Widely used distribution generations (DGs) and energy storage systems (ESSs) enable a distribution system to have a more flexible fault reconfiguration capability. In order to enhance the service reliability and the benefit of distribution networks with DGs and ESSs, this paper proposes a novel distribution system reconfiguration (DSR) model including DGs and ESSs. Meanwhile, the impact of sectionalizing switches and tie switches on reliability is considered. The concept of “boundary switch” is introduced for quantifying the customer interruption duration. The DSR model is presented to minimize the sum of the customer interruption cost, the operation cost of switches, and the depreciation cost of DGs and ESSs. Furthermore, the proposed model is converted into a mixed-integer linear programming, which can be efficiently solved by commercial solvers. Finally, the validity and efficiency of the proposed DSR model are verified by a modified IEEE 33-bus system and a modified PG&E69-bus netw... [more]

Energy Storage Systems (ESS) and Distributed Generation (DG) are topics in a large number of recent research works. Moreover, given the increasing adoption of EVs, high capacity EV batteries can be used as ESS, as most vehicles remain idle for long periods during work or home parking. However, the high EV penetration introduces some issues related to the charging power requirements, thereby increasing the peak demand for microgrids where EV chargers are installed. In addition, photovoltaic distributed generation is becoming another issue to deal with in EV charging microgrids. Therefore, this new scenario requires an Energy Management System (EMS) able to deal with charging demand, as well as with generation intermittency. This paper presents an EMS strategy for Microgrids that contain an EV parking lot (EVM), Photovoltaic (PV) arrays, and dynamic loads connected to the grid considering a Point of Common Coupling (PCC). The EVM-EMS utilizes the projections of future PV generation and f... [more]

A mono tiltrotor (MTR) design which combines concepts of a tiltrotor and coaxial rotor is presented. The aerodynamic modeling of the MTR based on blade element momentum theory (BEMT) is conducted, and the method is fully validated with previous experimental data. An automated optimization approach integrating BEMT modeling and optimization algorithms is developed. Parameters such as inter-rotor spacing, blade twist, taper ratio and aspect ratio are chosen as design variables. Single-objective (in hovering or in cruising state) optimizations and multi-objective (both in hovering and cruising states) optimizations are studied at preset design points; i.e., hovering trim and cruising trim. Two single-objective optimizations result in different sets of parameter selections according to the different design objectives. The multi-objective optimization is applied to obtain an identical and compromised selection of design parameters. An optimal point is chosen from the Pareto front of the mul... [more]

Power system parameter matching is one of the key technologies in the development of hybrid electric vehicles. The power source is the key component of the power system which composed of engine, motor, and battery. Reasonable power source parameters are conducive to improve the power, fuel economy, and emission performance of vehicles. In this paper, regarding the problem that the plug-in hybrid electric vehicle (PHEV) parameter matching needs to weigh different design objectives, a multi-objective optimization and matching method based on a genetic algorithm is proposed. The vehicle dynamic model is established based on MATLAB/Simulink (Mathworks in Natick, Massachusetts, USA), and the feasibility of the model is verified by simulation. The main performance parameters of the power source are matched by theoretical analysis, and the PHEV integrated optimization simulation platform is established based on Isight(Dassault Systemes in Paris, France) and MALTAB/Simulink. Power source compo... [more]

From airplanes to electric vehicles and trains, modern transportation systems require large quantities of energy. These vast amounts of energy have to be produced somewhere—ideally by using sustainable sources—and then brought to the transportation system. Energy is a scarce and costly resource, which cannot always be produced from renewable sources. Therefore, it is critical to consume energy as efficiently as possible, that is, transportation activities need to be carried out with an optimal intake of energetic means. This paper reviews existing work on the optimization of energy consumption in the area of transportation, including road freight, passenger rail, maritime, and air transportation modes. The paper also analyzes how optimization methods—of both exact and approximate nature—have been used to deal with these energy-optimization problems. Finally, it provides insights and discusses open research opportunities regarding the use of new intelligent algorithms—combining metaheur... [more]

Damping circuits are installed inside the converter valve to limit commutation overshoots. They have significant effects on the valve’s turn-off performances, which should be carefully considered in parameter design. First, the calculation models for the turn-off process are discussed, including the conventional low frequency model and the broadband model. Then, it is found that high-frequency equipment parameters have significant effects on the transient valve voltage, which means that the conventional analytical methods based on low-frequency models is not suitable for damping circuit parameter design. The relationships between the turn-off performances and damping circuit parameters have also been analyzed in detail with the broadband model. To achieve better economic efficiency, this paper proposes a novel method for damping circuit parameter optimization, which combines the electromagnetic transient (EMT) calculation and the numerical optimization. Last, the case study is carried... [more]

In this paper we propose an optimization scheme for a selling strategy of an electricity producer who in advance decides on the share of electricity sold on the day-ahead market. The remaining part is sold on the complementary (intraday/balancing) market. To this end, we use probabilistic forecasts of the future selling price distribution. Next, we find an optimal share of electricity sold on the day-ahead market using one of the three objectives: maximization of the overall profit, minimization of the sellers risk, or maximization of the median of portfolio values. Using data from the Polish day-ahead and balancing markets, we show that the assumed objective is achieved, as compared to the naive strategy of selling the whole produced electricity only on the day-ahead market. However, an increase of the profit is associated with a significant increase of the risk.

