Load shedding control is an emergency control measure to maintain the frequency stability of the power system. Most of the existing load shedding methods use the extensive form of directly cutting off the outlet of the substation, featuring low control accuracy and high control cost. A network reconfiguration technique can adjust the topology of the distribution network and offers more optimization space for load shedding control. Therefore, this paper proposes a reconfiguration−load shedding coordination optimization scheme to reduce the power loss caused by load shedding control. In the proposed method, a load shedding mathematical optimization model based on distribution network reconfiguration is first established. The tie switches and segment switches in the distribution network are used to perform the reconfiguration of the distribution network, and the load switches are adopted to realize the load shedding. To improve the solving efficiency of the model, a solving strategy that... [more]

One of the main challenges faced by floor treatment service robots is to compute optimal paths that completely cover a set of target areas. Short paths are of noticeable importance because their length is directly proportional to the energy used by the robot. Such a problem is known to be NP-hard; therefore, efficient algorithms are needed. In particular, computation efficiency is important for mobile robots with limited onboard computation capability. The general problem is known as coverage path planning (CPP). The CPP has several variants for single regions and for disjoint regions. In this research, we are investigating the solutions for disjoint target regions (rooms) that have fixed connection points (doors). In particular, we have found effective simplifications for the cases of rooms with one and two doors, while the challenging case of an unbounded number of rooms can be solved by approximation. As a result, this work presents a divide and conquer strategy (DnCS) to address th... [more]

This work proposes the use of fuzzy-logic-based voltage frequency control (VFC) and adaptive inertia to improve the frequency response of a virtual synchronous generator (VSG)-based isolated microgrid system. The joint VFC and inertial control scheme is proposed to limit frequency deviations in these isolated microgrid systems, mainly caused by the increasing penetration of intermittent distributed energy resources, which lack rotational inertia. The proposed controller uses artificial neural networks (ANN) to estimate the exponent of voltage-dependent loads and modulate the system frequency by adjusting the output voltage of the VSGs, which increases the system’s active power reserves while providing inertial control by adjusting the inertia of VSGs to minimize frequency and VSG DC-link voltage excursions. A genetic algorithm (GA)-based optimization strategy is developed to optimally adjust the parameters of the fuzzy logic controller to diminish the impact of disturbances on the syst... [more]

A heat integration optimization method that considers the changes in process parameters is proposed to find the global optimal process scheme for a coal chemical company’s phenols and ammonia recovery process. The phenols and ammonia recovery process is simulated by Aspen Plus, and a programming method for heat exchanger networks synthesis that can simultaneously optimize process parameters and heat integration is constructed by Matlab. Taking the total annual cost as the objective function, the following process parameters are optimized: the hot feed temperature and cold/hot feed ratio of sour water stripper, the temperature of three-step partial condensation system, the feed temperature and column pressure of both solvent distillation column and solvent stripper. The result shows that, compared with the heat integration process under original process parameters, the new heat integration process saves 14.3% energy consumption and reduces the total annual cost by about 15.1%. The new h... [more]

The development of electric vehicles plays an important role in the field of energy conservation and emission reduction. It is necessary to improve the thermal performance of battery modules in electric vehicles and reduce the power consumption of the battery thermal management system (BTMS). In this study, the heat transfer and flow resistance performance of liquid cold plates with serpentine channels were numerically investigated and optimized. Flow rate (m˙), inlet temperature (Tin), and average heat generation (Q) were selected as key operating parameters, while average temperature (Tave), maximum temperature difference (ΔTmax), and pressure drop (ΔP) were chosen as objective functions. The Response Surface Methodology (RSM) with a face-centered central composite design (CCD) was used to construct regression models. Combined with the multi-objective non-dominated sorting genetic algorithm (NSGA-II), the Pareto-optimal solution was obtained to optimize the operation parameters. The... [more]

