Accurate forecasting of electric loads has a great impact on actual power generation, power distribution, and tariff pricing. Therefore, in recent years, scholars all over the world have been proposing more forecasting models aimed at improving forecasting performance; however, many of them are conventional forecasting models which do not take the limitations of individual predicting models or data preprocessing into account, leading to poor forecasting accuracy. In this study, to overcome these drawbacks, a novel model combining a data preprocessing technique, forecasting algorithms and an advanced optimization algorithm is developed. Thirty-minute electrical load data from power stations in New South Wales and Queensland, Australia, are used as the testing data to estimate our proposed model’s effectiveness. From experimental results, our proposed combined model shows absolute superiority in both forecasting accuracy and forecasting stability compared with other conventional forecast... [more]

The development of electric vehicles has significant value for the sustainable utilization of energy resources. However, the unreasonable construction of charging stations causes problems such as low user satisfaction, waste of land resources, unstable power systems, and so on. Reasonable planning of the location and capacity of charging stations is of great significance to users, investors and power grids. This paper synthetically considers three indicators of user satisfaction: charging convenience, charging cost and charging time. Considering the load and charging requirements, the model of electric vehicle charging station location and volume is established, and the model based on artificial immune algorithm is used to optimize the solution. An empirical analysis was conducted based on a typical regional survey. The research results show that increasing the density of charging stations, lowering the charging price and shortening the charging time can effectively improve user satisf... [more]

The growing penetration of photovoltaic (PV) systems may cause an over-voltage problem in power distribution systems. Meanwhile, charging of massive electric vehicles may cause an under-voltage problem. The over- and under-voltage problems make the voltage regulation become more challenging in future power distribution systems. Due to the development of smart grid and demand response, flexible resources such as PV inverters and controllable loads can be utilized for voltage regulation in distribution systems. However, the voltage regulation needs to calculate the nonlinear power flow; as a result, utilizing flexible resources for voltage regulation is a nonlinear scheduling problem requiring heavy computational resources. This study proposes an intelligent search algorithm called voltage ranking search algorithm (VRSA) to solve the optimization of flexible resource scheduling for voltage regulation. The VRSA is built based on the features of radial power distribution systems. A numeric... [more]

The aim of this article is to highlight the impact of a periodic power source, such as a tidal turbine, on the operation and sizing of an autonomous hybrid microgrid with photovoltaic panels and storage. The technique of hill climbing (repeated local search) is used to find the optimum combination of Renewable Energy Sources (RES) and storage units with respect to the required capital cost for various load curves and weather conditions. To model the operation of the microgrid devices, analytical and phenomenological models, have been used, which take into account the specifications of actual commercial devices. Six different case studies are presented, with and without a tidal generator, which are based on six different sets of electrical consumption data corresponding to the Euripus campus of the National & Kapodistrian University of Athens (NKUA) in Psachna, Evia, Greece, and respective meteorological and tidal current data from the region. The results show that tidal energy may be u... [more]

Wireless Power Transfer (WPT) is a promising technique, yet still an experimental solution, to replace batteries in existing implants and overcome the related health complications. However, not all techniques are adequate to meet the safety requirements of medical implants for patients. Ensuring a compromise between a small form factor and a high Power Transfer Efficiency (PTE) for transcutaneous applications still remains a challenge. In this work, we have used a resonant inductive coupling for WPT and a coil geometry optimization approach to address constraints related to maintaining a small form factor and the efficiency of power transfer. Thus, we propose a WPT system for medical implants operating at 13.56 MHz using high-efficiency Complementary Metal Oxide-Semiconductor (CMOS) components and an optimized Printed Circuit Coil (PCC). It is divided into two main circuits, a transmitter circuit located outside the human body and a receiver circuit implanted inside the body. The trans... [more]

Aiming at the problem of easy-to-fall-into local convergence for automatic train operation (ATO) velocity ideal trajectory profile optimization algorithms, an improved multi-objective hybrid optimization algorithm using a comprehensive learning strategy (ICLHOA) is proposed. Firstly, an improved particle swarm optimization algorithm which adopts multiple particle optimization models is proposed, to avoid the destruction of population diversity caused by single optimization model. Secondly, to avoid the problem of random and blind searching in iterative computation process, the chaotic mapping and the reverse learning mechanism are introduced into the improved whale optimization algorithm. Thirdly, the improved archive mechanism is used to store the non-dominated solutions in the optimization process, and fusion distance is used to maintain the diversity of elite set. Fourthly, a dual-population evolutionary mechanism using archive as an information communication medium is designed to e... [more]

Maximizing regenerative energy utilization is an important way to reduce substation energy consumption in subway systems. Timetable optimization and energy storage systems are two main ways to improve improve regenerative energy utilization, but they were studied separately in the past. To further improve energy conservation while maintaining a low cost, this paper presents a strategy to improve regenerative energy utilization by an integration of them, which determines the capacity of each Wayside Energy Storage System (WESS) and correspondingly optimizes the timetable at the same time. We first propose a dual-objective optimization problem to simultaneously minimize substation energy consumption and the total cost of WESS. Then, a mathematical model is formulated with the decision variables as the configuration of WESS and timetable. Afterwards, we design an ϵ -constraint method to transform the dual-objective optimization problem into several single-objective optimization probl... [more]