The continuous development in the field of industrial automation and electric mobility has led to the need for more efficient electrical machines with a high power density. The improvement of electrical machines’ slot filling factors is one of the measures to satisfy these requirements. In recent years, this topic has aroused greater interest in the industrial sector, since the evolution of the winding technological manufacturing processes allows an economically sustainable realization of ordered winding arrangements, rather than random ones. Moreover, the manufacture of electrical machines’ windings must be preceded by an accurate design phase in which it is possible to evaluate the maximum slot filling factor obtainable for a given wire shape and for its dimensions. For this purpose, this paper presents an algorithmic approach for the evaluation of maximum slot filling factors in electrical machines under an ideal geometric premise. In particular, this algorithm has a greater degree... [more]

The main purpose of this paper is to quantitatively analyze the sensitivity of operating parameters of the system to the thermodynamic performance of an oxyfuel combustion (OC) power generation system. Therefore, the thermodynamic model of a 600 MW subcritical OC power generation system with semi-dry flue gas recirculation was established. Two energy consumption indexes of the system were selected, process simulation was adopted, and orthogonal design, range analysis, and variance analysis were used for the first time on the basis of single-factor analysis to conduct a comprehensive sensitivity analysis and optimization research on the changes of four operating parameters. The results show that with increasing oxygen purity, the net standard coal consumption rate first decreases and then increases. With decreasing oxygen concentration, the recirculation rate of dry flue gas in boiler flue gas ( χ 1 ) and an increasing excess oxygen coefficient, the net standard coal consumption... [more]

Overproduction of biomass and hyper-accumulation of lipids endow microalgae with promising characteristics to realize the cost-effective potential of advanced bioenergy. This study sought to heuristically optimize the culture conditions on a rarely reported Golenkinia sp. The results indicate that Golenkinia SDEC-16 can withstand the strong light intensity and grow in a modified BG11 medium. The optimal culture conditions for the favorable tradeoff between biomass and lipid accumulation were suggested as follows, 25,000 lux of light intensity, 9 mM of initial nitrogen concentration, and 20 mM of initial sodium chloride concentration. Under these conditions, the biomass concentration and productivity reached 6.65 g/L and 545 mg/L/d, and the synchronous lipid content and productivity reached 54.38% and 296.39 mg/L/d. Hypersalinity significantly promoted lipid contents at the cost of biomass and resulted in an increase of cell size but loss of spines of Golenkinia SDEC-16. The results she... [more]

This paper concerns the optimal design and comparative analysis of resonant and non-resonant high-frequency GaN-based rotating transformers. A multi-physical design approach is employed, in which magnetic, electrical, and thermal models are coupled. The results are verified by experiments. Two different optimization objectives are considered; firstly, the efficiency of two standard core geometries is maximized for a required output power level. Secondly, a geometrical optimization is performed, such that the core inertia is minimized for the desired output power level. The results of both design optimizations have shown large improvements in terms of output power and core inertia as a result of applying series−series resonant compensation.

The focus of this article is to introduce a method for the optimization of daily activity chains of travelers who use Electric Vehicles (EVs) in an urban environment. An approach has been developed based on activity-based modeling and the Genetic Algorithm (GA) framework to calculate a suitable schedule of activities, taking into account the locations of activities, modes of transport, and the time of attendance to each activity. The priorities of the travelers concerning the spatial and temporal flexibility were considered, as well as the constraints that are related to the limited range of the EVs, the availability of Charging Stations (CS), and the elevation of the road network. In order to model real travel behavior, two charging scenarios were realized. In the first case, the traveler stays in the EV at the CS, and in the second case, the traveler leaves the EV to charge at the CS while conducting another activity at a nearby location. Through a series of tests on synthetic activi... [more]

