Three-resonator wireless power transfer (WPT) systems have been proposed to improve the power transfer efficiency (PTE) and power delivered to the load (PDL) in recent years. However, analysis formulas of a three-resonator WPT system are complicated, and the parameters for clarifying the transfer characteristics of this system are difficult to extract. In this paper, concise formulas for analyzing PTE and PDL of the three-resonator system are derived by introducing three factors. Diagram discriminance based on the derived formulas is proposed to obtain the frequency splitting criterions of PTE and PDL in this system. Further, at the transfer distances, where the PTE and PDL are low at original frequency due to frequency splitting phenomenon, the two predetermined-goals of maximizing PTE and PDL are achieved by optimizing coupling strength between the three resonators. The third predetermined-goal of obtaining a constant amount of PDL transfer at maximum PTE is also implemented based on... [more]

Aiming at the impact of heat generation and temperature rise on the driving performance of a permanent magnet (PM) motor, taking the PM in-wheel motor (IWM) for electric vehicles as an object, research is conducted into the temperature distribution of the electromagnetic−thermal effect and cooling structure optimization. Firstly, the electromagnetic−thermal coupling model considering electromagnetic harmonics is established using the subdomain model and Bertotti’s iron loss separation theory. Combined with the finite element (FE) simulation model established by Ansoft Maxwell software platform, the winding copper loss, stator core loss and PM eddy current loss under the action of complex magnetic flux are analyzed, and the transient temperature distribution of each component is obtained through coupling. Secondarily, the influence of the waterway structure parameters on the heat dissipation effect of the PM-IWM is analyzed by the thermal-fluid coupled relationship. On the basis, the op... [more]

The study examines alternative on-board energy management system (EMS) supervisory control algorithms for plug-in hybrid electric vehicles. The optimum fuel consumption was sought between an equivalent consumption minimization strategy (ECMS) algorithm and a back-engineered commercial rule-based (RB) one, under different operating conditions. The RB algorithm was first validated with experimental data. A method to assess different algorithms under identical states of charge variations, vehicle distance travelled, and wheel power demand criteria is first demonstrated. Implementing this method to evaluate the two algorithms leads to fuel consumption corrections of up to 8%, compared to applying no correction. We argue that such a correction should always be used in relevant studies. Overall, results show that the ECMS algorithm leads to lower fuel consumption than the RB one in most driving conditions. The difference maximizes at low average speeds (<40 km/h), where the RB leads to mo... [more]

There are many studies that focus on extracting harmonics from both DC and AC sides of grid-interfaced photovoltaic (PV) systems. Based on these studies, the paper introduces an efficient method depending on hybrid DC voltage, and an active and reactive power (DC-V PQ) control scheme in a single-stage three-phase grid-interfaced PV system. The proposed scheme is designed to regulate DC voltage to minimize power loss and energy share between the network reconfiguration and the utility grid. Moreover, the technique is more effective at dealing with uncertainty and has higher reliability under various operating scenarios. These operations are the insertion of linear load 1, nonlinear load, and linear load 2. Moreover, a novel objective function (OF) is developed to improve the dynamic response of the system. OF is coupled with a particle swarm optimization (PSO) algorithm and a gradient optimization (GBO) algorithm. The analysis and the comparative study prove the superiority of GBO with... [more]

This work proposes a structural enhancement and a new technique to design the loop filter (LF) of a third-order phase-locked loop (PLL) to enhance the PLL dynamic performance under abnormal grid conditions. The proposed PLL combines a moving average filter (MAF) and an arbitrarily delayed signal cancelation (ADSC) for structural enhancement to achieve DC-offset rejection and harmonics elimination. The window length of the MAF is selected to be one-sixth of the fundamental grid period to remove non-triple odd harmonics and speed up the PLL dynamic response. The triple harmonics are eliminated, adopting the line-to-line voltage concept, while the ADSC operator rejects the DC offset. The LF design is based on a modified third-order polynomial tuned using stochastic optimization to minimize the settling time of the frequency deviation, offering better dynamic performance over the symmetrical optimum method (SOM) and achieving synchronization within one grid cycle. The PLL mathematical mode... [more]

Vehicular ad hoc networks (VANETs) are vital to many Intelligent Transportation System (ITS)-enabled technologies, including efficient traffic control, media applications, and encrypted financial transactions. Due to an increase in traffic, vehicular network topology is constantly changing, and sparse vehicle distribution (on highways) hinders network scalability. Thus, there is a challenge for all vehicles (in the network) to maintain a stable route, which would increase network instability. Concerning IoT-based network transportation, this study proposes a bio-inspired, cluster-based algorithm for routing, i.e., the intelligent, probability-based, and nature-inspired whale optimization algorithm (p-WOA), which produces cluster formation in vehicular communication. Various parameters, such as communication range, number of nodes, velocity, and route along the highway were considered, and their probaabilities were incorporated into the fitness function, hence resulting in randomness re... [more]

