In this research, a Concentrated Solar Power (CSP) as a Parabolic Trough Collector (PTC), using Peltier cooling modules for power generation was analyzed by the Cross-Entropy method. When comparing conventional solar electric generators with this system, we have the advantage that it is compact and lightweight and can be easily assembled and used as low-cost power generation equipment. For this system, we perform I(V) measurements and use fit models to accurately extract the model parameters. This is all in a standalone, robust, and simultaneous fit of three equations, through the global optimization method called Cross-Entropy. This is a robust method that had never been applied to extract parameters in a thermoelectric generation.

The optimal allocation of protective devices is a serious issue in an electrical power system; in order to reduce the possibility of faults, the protection devices should be optimally placed. The paper presents a continuous genetic algorithm (CGA) for the optimal allocation of directional relays for the efficient energy minimization in a radial distribution system (DG). The algorithm is flexible to use for the changes and improvements in the optimal location for a DG unit and can optimize the energy consumption in the radial distribution system. The proposed algorithm has been implemented on IEEE 33 and 69-bus system using MATLAB (R2014b, MathWorks). Low energy consumption is a common design objective in an energy-constrained distribution system. Engineers, power utilities, and network operators can profit from the proposed methodology to enhance the use of DG in distribution networks.

We have established a simulation platform for the machine−electro-hydraulic coupling system of the transmission system and the control system to study the root causes of the problems of large shifting impact and slow change of the machine tool transmission system. The dynamic analysis of the gear shift work of the gearbox was carried out, and the main factors affecting its shift instability were studied. With the impact and sliding power as the optimization goals, the shift quality is optimized based on the multi-objective genetic algorithm. Through the shift experiment, it was found that the power interruption phenomenon during the shift process was eliminated after optimization, and the quality of the shift was improved. Simulated planetary row wheel gear meshing force was found in the same gear, and the second planetary row gear meshing force was the largest among the planetary rows. The stress of the node near the top of the tooth is greater than the stress of the node near the nod... [more]

This paper examines the application of surface drilling parameters and drilling optimization techniques, such as mechanical specific energy (MSE) and equivalent strength (EST), in detecting hydrate gas-bearing sediments during drilling operations. Gas hydrates are usually detected from 3D seismic imaging and later confirmed with Measurement-While-Drilling (MWD)/Logging-While-Drilling (LWD) data and collected core samples. Here, we describe an analysis of the time-based surface drilling parameters recorded from two wells drilled during the International Ocean Discovery Program (IODP) Expedition 372A offshore of New Zealand and the Indian National Gas Hydrate Program Expedition 02 (NGHP-02) offshore of India. The investigation revealed that drilling parameters, as well as MSE/EST methods, can and should be used to monitor and optimize the drilling process and to detect lithological/tectonic (fractures, fault zones, rock hardness, etc.) changes in the drilled substrata and signs of the dy... [more]

In this work, the optimal design of a hybrid energy complex, including wind turbines, an internal combustion engine, and an adiabatic compressed air energy storage system is investigated. A novel bi-level optimization strategy is proposed for optimizing the capacity and operational power of each component of the system based on techno-economic considerations. The article presents information and discussions about the impacts of the partial-load operation of the energy storage system components on the optimal rated power and working strategies. The off-design characteristics are proven to have a huge negative impact on the efficiency and economy of the hybrid system. The efficiency reduction of the compressed air energy storage system is about 21% in summer and 8.9% in winter, when the system is operating in partial-load conditions. The operation cost of the system is reduced significantly when carrying out the proposed bi-level optimization strategy.

A chance-constrained programming-based optimization model for the dynamic economic emission dispatch problem (DEED), consisting of both thermal units and wind turbines, is developed. In the proposed model, the probability of scheduled wind power (WP) is included in the set of problem-decision variables and it is determined based on the system spinning reserve and the system load at each hour of the horizon time. This new strategy avoids, on the one hand, the risk of insufficient WP at high system load demand and low spinning reserve and, on the other hand, the failure of the opportunity to properly exploit the WP at low power demand and high spinning reserve. The objective functions of the problem, which are the total production cost and emissions, are minimized using a new hybrid chaotic maps-based artificial bee colony (HCABC) under several operational constraints, such as generation capacity, system loss, ramp rate limits, and spinning reserve constraints. The effectiveness and feas... [more]