Financial costs and energy savings are considered to be more critical on average for computationally intensive workflows, as such workflows which generally require extended execution times, and thus, require efficient energy consumption and entail a high financial cost. Through the effective utilization of scheduled gaps, the total execution time in a workflow can be decreased by placing uncompleted tasks in the gaps through approximate computations. In the current research, a novel approach based on multi-objective optimization is utilized with CloudSim as the underlying simulator in order to evaluate the VM (virtual machine) allocation performance. In this study, we determine the energy consumption, CPU utilization, and number of executed instructions in each scheduling interval for complex VM scheduling solutions to improve the energy efficiency and reduce the execution time. Finally, based on the simulation results and analyses, all of the tested parameters are simulated and evalua... [more]

One of the main energy sources utilized to produce power is coal. Due to the lack of combustion enhancement, the main issue with coal-based power plants is that they produce significant amount of pollutants. The major problem of slagging formation within the boiler; it sticks to the water tube walls, superheater, and reheater. Slagging might decrease the heat transferred from the combustion area to the water or steam inside the tubes, increasing the amount of coal and extra air. The abrupt fall of slag on the tube surface into the water-filled seal-trough at the bottom of the furnace might occasionally cause boiler explosions. In order to maximize heat transmission to the water and steam tubes by reducing or eliminating slag formation on the tube surface, the work presented here proposes an appropriate computational fluid dynamics (CFD) technique with a genetic algorithm (GA) integrated with conventional supercritical power plant operation. Coal usage and surplus air demand are both de... [more]

The integration of Photovoltaic (PV) systems requires the implementation of potential PV power forecasting techniques to deal with the high intermittency of weather parameters. In the PV power prediction process, Genetic Programming (GP) based on the Symbolic Regression (SR) model has a widespread deployment since it provides an effective solution for nonlinear problems. However, during the training process, SR models might miss optimal solutions due to the large search space for the leaf generations. This paper proposes a novel hybrid model that combines SR and Deep Multi-Layer Perceptron (MLP) for one-month-ahead PV power forecasting. A case study analysis using a real Australian weather dataset was conducted, where the employed input features were the solar irradiation and the historical PV power data. The main contribution of the proposed hybrid SR-MLP algorithm are as follows: (1) The training speed was significantly improved by eliminating unimportant inputs during the feature se... [more]

As a typical representative of the stator permanent magnet (PM) machines, the flux reversal machines (FRMs) have a simple structure, high availability of PMs, and high efficiency, making them suitable for direct drive applications. However, the PMs of the FRMs are mounted on the surface of the stator tooth, and its equivalent length of air gap is relatively large, which limits the torque increase. To improve the torque density, a novel FRM with auxiliary teeth is proposed in this paper. Half of the stator teeth are replaced by auxiliary teeth without PMs to reduce magnetic flux leakage, the number of PMs on each stator tooth is also changed. To improve the torque, the genetic algorithm is used to optimize the key design parameters to determine the optimal parameters of the machine. Finally, a finite element model is established to verify the analysis results. Compared with the conventional FRM, the torque of the proposed FRM is increased by 25.1%, the torque ripple is reduced by 24.1%,... [more]

Aerodynamic lift force acting on the solar structure is important while designing the counterweight for rooftop-mounted solar systems. Due to their unique configuration, the load estimated for solar structures using international building codes can be either higher or lower than the actual. Computational Fluid Dynamics(CFD) simulations haveproven to be an efficient tool for estimating wind loads on solar panels for design purposes and identifying critical design cases. Computational Fluid Dynamics (CFD) simulations usually require high computation power, and slight changes in geometry to find optimum configuration can be time-consuming. An optimization method to minimize lift force effects on solar photovoltaic (PV) arrays installed on rooftops usesthe Computational Fluid Dynamics (CFD)and genetic algorithms proposed in this paper. The tilt angle and pitch between two rows of solar panels were parameterized, and a genetic algorithm was used to search for aconfiguration resulting in min... [more]