Firewood stoves are widespread and popular for renewable heat supply in Europe. Several new technological measures have been developed recently that aim at improving the appliance performance in terms of emissions and efficiency. In order to support the trend towards “(nearly) zero-emissions technologies”, the objective of this study was to provide a profound overview of the most relevant technical primary and secondary measures for emission reduction and to analyze their functionality, the relevant framework conditions for their application and their costs. Since user behavior is essential for emission and efficiency performance, the state of knowledge about user behavior is summarized and the latest measures for its optimization are evaluated as non-technical primary measures. Primary and secondary measures were analyzed separately, but also potentially promising combinations of primary and secondary optimization were evaluated using SWOT analysis. The results showed that complementa... [more]

In order to optimize the energy management strategy and solve the problem of the power quality degradation of fuel cell hybrid electric ships, a particle swarm optimization algorithm based energy management strategy is proposed in this paper. Taking a fuel cell ship as the target ship, a system simulation model is built in Matlab/Simulink to verify the proposed energy management strategy. Through simulations and comparisons, the bus voltage curve of the optimized hybrid power system fluctuates more gently, and the voltage sag is smaller. The amplitude of the voltage fluctuation under maneuvering conditions is reduced by 55% compared with that of the original ship. The charging and discharging process of the composite energy storage system is optimized under maneuvering conditions, the power quality of the marine power grid is improved, and the use of the energy management strategy can extend the service life of the battery.

This paper proposes a new cascaded fractional-order controller (CC-FOC) to solve the load frequency control (LFC) problem of an interconnected power system. The CC-FOC consists of a three-degree-of-freedom fractional-order proportional-integral-differential (3DOF-FOPID) controller and a fractional-order proportional-integral (FOPI) controller. Each area of the two-area interconnected power system in this study consists of a thermal unit, a hydro unit, a diesel unit, and a doubly-fed induction generator (DFIG). The enhanced particle swarm optimization (PSO) and gravitational search algorithm (GSA) under the chaotic map optimization (CPSOGSA) technique are used to optimize the controller gains and parameters to enhance the load frequency control performance of the cascade controller. Moreover, simulation experiments are conducted for the interconnected power system under load perturbation and random wind speed fluctuations. The simulation results demonstrate that the proposed cascaded fr... [more]

This paper studies the problem regarding the optimal power dispatch of photovoltaic (PV) distributed generators (DGs) in Direct Current (DC) grid-connected and standalone networks. The mathematical model employed considers the reduction of operating costs, energy losses, and CO2 emissions as objective functions, and it integrates all technical and operating constraints implied by DC grids in a scenario of variable PV generation and power demand. As a solution methodology, a master−slave strategy was proposed, whose master stage employs Antlion Optimizer (ALO) for identifying the values of power to be dispatched by each PV-DG installed in the grid, whereas the slave stage uses a matrix hourly power flow method based on successive approximations to evaluate the objective functions and constraints associated with each solution proposed within the iterative process of the ALO. Two test scenarios were considered: a grid-connected network that considers the operating characteristics of the c... [more]

To continue improving the integration of solar thermal in district heating networks, optimization tools that can study both sizing and operation of heating plants are needed. In this article, the ISORC tool was used to study the sizing and coupled operation of smaller storage and solar fields with other heating sources such as biomass and gas boilers. For this, a k-medoids algorithm was applied to select consecutive characteristic days to size the system based on an optimal operation of consecutive days in the same season. The formulated problem was nonlinear, and the objective function to be minimized was the total cost. Two case studies with different day constructions and distributions were studied with various sensitivity analysis. The formulation and methodology allowed us to study different cases and situations easily and proved the importance of the selection and attribution of typical days. In all cases, the results showed that even with a daily approach, solar thermal covers a... [more]

As more electrification and emission-free transportation trends receive more attention, electrical systems applied in the aircraft and automotive industries are changing from fossil fuel and hydraulic systems to electric AC machine drive systems. Three-dimensional printing technology has been contributing to a new design of machines, because it provides many opportunities without limitation compared to the conventional manufacturing system. Although 3D printing technology opened a door for increasing the efficiency and power density of AC machine drives with low conduction loss, an optimal design process for eddy current loss reduction is required, because eddy current loss is affected by the design structure of the machine. The slit structure at the stator shoe is proposed to reduce eddy current loss. With the three variables, the number of slits, the thickness of slits, and the length of ribs, a parametric analysis was conducted to find an optimal design with eddy current loss reduct... [more]