Electricity access is strongly linked to human growth. Despite this, a portion of the world’s population remains without access to energy. In Colombia, rural communities have energy challenges due to the National Interconnected System’s (NIS) lack of quality and stability. It is common to find that energy services in such locations are twice as costly as in cities and are only accessible for a few hours every day due to grid overload. Implementing market mechanisms that enable handling imbalances through the flexible load management of main loads within the grid is vital for improving the rural power grid’s quality. In this research, the energy from the rural grid is primarily employed to power a heating, ventilation, and air-conditioning (HVAC) system that chills flowers for future commerce. This load has significant consumption within the rural grid, so handling HVAC consumption in a suitable form can support the grid to avoid imbalances and improve the end-user access to energy. The... [more]

In order to realize the sustainable development of energy, the combination of new energy power generation technology and the traditional offshore platform has excellent research prospects. The access to new energy sources can provide a powerful supplement to the power grid of the offshore platform, but will also create new challenges for the planning, operation, and control of the power grid of the platform; hence, it is very important to optimize the reactive power of the offshore platform with new study, a mathematical model was first built for the reactive power optimization of offshore platform power systems with new energy sources, and the Taguchi method was then used to optimize the parameters and population of particle swarm optimization, thereby addressing a defect in particle swarm optimization, namely, that it can easily fall into local optimal solutions. Finally, the algorithm proposed in this paper was applied to solve the reactive power optimization problem of the offshore... [more]

The aging of PV cells reduces their electrical performance i.e., the parasitic parameters are introduced in the solar panel. The shunt resistance (RSh), series resistance (RS), photo current (IPh), diode current (Id), and diffusion constant (a1) are known as parasitic or extraction parameters. Cracks and hotspots reduce the performance of PV cells and result in poor V−I characteristics. Certain tests are carried out over a long period of time to determine the quality of solar cells; for example, 1000 h of testing is comparable to 20 years of operation. The extraction of solar parameters is important for PV modules. The Tabu Search Optimization (TSO) algorithm is a robust meta-heuristic algorithm that was employed in this study for the extraction of parasitic parameters. Particle Swarm Optimization (PSO) and a Genetic lgorithm (GA), as well as other well-known optimization methods, were used to test the proposed method’s correctness. The other approaches included the lightning search al... [more]

The goal of carbon neutrality is an extensive and profound economic and social change, which will have far-reaching impacts on industrial structure, energy structure, and social consumption structure. Energy sectors will face in-depth adjustment, and it is essential to optimize major structures consequently due to the foresight of talent training. This research first employs Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis, Analytic Network Process (ANP), and the weighted fuzzy Technique for Order Performance by Similarity to Ideal Solutions (TOPSIS) to formulate and analyze the structure optimization of academic disciplines, and finally, the universities featuring mining are taken as an example to verify the feasibility of the method. Results reveal that the integration of ANP, SWOT, and the fuzzy TOPSIS evaluation method is able to qualify the assessment for academic discipline optimization. The specialty structure optimization results should focus on clean, intellig... [more]

The characteristics of solar and wind energy determine that the optimization of a standalone hybrid wind turbine (WT)/photovoltaic panel (PV) system depends on the natural resources of the installation location. In order to ensure system reliability and improve the resource utilization, a method for determining the installed capacity ratio of a hybrid renewable energy system is required. This study proposes a calculation method to optimize the installed capacity ratio, considering the system reliability to meet the needs of the hybrid system to adapt to different natural resources. In this paper, a standalone hybrid WT/PV system to provide electricity for rural areas is designed. Taking the power supply guarantee rate and electricity supply continuity as indicators, the system is simulated by using the Transient System Simulator solver. The results show that the recommended installed capacity ratio of the WT and PV is 5:1 when the total solar irradiation is less than 5040 MJ/(m2·a) and... [more]

Carbon trading is a market-based mechanism towards low-carbon electric power systems. A hy-brid game optimization model is established for deriving the optimal trading price between mi-crogrids (MGs) as well as providing the optimal pricing scheme for trading between the microgrid cluster(MC) and the upper-layer service provider (SP). At first, we propose a robust optimization model of microgrid clusters from the perspective of risk aversion, in which the uncertainty of wind and photovoltaic (PV) output is modeled with resort to the information gap decision theo-ry(IGDT). Finally, based on the Nash bargaining theory, the electric power transaction payment model between MGs is established, and the alternating direction multiplier method (ADMM) is used to solve it, thus effectively protecting the privacy of each subject. It shows that the proposed strategy is able to quantify the uncertainty of wind and PV factors on dispatching operations. At the same time, carbon emission could be effe... [more]