A P0 system is used in hybrid automobiles to improve engine economy and performance. An essential element of the P0 system for effectively transmitting power to the drive train is the belt drive system (BDS). The features of electric machine (EM) and internal combustion engines (ICE) are taken into account by standard energy management systems, such as the equivalent consumption minimization strategy (ECMS). In order to maximize the effectiveness of the P0 system, this work provides a novel formulation of the ECMS, which considers the power loss map of the BDS in addition to the characteristic maps of EM and ICE. A test bench is built up to characterize the BDS, and it is verified using an open-loop Hardware in the Loop (HIL) in the WLTP driving cycle. To find the most appropriate equivalence factors for the ECMS, which would ordinarily be tuned through trial and error, a genetic algorithm (GA) is used. With regard to the standard ECMS, the proposed methodology intends to reduce fuel u... [more]

The six-pole radial−axial hybrid magnetic bearing (RAHMB) has the advantages of small space and low power consumption, making it suitable for flywheel batteries. The bearing capacity and the volume are the main specifications of magnetic bearings that should be considered comprehensively. In this work, the six-pole RAHMB was used in a horizontal flywheel battery. As the axial bearing capacity is relatively smaller than the radial bearing capacity, a design method with independent radial and axial bearing capacity is proposed, and the parameters are optimized to minimize the volume. The mathematical model of six-pole RAHMB was derived from the equivalent magnetic circuit method. The relationships between bearing capacity, biased flux density, saturation flux density and the section area of magnetic poles were analyzed. The basic principle of the design method with independent radial and axial bearing capacity is to determine which five of the variables are preferred. According to the de... [more]

With the rapid increase in demand for the construction and development of island cities in the South China Sea, the urban heat island phenomenon in such cities should become a key factor to be considered in future urban planning. This paper took Sanya, China as a typical case, and long-term field experiments were conducted in the Mangrove Bay Area in summer and winter. An innovative urban green space cooling model was proposed, using the “green space cooling index” to quantitatively characterize the green space cooling effect, and aiming to minimize the intensity of urban heat islands. This paper studied the optimization method of green space planning and layout under the constraint of a centralized green space total area. Moreover, a genetic algorithm was adopted to optimize the calculation and the layout of the urban green space. The experimental results showed that the urban heat island intensity was more significant at night and was less effective in the daytime during summer. In w... [more]

Electrical machines are prone to faults and failures and demand incessant monitoring for their confined and reliable operations. A failure in electrical machines may cause unexpected interruptions and require a timely inspection of abnormal conditions in rotating electric machines. This article aims to summarize an up-to-date overview of all types of bearing faults diagnostic techniques by subdividing them into different categories. Different fault detection and diagnosis (FDD) techniques are discussed briefly for prognosis of numerous bearing faults that frequently occur in rotating machines. Conventional approaches, statistical approaches, and artificial intelligence-based architectures such as machine learning and deep learning are discussed summarily for the diagnosis of bearing faults that frequently arise in revolving electrical machines. The most advanced trends for diagnoses of frequent bearing faults based on intelligence and novel applications are reviewed. Future research di... [more]

The electrification of vehicles is considered to be the means of reducing the greenhouse gas (GHG) emissions of the transport sector, but “range anxiety” makes most people reluctant to adopt electric vehicles (EVs) as their main method of transportation. Workplace charging has been proven to counter range anxiety and workplace charging is becoming quite common. A workplace parking lot can house hundreds of EVs. In this paper, a program has been developed in MATLAB that uses the well-known evolutionary optimization algorithm, the genetic algorithm (GA), to optimize the charging schedule of fifty EVs that aims at achieving three goals: (a) keeping the electricity demand low, (b) reducing the cost of charging and (c) applying load shifting. Three schedules were developed for three scenarios. The results demonstrate that each schedule was successful in achieving its goal, which means that scheduling the charging of a fleet of EVs can be used as a method of demand-side management (DSM) in w... [more]