The thermal management and reduction of energy consumption in cooling systems have become major trends with the continued growth of high heat dissipation data centers and the challenging energy situation. However, the existing studies have been limited to studying the influences of individual factors on energy saving and thermal management and have not been systematically summarized. Thus, this paper reviews the key factors in achieving thermal management and reducing energy consumption in each cooling system, the corresponding research, and optimization methods. To achieve these goals, in this paper, literature surveys on data center cooling systems are investigated. For data center air cooling, thermal management is mainly related to the uniform distribution of hot and cold air. Adjusting the porosity of perforated tiles can reduce energy consumption. For liquid cooling and free cooling systems, climate conditions, cooling system structural design, coolant type, and flow rate are key... [more]

Mobility and transportation activities in smart cities require an increasing amount of energy. With the frequent energy crises arising worldwide and the need for a more sustainable and environmental friendly economy, optimizing energy consumption in these growing activities becomes a must. This work reviews the latest works in this matter and discusses several challenges that emerge from the aforementioned social and industrial demands. The paper analyzes how collaborative concepts and the increasing use of electric vehicles can contribute to reduce energy consumption practices, as well as intelligent x-heuristic algorithms that can be employed to achieve this fundamental goal. In addition, the paper analyzes computational results from previous works on mobility and transportation in smart cities applying x-heuristics algorithms. Finally, a novel computational experiment, involving a ridesharing example, is carried out to illustrate the benefits that can be obtained by employing these... [more]

Intermittency in the grid creates operational issues for power system operators (PSO). One such intermittent parameter is load. Accurate prediction of the load is the key to proper planning of the power system. This paper uses regression analyses for short-term load forecasting (STLF). Assumed load data are first analyzed and outliers are identified and treated. The cleaned data are fed to regression methods involving Linear Regression, Decision Trees (DT), Support Vector Machine (SVM), Ensemble, Gaussian Process Regression (GPR), and Neural Networks. The best method is identified based on statistical analyses using parameters such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Square Error (MSE), R2, and Prediction Speed. The best method is further optimized with the objective of reducing MSE by tuning hyperparameters using Bayesian Optimization, Grid Search, and Random Search. The algorithms are implemented in Python and Matlab Platforms. It is observed that the be... [more]

To solve the challenge of low efficiency and high operation cost caused by intermittent high-power charging in an energy storage tram, this work presents a collaborative power supply system with supercapacitor energy storage. The scheme can reduce the peak power of the transformer, therefore reducing the grid-side capacity and improving the efficiency. However, there is a lack of quantitative analysis on the performance improvement of the solution. The energy efficiency models of critical components are proposed to evaluate the efficiency of the system, and energy efficiency optimization is conducted. Taking an operational tram line as an example, the improved charging efficiency and reduced operating costs are derived. Further, the ground energy storage capacity is designed and implemented. The measured data demonstrates that the energy efficiency of the optimized charging system is improved, which proves its effectiveness and practicability.

The growing number of electric vehicles (EVs) affects the national electricity system in terms of power demand and load variation. Turning our attention to Italy, the number of vehicles on the road is 39 million; this represents a major challenge, as they will need to be recharged constantly when the transition to electric technology is complete. If we consider that the average power is 55 GW and the installed system can produce 120 GW of peak power, we can calculate that with only 5% of vehicles in recharging mode, the power demand increases to 126 GW, which is approximately 140% of installed power. The integration of renewable energy sources will help the grid, but this solution is less useful for handling large load variations that negatively affect the grid. In addition, some vehicles committed to public utility must have a reduced stop time and can be considered to have higher priority. The introduction of priorities implies that the power absorption limit cannot be easily introdu... [more]

For the sake of reducing the total operation cost of grid-connected microgrids, an improved pinning consensus algorithm based on the incremental cost rate (ICR) is proposed, which defines ICR as the state variable. In the algorithm, the power deviation elimination term is introduced to rapidly eliminate the total power deviation, and the pinning term is brought to realize the fast convergence to reference value. By computing the optimal ICR of the system, the optimal active output reference value of each distributed generation (DG) is obtained when the system realizes the economic optimization operation. In addition, an economic optimization control method of grid-connected microgrids, based on improved pinning consensus, is proposed. By utilizing the method, the economic optimization operation of the system is attained by basing on the established distributed hierarchical architecture and by sending the reference value of optimal active output of each DG to the P-f droop control loop.... [more]

The performance of a hybrid solar desalination system is predicted in this work using an enhanced prediction method based on a supervised machine-learning algorithm. A humidification−dehumidification (HDH) unit and a single-stage flashing evaporation (SSF) unit make up the hybrid solar desalination system. The Al-Biruni Earth Radius (BER) and Particle Swarm Optimization (PSO) algorithms serve as the foundation for the suggested algorithm. Using experimental data, the BER−PSO algorithm is trained and evaluated. The cold fluid and injected air volume flow rates were the algorithms’ inputs, and their outputs were the hot and cold fluids’ outlet temperatures as well as the pressure drop across the heat exchanger. Both the volume mass flow rate of hot fluid and the input temperatures of hot and cold fluids are regarded as constants. The results obtained show the great ability of the proposed BER−PSO method to identify the nonlinear link between operating circumstances and process responses.... [more]