Considering different objectives and using powerful optimization methods in the distribution networks reconfiguration by accurately achieving the best network configuration can further improve network performance. In this paper, reconfiguration of radial distribution networks is performed to minimize the power loss, voltage sag, voltage unbalance, and energy not supplied (ENS) of customers using a new intelligent artificial electric field algorithm-pattern search (AEFAPS) method based on the many-criteria optimization approach. The voltage sag and voltage unbalance are defined as power quality indices and the ENS is the reliability index. In this study, the pattern search (PS) algorithm enhances the artificial electric field algorithm’s (AEFA) flexibility search both globally and locally. AEFAPS is applied to determine the decision variables as open switches of the networks considering the objective function and operational constraints. The proposed methodology based on AEFAPS is perfo... [more]

Based on the square heat-generation body (HGB) with “arrow-shaped” high-thermal-conductivity channel (HTCC) model established in the previous literature, we performed multi-objective optimization (MOO) with maximum temperature difference (MTD) minimization and entropy-generation rate (EGR) minimization as optimization objectives for its performance. Pareto frontiers with optimal set were obtained based on NSGA-II. TOPSIS, LINMAP, and Shannon entropy decision methods were used to select the optimal results in Pareto frontiers, and the deviation index was used to compare and analyze advantages and disadvantages of the optimal results for each decision method. At the same time, multi-objective constructal designs of the “arrow-shaped” HTCC were carried out through optimization of single degree of freedom (DOF), two DOF, and three DOF, respectively, and the thermal performance of the square heat-generation body under optimizations of different DOF were compared. The results show that const... [more]

In Wireless Sensor Networks (WSNs), routing algorithms can provide energy efficiency. However, due to unbalanced energy consumption for all nodes, the network lifetime is still prone to degradation. Hence, energy efficient routing was developed in this article by selecting cluster heads (CH) with the help of adaptive whale optimization (AWOA) which was used to reduce time-consumption delays. The multi-objective function was developed for CH selection. The clusters were then created using the distance function. After establishing groupings, the supercluster head (SCH) was selected using the benefit of a fuzzy inference system (FIS) which was used to collect data for all CHs and send them to the base station (BS). Finally, for the data-transfer procedure, hop count routing was used. An Oppositional-based Whale optimization algorithm (OWOA) was developed for multi-constrained QoS routing with the help of AWOA. The performance of the proposed OWOA methodology was analyzed according to the... [more]

Accurate photovoltaic (PV) power forecasting is indispensable to enhancing the stability of the power grid and expanding the absorptive photoelectric capacity of the power grid. As an excellent nonlinear regression model, the relevance vector machine (RVM) can be employed to forecast PV power. However, the optimization of the free parameters is still a key problem for improving the performance of the RVM. Taking advantage of the strong global search capability, good stability, and fast convergence rate of the sparrow search algorithm (SSA), this paper optimizes the parameters of the RVM by using the SSA to develop an excellent RVM (called SSA-RVM). Consequently, a novel hybrid PV power forecasting model via the SSA-RVM is proposed to perform ultra-short-term (4 h ahead) prediction. In addition, the effects of seasonal distribution and weather type on PV power are fully considered, and different seasonal prediction models are established separately to improve the prediction capability.... [more]

Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that... [more]

Heat transfer is one of the most fundamental engineering subjects and is found in every moment of life. Heat transfer problems, such as heating and cooling, where the transfer of heat between regions is calculated, are problems that can give exact solutions with parametric equations, many of which were obtained by solving differential equations in the past. Today, the fact that heat transfer problems have a more complex structure has led to the emergence of multivariate models, and problems that are very difficult to solve with differential equations have emerged. Optimization techniques, which are also the subject of computer science, are frequently used to solve complex problems. In this study, laminar thermal boundary layers in flow over a flat plate, a sub-problem of heat transfer, is solved with recent metaheuristic algorithms. Teaching learning-based optimization (TLBO), sine cosine optimization (SCO), gray wolf optimization (GWO), whale optimization (WO), salp swarm optimization... [more]

The excitation pulse current used to drive the railgun needs to present very a high magnitude (hundreds of kA) flat-top with very low ripple. At present, the main method to obtain this current is to increase the number of the capacitive pulsed power supply (PPS) modules. However, low utilization and massive volume of the railgun system would occur with this method, hampering the application of railgun. Therefore, the utilization optimization technology of PPS is researched in this paper. In order to obtain highly stable flat-top current, the control strategy of the capacitive PPS is designed, and a new charging voltage configuration is proposed, which significantly decreases the use of the capacitive modules. Besides, a miniaturization transformation scheme of capacitive PPS is proposed based on the control strategy. The result shows that the flat-top current ripple has the biggest influence on the PPS utilization, and the smaller the flat-top current ripple, the lower the utilization.... [more]

