, the peak-to-peak output AC voltage may reach 13.88 V. In addition, the voltage at both ends of the closed-loop circuit's external resistance is examined. The maximum electric power of the PEH may reach 43.4 μW with an external resistance of 650 kΩ. After passing through the AC-DC conversion circuit, the flag-swing PEH has a steady DC voltage output of 1.67 V. The proposed energy harvester transforms wind energy from a wind farm into electrical energy for supply to low-power electronic devices, allowing for the creation and use of green energy to efficiently address the issue of inadequate energy. [ABSTRACT FROM AUTHOR]

Electric power steering (EPS) is widely used in tractor automatic driving because of its good operation stability. However, there is a lack of research about solving robust problems and response ability simultaneously when the tractor encounters emergency steering in harsh fields. The traditional robust controller has poor tracking performance and antidisturbance ability when encountering emergency steering. This paper proposes to add the corresponding mixed sensitivity operator to the corresponding performance index in the controller. By adjusting the amplitude of the mixed sensitivity operator, the tracking performance and the speed of disturbance attenuation can be both adjusted for the tractor EPS system. Simulation and hardware in the loop experiments verify the antidisturbance ability of the controller and the torque tracking performance. The results show that the control method has strong robustness and robust stability, which can meet the practical requirements. Also, the power steering characteristic of the H∞ controller with hybrid sensitivity design method is better than that of an unoptimized one, and its robustness is better, and under external pavement interference, the following ability is stronger for the ideal hand torque and the steering is more stable. [ABSTRACT FROM AUTHOR]

This paper presents new evidence supporting the development of a screening threshold to evaluate the impact aggregations of solar PV facilities in the northeastern United States can have on voltage deviations in the distribution grid (often called flicker). Using measurements from solar irradiance meters and customer-sited monitoring equipment for residential and light commercial solar systems in Central New York along with data from the Measurement and Instrumentation Data Centers at the Oak Ridge National Laboratory, Elizabeth City State University, and Bluefield College, we present multiple lines of support for the adoption of a flicker screening threshold equivalent to a 5% change in voltage resulting from a full-on to full-off transition of a solar facility. This approach is based on both the newer flicker perception limits in IEEE 1453-2015 and the previous limits derived from the flicker curves in IEEE 519-1992 and is consistent with recent draft recommendations from the Electric Power Research Institute (EPRI) for use in New York. Measurements of correlations between fluctuations at different sites along with a model for high densities of solar facilities are applied to allow the impact of multiple systems on a single feeder to be taken into account while maintaining the simplicity of a single screening threshold. [ABSTRACT FROM AUTHOR]

This paper investigates chronic diseases in the older population in the Chinese province of Henan and analyzes the rehabilitation needs and the current supply of related services in different levels of medical and elderly care institutions. We explore the fundamental causes for the diversified needs and insufficient supply of chronic disease patients in professional medical services and daily care. Using big data and deep learning (DL) in the sports domain, we propose a novel and intelligent prediction system for chronic diseases. Our model explores effective sinking methods of high-quality medical resources, training and guidance practices, assistance and guidance measures, and the ability to improve the grassroots services so that more chronically ill populations can stay in the community family as long as possible. In such an environment, they can receive cheap, safe, and suitable services. It can also lead to further improvement in constructing the government's regional medical rehabilitation care service system and can formulate long-term care relevant compensation policies. [ABSTRACT FROM AUTHOR]

Solar greenhouse technology emerges as a solution that intensifies crop yields and allows utilities to generate energy from photovoltaic cells. Here, we demonstrate a photonic crystal-integrated solar cell that selectively transmits photosynthetic light for plant cultivation and reflects the remaining light to the adjacent solar cells to generate electricity. The photonic crystal is fabricated using an e-beam evaporation method by nonperiodic stacking of TiO2 and SiO2 layers to transmit light at 400–500 nm (blue) and 600–700 nm (red) and reflect green (500–600 nm), ultraviolet, and infrared light. The photonic crystal-integrated solar cell is constructed with the vertically arranged copper indium gallium diselenide (CIGS) solar cell and the tilted photonic crystal with respect to the CIGS cell. By controlling the tilting angle of the photonic crystal film, it achieves the generated electric power of 40.2 W m-2 and the irradiance of 124.6 W m-2 for transmitted photosynthetic lights (400–500 and 600–700 nm). In contrast, a conventional horizontal CIGS cell shows a power generation of 55.6 W m-2 without any light transmission. This work provides a new optical strategy and design principle for the development of a wavelength-selective semitransparent solar cell. [ABSTRACT FROM AUTHOR]

The present investigation introduces an advanced methodology for maximum power point tracking (MPPT) applied to a piezo harvester scheme. A comprehensive rectifier circuit, equipped with an embedded MPPT component, is established to optimize energy production by monitoring a DC-DC inverter connected to the rectifier. Furthermore, the system's sensitivity error has been finely tuned to dynamically adjust its impedance unit in real time, thereby optimizing load acquisition. This innovative approach seamlessly integrates the MPPT algorithm into the piezo harvester circuit. Moreover, the vehicle's road handling is significantly augmented through the incorporation of a robust steering front and an active differential control system. Leveraging the MPPT module, the rectifier consistently achieves a power recovery efficiency exceeding 85%, independent of varying load conditions. Additionally, a DC-DC converter circuit has been seamlessly integrated to finely adjust the output voltage to meet specified levels. Numerical simulations demonstrate the effectiveness of the harvesting scheme, extracting a substantial output power of 90 W with an overall efficiency of 70%. The improved MPPT approach, employing angles of arrival (AoA) DV-Hop control strategies, minimizes the system's power consumption based on the Global Positioning System (GPS). The utilization of Harris Hawks optimization (HHO) and the generation of quadrants in the four-quadrant operation mode of DC motors in the wireless sensor network (RCSFs) have been significantly enhanced in this study. Simulations reveal that, at a velocity of 50 km/h, shock absorbers utilizing the received signal strength indication (RSSI) can harvest between 60 and 90 W on a class C road, based on the time of arrival (TOA). Striking a balance in ride comfort using the time difference of arrival (TDOA) as a trade-off constitutes approximately 30% of the piezoelectric harvester (PEH) system's power consumption when operating in active suspension mode, optimized by particle swarm optimization (PSO). [ABSTRACT FROM AUTHOR]