This paper proposes a novel technique to tune the PI controllers of a bidirectional HVDC light system by embedding particle swarm optimization directly in the Simulink model in the design procedure. The HVDC light system comprises of a rectifier station, a DC link, and an inverter station. Each converter station requires four PI controllers to be tuned in the decoupled d-q vector control scheme, and with the bidirectional HVDC system, the required PI controllers are doubled. Tuning these many controllers using conventional methods is a challenging task, especially if the parameters of the converter stations are different. A novel approach to tune the PI controllers for a bidirectional HVDC system using the time-domain performance indices is presented in this paper. The time-domain performance indices are optimized using the particle swarm optimization (PSO) algorithm. The results of the proposed tuning method show that the proposed method not only gives superior results but also is les... [more]

One direction in optimizing wind farm production is reducing wake interactions from upstream turbines. This can be done by optimizing turbine layout as well as optimizing turbine yaw and pitch angles. In particular, wake steering by optimizing yaw angles of wind turbines in farms has received significant attention in recent years. One of the challenges in yaw optimization is developing fast optimization algorithms which can find good solutions in real-time. In this work, we developed a random search algorithm to optimize yaw angles. Optimization was performed on a layout of 39 turbines in a 2 km by 2 km domain. Algorithm specific parameters were tuned for highest solution quality and lowest computational cost. Testing showed that this algorithm can find near-optimal (<1% of best known solutions) solutions consistently over multiple runs, and that quality solutions can be found under 200 iterations. Empirical results show that as wind farm density increases, the potential for yaw opt... [more]

To improve the efficiency of bioethanol production, an advanced process was required to extract ethanol from solid-state fermented feedstock. With regard to the characteristics of no fluidity of solid biomass, a continuous solid-state distillation (CSSD) column was designed with a proprietary rotary baffle structure and discharging system. To optimize the operation condition, fermented sweet sorghum bagasse was prepared as feedstock for a batch distillation experiment. The whole distillation time was divided into heating and extracting period which was influenced by loading height and steam flow rate simultaneously. A total of 16 experiments at four loading height and four steam flow rate levels were conducted, respectively. Referring to packing, rectifying column, mass, and heat transfer models of the solid-state distillation heating process were established on the basis of analyzing the size distribution of sweet sorghum bagasse. The specific heat capacity and thermal conductivity va... [more]

The accurate prediction of pressure loss for two-phase slug flow in pipes with a simple and powerful methodology has been desired. The calculation of pressure loss has generally been performed by complicated mechanistic models, most of which require the iteration of many variables. The objective of this study is to optimize the previously proposed simplified slug flow model for horizontal pipes, extending the applicability to turbulent flow conditions, i.e., high mixture Reynolds number and near horizontal pipes. The velocity field previously measured by particle image velocimetry further supports the suggested slug flow model which neglects the pressure loss in the liquid film region. A suitable prediction of slug characteristics such as slug liquid holdup and translational velocity (or flow coefficient) is required to advance the accuracy of calculated pressure loss. Therefore, the proper correlations of slug liquid holdup, flow coefficient, and friction factor are identified and uti... [more]

An accurate lithium-ion battery state of health (SOH) estimate is a key factor in guaranteeing the reliability of electronic equipment. This paper proposes a new method that is based on an indirect enhanced health indicator (HI) and uses support vector regression (SVR) to estimate SOH values. First, three original features that can describe the dynamic changes of the battery charging and discharging processes are extracted. Considering the coupling relationship between pairs of the original health indicators, we use the differential evolution (DE) algorithm to optimize their corresponding feature parameters and combine them to form an enhanced health indicator. Second, this paper modifies the kernel function of the SVR model to describe the trend of SOH as the number of cycles increases, with simultaneous hyperparameters optimization via DE algorithm. Third, the proposed model and other published methods are compared in terms of accuracy on the same NASA datasets. We also evaluated the... [more]

The ongoing electrification of the heat and transport sectors is expected to lead to a substantial increase in peak electricity demand over the coming decades, which may drive significant investment in network reinforcement in order to maintain a secure supply of electricity to consumers. The traditional way of security provision has been based on conventional investments such as the upgrade of the capacity of electricity transmission or distribution lines. However, energy storage can also provide security of supply. In this context, the current paper presents a methodology for the quantification of the security contribution of energy storage, based on the use of mathematical optimization for the calculation of the F-factor metric, which reflects the optimal amount of peak demand reduction that can be achieved as compared to the power capability of the corresponding energy storage asset. In this context, case studies underline that the F-factors decrease with greater storage power capa... [more]

The implicit model of photovoltaic (PV) arrays in series-parallel (SP) configuration does not require the LambertW function, since it uses the single-diode model, to represent each submodule, and the implicit current-voltage relationship to construct systems of nonlinear equations that describe the electrical behavior of a PV generator. However, the implicit model does not analyze different solution methods to reduce computation time. This paper formulates the solution of the implicit model of SP arrays as an optimization problem with restrictions for all the variables, i.e., submodules voltages, blocking diode voltage, and strings currents. Such an optimization problem is solved by using two deterministic (Trust-Region Dogleg and Levenberg Marquard) and two metaheuristics (Weighted Differential Evolution and Symbiotic Organism Search) optimization algorithms to reproduce the current−voltage (I−V) curves of small, medium, and large generators operating under homogeneous and non-homogen... [more]