Electric vehicles (EVs) are becoming more commonplace as they cut down on both fossil fuel use and pollution caused by the transportation sector. However, there are a number of major issues that have arisen as a result of the rapid expansion of electric vehicles, including an inadequate number of charging stations, uneven distribution, and excessive cost. The purpose of this study is to enable EV drivers to find charging stations within optimal distances while also taking into account economic, practical, geographical, and atmospheric considerations. This paper uses the Fez-Meknes region in Morocco as a case study to investigate potential solutions to the issues raised above. The scorching, arid climate of the region could be a deterrent to the widespread use of electric vehicles there. This article first attempts to construct a model of an EV battery on MATLAB/Simulink in order to create battery autonomy of the most widely used EV car in Morocco, taking into account weather, driving s... [more]

Copper oxide ore is an important copper ore resource. For a certain copper oxide ore in Yunnan, China, experiments have been conducted on the grinding fineness, collector dosage, sodium sulfide dosage, inhibitor dosage, and activator dosage. The results showed that, by controlling the above conditions, better sulfide flotation indices of copper oxide ore are obtained. Additionally, ammonium bicarbonate and ethylenediamine phosphate enhanced the sulfide flotation of copper oxide ore, whereas the combined activator agent exhibited a better performance than either individual activator. In addition, to optimize all of the conditions in a more reasonable way, a combination of the 5-11-1 genetic algorithm and back propagation neural network (GA−BPNN) was used to set up a mathematical optimization model. The results of the back propagation neural network (BPNN) model showed that the R2 value was 0.998, and the results were in accordance with the requirement model. After 4169 iterations, the e... [more]

In the last decade, simulation software as a tool for managing and controlling business processes has received a lot of attention. Many of the new software features allow businesses to achieve better quality results using optimisation, such as genetic algorithms. This article describes the use of modelling and simulation in shipment and sorting processes that are optimised by a genetic algorithm’s involvement. The designed algorithm and simulation model focuses on optimising the duration of shipment processing times and numbers of workers. The commercially available software Tecnomatix Plant Simulation, paired with a genetic algorithm, was used for optimisation, decreasing time durations, and thus selecting the most suitable solution for defined inputs. This method has produced better results in comparison to the classical heuristic methods and, furthermore, is not as time consuming. This article, at its core, describes the algorithm used to determine the optimal number of workers in s... [more]

In this paper, the artificial bee colony (ABC) algorithm is hybridized with the genetic algorithm (GA) for a model parameter identification problem. When dealing with real-world and large-scale problems, it becomes evident that concentrating on a sole metaheuristic algorithm is somewhat restrictive. A skilled combination between metaheuristics or other optimization techniques, a so-called hybrid metaheuristic, can provide more efficient behavior and greater flexibility. Hybrid metaheuristics combine the advantages of one algorithm with the strengths of another. ABC, based on the foraging behavior of honey bees, and GA, based on the mechanics of nature selection, are among the most efficient biologically inspired population-based algorithms. The performance of the proposed ABC-GA hybrid algorithm is examined, including classic benchmark test functions. To demonstrate the effectiveness of ABC-GA for a real-world problem, parameter identification of an Escherichia coli MC4110 fed-batch cu... [more]

The aim of the study was to estimate the optimal parameters of apple drying and the rehydration temperature of the obtained dried apple. Conducting both processes under such conditions is aimed at restoring the rehydrated apple to the raw material properties. The obtained drying parameters allow the drying process to be carried out in a short drying time (DT) and at low energy consumption (EC). The effect of air velocity (vd), drying temperature (Td), characteristic dimension (CD), and rehydration temperature (Tr) on rehydrated apple quality was studied. Quality parameters of the rehydrated apple as: color change (CC), mass gain ratio (MG), solid loss ratio (SL), volume gain ratio (VG) together with DT and EC were taken into consideration. The artificial neural network was used for modeling of rehydrated apple quality parameters, DT, and EC. A multi-objective genetic algorithm was developed in order to optimize parameters of the drying and rehydration processes. The simultaneous minimi... [more]