Wind power ramp events (WPREs) are a common phenomenon in wind power generation. This unavoidable phenomenon poses a great harm to the balance of active power and the stability of frequency in the power supply system, which seriously threatens the safety, stability, and economic operation of the power grid. In order to deal with the impact of ramp events, accurate and rapid detection of ramp events is of great significance for the formulation of response measures. However, some attribute information is ignored in previous studies, and the laws and characteristics of ramp events are difficult to present intuitively. In this paper, we propose a visualization-based ramp event detection model for wind power generation. Firstly, a ramp event detection model is designed considering the multidimensional attributes of ramp events. Then, an uncertainty analysis scheme of ramp events based on the confidence is proposed, enabling users to analyze and judge the detection results of ramp events fro... [more]

The present work proposes an enhanced method of investigation and optimization photovoltaic (PV) modules by approaching and using MPPT (Maximum Power Point Tracking) technique to improve their output power. The performance of the PV panels is strongly influenced by the operating conditions, especially regarding the solar irradiance, temperature, configuration, and the shading (due to a passing cloud or neighboring buildings); all these cause, both on energy conversion loss, and further on non-linearity of the I-V characteristics. From this reason, the present study could have a high relevance based on the improvement of the performances (including the efficiency) of the shaded photovoltaic panels and would quantify the impact of a complex approach represented by numerical modeling and experimental validation. For a better understanding of these issues determined by partial shading, and improvement of MPP tracking, it is required to study the behavior of individual panels. For the best... [more]

Metaheuristic optimization techniques have successfully been used to solve the Optimal Power Flow (OPF) problem, addressing the shortcomings of mathematical optimization techniques. Two of the most popular metaheuristics are the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The literature surrounding GA and PSO OPF is vast and not adequately organized. This work filled this gap by reviewing the most prominent works and analyzing the different traits of GA OPF works along seven axes, and of PSO OPF along four axes. Subsequently, cross-comparison between GA and PSO OPF works was undertaken, using the reported results of the reviewed works that use the IEEE 30-bus network to assess the performance and accuracy of each method. Where possible, the practices used in GA and PSO OPF were compared with literature suggestions from other domains. The cross-comparison aimed to act as a first step towards the standardization of GA and PSO OPF, as it can be used to draw preliminary c... [more]

Conventional methods used to determine pyrolysis gas composition are based on chemical kinetics. The mechanism of those reactions is often unknown, which makes the calculations more difficult. Solving complex chemical reactions’ kinetics involving a nonlinear set of equations is CPU time demanding. An alternative approach is based on the Gibbs free energy minimization method. It requires only the initial composition and operation parameters as the input data, for example, temperature and pressure. In this paper, the method for calculating the pyrolytic gas composition from biogenic fuels has been presented, and the thermogravimetric experimental results have been adopted to determine the total gas yield. The studied problem has been reduced to the optimization method with the use of the Lagrange multipliers. This solution procedure is advantageous since it does not require knowledge of the reaction mechanism. The obtained results are in good agreement with experimental data, demonstrat... [more]

This paper proposes an impedance-accelerated inverse-time over-current protection optimization scheme based on the improved quantum genetic algorithm. First, the speed of remote backup protection is improved by increasing the optimization level of backup protection. Second, to ensure the coordination of protection when the distributed generation is connected to the distribution network, a mathematical model for the optimization of inverse time protection parameters is established. The mathematical model takes the minimum total action time of the optimized main and backup protection as the objective function, and the selectivity and sensitivity requirements of the protection as the constraints. In addition, the genetic algorithm is improved from four aspects: coding method, population initialization, quantum revolving gate, and variational evolution. The theoretical analysis and simulation results show that the proposed scheme can effectively improve the selectivity and operation speed... [more]

This paper introduces a brand-new, inspired optimization algorithm (the chaotic billiards optimization (C-BO) approach) to effectively develop the optimal parameters for fuzzy PID techniques to enhance the dynamic response of the solar−hydrogen drive of an induction motor. This study compares fuzzy-PID-based C-BO regulators to fuzzy PID regulators based on particle swarm optimization (PSO) and PI-based PSO regulators to provide speed control in solar−hydrogen, induction-motor drive systems. The model is implemented to simulate the production and storage of hydrogen while powering an induction-motor drive which provides a great solution for the renewable energy storage problem in the case of solar pumping systems. MATLAB/Simulink 2021a is used to simulate and analyze the entire operation. The laboratory prototype is implemented in real time using a DSP-DS1104 board. Based on the simulation and experimental results, the proposed fuzzy-PID-based C-BO has reduced speed peak overshoot by 45... [more]