For the oil−electric−hydraulic hybrid power system, a logic threshold energy management strategy based on the optimal working curve is proposed, and the optimal working curve in each mode is determined. A genetic algorithm is used to determine the optimal parameters. For driving conditions, a real-time energy management strategy based on the lowest instantaneous energy cost is proposed. For braking conditions and subject to the European Commission for Europe (ECE) regulations, a braking force distribution strategy based on hydraulic pumps/motors and supplemented by motors is proposed. A global optimization energy management strategy is used to evaluate the strategy. Simulation results show that the strategy can achieve the expected control target and save about 32.14% compared with the fuel consumption cost of the original model 100 km 8 L. Under the New European Driving Cycle (NEDC) working conditions, the energy-saving effect of this strategy is close to that of the global optimizati... [more]

This study adopts a multi-disciplinary optimization design method based on an approximation model to improve the comprehensive performance of axial-flow pump impellers and fully consider the interaction and mutual influences of the hydraulic and structural designs. The lightweight research on axial-flow pump impellers takes the blade mass and efficiency of the design condition as the objective functions and the head, efficiency, maximum stress value, and maximum deformation value under small flow condition as constraints. In the optimization process, the head of the design condition remains unchanged or varies in a small range. Results show that the mass of a single blade was reduced from 0.947 to 0.848 kg, reaching a decrease of 10.47%, and the efficiency of the design condition increased from 93.91% to 94.49%, with an increase rate of 0.61%. Accordingly, the optimization effect was evident. In addition, the error between the approximate model results and calculation results of each r... [more]

This paper deals with the implementation of a new technique of stochastic search to find the best set of parameters in a mathematical model, applied to the single cage (SC) model of the induction motor (IM). The technique includes a new strategy to generate variable constraints of the domain, seven error functions, weight for the operating zones of the IM, and multi-objective functions. The results are validated with experimental data of the torque and current in an IM, and show better fitting to the experimental curves compared with the results of two different techniques, one deterministic and the other one stochastic. The results obtained allow us to conclude that the best set of parameters for the model depends on the weights assigned to the objective functions and to the operating zones.

In this article, the characteristics of the wave energy converter are considered and a novel dynamic controller (NDC) for a permanent magnet synchronous generator (PMSG) is proposed for Wells turbine applications. The proposed NDC includes a recursive cerebellum model articulation controller (RCMAC) with a grey predictor and innovative particle swarm optimization (IPSO). IPSO is developed to adjust the learning speed and improve learning capability. Based on the supervised learning method, online adjustment law of RCMAC parameters is derived to ensure the system’s stability. The NDC scheme is designed to maintain a supply−demand balance between intermittent power generation and grid power supply. The proposed NDC exhibits an improved power regulation and dynamic performance of the wave energy system under various operation conditions. Furthermore, better results are obtained when the RCMAC is used with the grey predictive model method.

With respect to the light environment of the exhibition halls for Chinese calligraphy and painting works in the museums, the daylighting design in these display spaces have been studied, the key design factors, such as daylighting pattern, and arrangement of exhibits are examined and explored by field trips. Then, the display spaces are divided into diverse categories whose sky light environments are predicted by the demands of exhibits. Under changed daylighting situations, the daylight parameters, i.e., daylight factor (DF) and DF uniformity, discomfort glare index (DGI) and luminance distribution are calculated. Thus, the proper daylighting pattern and elements in the exhibition halls will be decided. The optimization strategies that optimize the parameters of daylighting patterns and elements are presented. The studies have shown that the daylighting quality will improved by the implement of optimal design, and good luminance environment in the calligraphy and painting exhibition h... [more]

In this paper, we propose a side-absorption concentrated module with diffractive grating as a spectral-beam-splitter to divide sunlight into visible and infrared parts. The separate solar energy can be applied to different energy conversion devices or diverse applications, such as hybrid PV/T solar systems and other hybrid-collecting solar systems. Via the optimization of the geometric parameters of the diffractive grating, such as the grating period and height, the visible and the infrared bands can dominate the first and the zeroth diffraction orders, respectively. The designed grating integrated with the lens and the light-guide forms the proposed module, which is able to export visible and infrared light individually. This module is demonstrated in the form of an array consisting of seven units, successfully out-coupling the spectral-split beams by separate planar ports. Considering the whole solar spectrum, the simulated and measured module efficiencies of this module were 45.2% a... [more]