The proportional integral derivative (PID) controller is one of the most robust and simplest configuration controllers used for industrial applications. However, its performance purely depends on the tuning of its proportional (KP), integral (KI) and derivative (KD) gains. Therefore, a proper combination of these gains is primarily required to achieve an optimal performance of the PID controllers. The conventional methods of PID tuning such as Cohen-Coon (CC) and Ziegler−Nichols (ZN) generate unwanted overshoots and long-lasting oscillations in the system. Owing to the mentioned problems, this paper attempts to achieve an optimized combination of PID controller gains by exploiting the intelligence of the whale optimization algorithm (WOA) and one of its recently introduced modified versions called improved whale optimization algorithm (IWOA) in an automatic voltage regulator (AVR) system. The stability of the IWOA-AVR system was studied by assessing its root-locus, bode maps, and pole/... [more]

To address the severity of the wind and light abandonment problem and the economics of hydrogen energy production and operation, this paper explores the problem of multi-cycle resource allocation optimization of hydrogen storage systems for coal−wind−solar power generation. In view of the seriousness of the problem of abandoning wind and photovoltaic power and the economy of hydrogen production and operation, the node selection and scale setting issues for hydrogen production and storage, as well as decision-making problems such as the capacity of new transmission lines and new pipelines and route planning, are studied. This research takes the satisfaction of energy supply as the basic constraint and constructs a multi-cycle resource allocation optimization model for an integrated energy system, aiming to achieve the maximum benefit of the whole system. Using data from Inner Mongolia, where wind abandonment and power limitation are severe, and Beijing and Shanxi provinces, where hydrog... [more]

A remodeled sperm swarm optimization (RMSSO) algorithm for a home energy management (HEM) system is proposed, and its real-time efficacy was evaluated using a hardware experimental model. This home environment comprised sixteen residential loads, a smart meter and a Raspberry Pi controller to optimize the energy consumption cost (ECC) in response to the Indian day-ahead pricing (DAP) scheme. A wired/wireless communication network was considered to communicate with the smart meter and controller. To address this optimization problem, the sperm swarm optimization (SSO) algorithm’s constriction coefficient was remodeled to improve its global searching capability and proposed as RMSSO. For the first time, salp swarm optimization (SSA), SSO, and RMSSO algorithms were employed to schedule home appliances in the Indian scenario. To validate the proposed technique’s outcome, the results were compared to those of the conventional SSO and SSA algorithms. This problem was solved using the Python/... [more]

This paper provides insight into the optimal configuration scheme of the grid-connected inverters based on harmonic amplification suppression. The connection of the inverters changes the natural resonance frequencies of the grid. Hence, a reasonable configuration of grid-connected inverters can optimize the impedance distribution and shift the natural resonance frequencies to frequency bands farther away from the harmonic sources. We proposed a scheme of site selection and determination of the number of inverters to suppress harmonic amplification. The resonance frequencies and modal frequency sensitivities (MFSs) were obtained by the resonance modal analysis (RMA). Moreover, the concepts of security region and insecurity region of resonance frequency were illustrated. The grid-connected sites can be obtained by calculating the participation factors (PFs) of the resonance frequencies in the insecurity region. Furthermore, the optimal number was determined by building the Norton equival... [more]

Magnetic gears (MGs) have gained increasing attention due to their sound performance in high torque density and low friction loss. Aiming to maximize the torque density, topology design has been a popular issue in recent years. However, studies on the optimization comparisons of a general MG topology pattern are very limited. This paper proposes a Taguchi-method-based optimization method for a general MG topology pattern, which can cover most of the common types of radially magnetized concentric-surface-mounted MGs (RMCSM-MGs). The Taguchi method is introduced to evaluate the influence of each parameter in MGs. Moreover, the parameter value range is re-examined based on the sensitivity analysis results. The genetic algorithm (GA) method is adopted to optimize the topology pattern in the study.

Parametric design, with its unique scientific and logical nature, is gradually applied in the field of landscape design. Therefore, the GIS (geographic information systems) technology of parametric software was applied to the optimization of traditional landscape architecture, and its practical application quality was discussed. The actual analysis results showed that the evaluation result of parametric design had the highest score of 7.71 in behavioral perception. The overall score was 7.28, showing a high scientific nature. In the evaluation of landscape environmental benefits, after the optimization of landscape greening by parametric design, the air cleanliness and living comfort were generally improved, compared with those before optimization, and the highest values were 11.97 ± 6.01 and 5.86 ± 2.11 respectively. In the evaluation of the economic benefits of gardens, the economic income of gardens in the past 8 years generally increased, reaching the highest of 3.5795 billion yuan... [more]