In order to improve the functionality and efficiency of a unified power quality conditioner (UPQC), a DC-link bus integrated photovoltaic charging module is proposed in a UPQC. It can generate power for essential loads apart from providing energy to a DC-link bus. A conventional proportional integral (PI) controller fails to run smoothly in dynamic conditions of the micro-grid, since it has poor capabilities in determining suitable values of proportional gain and integral gain. So, the optimization algorithm for a PI controller based on chaos particle swarm optimization based on a multi-agent system (CPSO-MAS) algorithm was developed in this paper to overcome properties such as intermittent instability in the micro-grid. Through verification by simulation and experiment of UPQC harmonic compensation, it showed that the proposed DC link bus voltage control strategy can be effectively applied to UPQC towards various conditions related to voltage and current distortion. In addition, it pr... [more]

Designs of saturated-cores fault current limiters (FCLs) usually implement conducting or superconducting DC coils serving to saturate the magnetic cores during nominal grid performance. The use of coils adds significantly to the operational cost of the system, consuming energy, and requiring maintenance. A derivative of the saturated-cores FCL is a design implementing permanent magnets as an alternative to the DC coils, eliminating practically all maintenance due to its entirely passive components. There are, however, various challenges such as the need to reach deep saturation with the currently available permanent magnets as well as the complications involved in the assembly process due to very powerful magnetic forces between the magnets and the cores. This paper presents several concepts, achieved by extensive magnetic simulations and verified experimentally, that help in maximizing the core saturation of the PMFCL (Permanent Magnet FCL), including optimization of the permanent mag... [more]

Research demonstrated that the application of a multi-speed transmission could improve the dynamic and economic performance of electric vehicles. This paper deals with a novel multi-speed transmission for the electric dump truck (EDT) operating on the structure route (SR), which has a definite starting point and end point without complex traffic conditions. To optimize the gear ratio and shift schedule to reduce energy consumption in such conditions, the mathematical model of the transmission and the dynamic model of the EDT are initially required. Following this, the shift schedule is presented according to the motor efficiency map. After that, the gear ratio optimization is carried out by a particle swarm optimization (PSO) algorithm. Moreover, the proposed EDT is compared with an EDT with a single-speed transmission. The simulation results show that the energy consumption is reduced by 6.1%.

Micro-Grid (MG) with hybrid power resources can supply electric loads independently. In case of surplus power, the neighborhood micro-grids can be integrated together in order to supply the overloaded micro-grid. The challenge is to select the most suitable, optimal and preferable micro-grid within a distributed network, which consists of islanded MGs, to form that integration. This paper presents an intelligent decision-making criteria based on the Weighted Arithmetic Mean (WAM) of different technical indices, for optimal selection of micro-grids integration in case of overloaded event due to either unusual increase in consumed power or any deficiency in power generation. In addition, overloading is expected due to excess increase or decrease in weather temperature. This may lead to extreme increase of load due to increase of air conditioning or heating loads respectively. The proposed arithmetic mean determination based on six multi-objective indices, which are voltage deviation, fre... [more]

The openness of the electricity retail market results in the power retailers facing fierce competition in the market. This article aims to analyze the electricity purchase optimization decision-making of each power retailer with the background of the big data era. First, in order to guide the power retailer to make a purchase of electricity, this paper considers the users’ historical electricity consumption data and a comprehensive consideration of multiple factors, then uses the wavelet neural network (WNN) model based on “meteorological similarity day (MSD)„ to forecast the user load demand. Second, in order to guide the quotation of the power retailer, this paper considers the multiple factors affecting the electricity price to cluster the sample set, and establishes a Genetic algorithm- back propagation (GA-BP) neural network model based on fuzzy clustering (FC) to predict the short-term market clearing price (MCP). Thirdly, based on Sealed-bid Auction (SA) in game theory, a Bayesi... [more]

In this paper the emphasis is on the optimization of synthetic inertial response of wind power plants (WPPs) for power systems with high wind power penetration levels, considering different wind speed operating conditions. The synthetic inertial response of wind power plants can play an important role in the resilience of future power systems with low inertia during large frequency disturbances. In order to investigate this role, a generic optimization methodology employing the genetic algorithm is proposed, taking into consideration the frequency nadir, second frequency dip, and time to reach the quasi⁻steady-state frequency. This optimization methodology comprehends the inertial response capability of WPPs and the frequency control dynamics of the power system. Accordingly, offline parameter tuning of synthetic inertial response is performed at the power system level with the proposed methodology. Based on the optimization results, the relevant aspects to be considered by transmissio... [more]

This paper proposes a driving-scenario oriented optimal design of an axial-flux permanent-magnet (AFPM) motor for an electric vehicle. The target torque and speed (TN) curve is defined as three operation zones-constant torque, maximum direct current, and maximum voltage—based on the driving scenario. The AFPM motor is designed to minimize energy consumption based on the motor weight and the frequent operating points of a driving cycle. The final result shows that the electric vehicle driven by the proposed AFPM motor consumes about 15% less energy than motors designed using traditional methods.

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]