The friction rotary welding (FRW) of magnesium alloy to aluminum alloy was presented in a paper due to significant interest in the manufacturing industry. A genetic algorithm (GA) method for optimizing FRW process parameters of dissimilar light alloys was presented. After obtaining the welding parameters by GA method, it was possible to determine the best tensile strength of the friction joint. The obtained joints were subjected to tensile strength. The highest tensile strength TS = 178 MPa was found using a genetic algorithm for the following friction welding parameters: friction force FF = 16 kN, friction time FT = 4 s, and upsetting force UF = 44 kN. The optimized values were compared with the experimental results. The application of the genetic algorithm method allowed increasing the tensile strength joint from 88 to 180 MPa. The maximum tensile strength of the friction welded magnesium alloy-aluminum alloy joints was 73% of the base AZ31B metal. The relationship between welding pa... [more]

Globally, wind power plays a leading role in the renewable energy industry. In order to ensure the normal operation of a wind farm, the staff will regularly check the equipment of the wind farm. However, manual inspection has some disadvantages, such as heavy workload, low efficiency and easy misjudgment. In order to realize automation, intelligence and high efficiency of inspection work, inspection robots are introduced into wind farms to replace manual inspections. Path planning is the prerequisite for an intelligent inspection robot to complete inspection tasks. In order to ensure that the robot can take the shortest path in the inspection process and avoid the detected obstacles at the same time, a new path-planning algorithm is proposed. The path-planning algorithm is based on the chaotic neural network and genetic algorithm. First, the chaotic neural network is used for the first step of path planning. The planning results are encoded into chromosomes to replace the individuals w... [more]

Parallel Machine Scheduling (PMS) is a well-known problem in modern manufacturing. It is an optimization problem aiming to schedule n jobs using m machines while fulfilling certain practical requirements, such as total tardiness. Traditional approaches, e.g., mix integer programming and Genetic Algorithm (GA), usually fail, particularly in large-size PMS problems, due to computational time and/or memory burden and the large searching space required, respectively. This work aims to overcome such challenges by proposing a heuristic-based GA (DAS/GA). Specifically, a large-scale PMS problem with n independent jobs and m identical machines with a single server is studied. Individual heuristic algorithms (DAS) and GA are used as benchmarks to verify the performance of the proposed combined DAS/GA on 18 benchmark problems established to cover small, medium, and large PMS problems concerning standard performance metrics from the literature and a new metric proposed in this work (standardized... [more]

There are unfavorable conditions such as constantly changing working conditions and frequent disturbances that affect Mach number control in wind tunnel flow fields. As the proportional, integral and differential (PID) parameters need to be re-tuned for each working conditions of a wind tunnel, the operational costs of wind tunnels are very high. Therefore, to lower these costs, a genetic algorithm was utilized to tune the PID parameters to achieve Mach number control of a multi-mode wind tunnel flow field. In this paper, firstly, models for the multi-mode wind tunnel were established; secondly, a PID control system was designed based on the genetic algorithm and the control effects of the proposed PID control system were verified by simulations and were compared with the effects of a PSO tuning PID control system.

In this article, we describe a prototype photoreactor of which the geometrical configuration was obtained by Genetic Algorithms to maximize the residence time of the reactant gases. A gas reaction mixture of CO2:H2O (1:2 molar ratio) was studied from the fluid dynamic point of view. The two main features of this prototype reactor are the conical shape, which enhances the residence time as compared to a cylindrical shape reference reactor, and the inlet heights and position around the main chamber that enables turbulence and mass transfer control. Turbulence intensity, mixing capability, and residence time attributes for the optimized prototype reactor were calculated with Computational Fluid Dynamics (CFD) software and compared with those from a reference reactor. Turbulence intensity near the envisioned catalytic bed was one percentage point higher in the reference than in the optimized prototype reactor. Finally, the homogeneity of the mixture was guaranteed since both types of react... [more]