Dong Sun
Abstract
One of the important and more challenging categories in the smart cities and IoT is to monitor the vehicles plate licenses. This system is a key factor in most of the traffic monitoring in the IoT based smart city applications. In this research, a method for plate license recognition based on optimal ...
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One of the important and more challenging categories in the smart cities and IoT is to monitor the vehicles plate licenses. This system is a key factor in most of the traffic monitoring in the IoT based smart city applications. In this research, a method for plate license recognition based on optimal training of the CNN is proposed. To do this, the configuration and the hyperparameters of the CNN were optimized by a new hybrid optimization including world cup optimizer, whale optimizer, and chaotic theory to obtain a better result with high convergence. Simulations are applied to the UFPR-ALPR dataset and are compared with six popular techniques in terms of accuracy and time. Experimental achievements indicated that the proposed method gives superiority toward the other comparative techniques and is an efficient method for vehicles plate licenses detection.
Roza Gholamin
Abstract
The combined heating, cooling, and power source (CCHP) system is a good tool for the optimal consumption of fossil fuel thermal energy. In CCHPs, the produced waste heat from the hot gases can be recycled for generating power, heat, and water cooling and oil in electrical power generation systems which ...
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The combined heating, cooling, and power source (CCHP) system is a good tool for the optimal consumption of fossil fuel thermal energy. In CCHPs, the produced waste heat from the hot gases can be recycled for generating power, heat, and water cooling and oil in electrical power generation systems which can improve the efficiency of the system to more than 85%. This study presents an optimum structure for the combined heating, cooling, and power source energy flow to decrease the power demand in a building in Yazd city, Iran. In this research, a developed version of collective animal behavior optimizer is introduced to develop the combined heating, cooling, and power source system efficiency compared to the separation generation system. Two different scenarios have been studied for analyzing system efficiency. In one scenario, a constant value (670 kW) was assumed to the capacity while the electric cooling (EC) to cool load ratio (CLR) is assumed variant in a determined range and at the other scenario, an opponent condition with 0.75 constant EC to CLR were assumed. Simulation achievements of the presented technique are put in comparison with standard balanced moth search optimizer and genetic algorithm to indicate the efficiency of the algorithm.
Majid Khayatnezhad
Abstract
Renewable energy technology is quickly developing in last decades due to the increasing attention of countries to sustainable and clean energy, and is constantly evolving in terms of technology. Nevertheless, there are obstacles to this case, such as rising costs and declining reliability due to the ...
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Renewable energy technology is quickly developing in last decades due to the increasing attention of countries to sustainable and clean energy, and is constantly evolving in terms of technology. Nevertheless, there are obstacles to this case, such as rising costs and declining reliability due to the volatility of renewable power resources. Renewable technologies with the aim of using one source to cover other weaknesses, is one way to overcome these obstacles. In the present paper, a technique for optimum sizing of the components in a hybrid renewable power system (HRPS) consists of PV panels, electrolyzer, fuel cell, wind turbines, and the converters has been studied with keeping the value of the Net Present Cost (NPC) minimum. For giving a more efficient power generation cost, the optimization is obtained by using an Adaptive version of Wildebeest Herd Optimizer (AWHO). The main profit of the suggested algorithm is to resolve the main disadvantages of the other metaheuristic from the literature, like reliability, convergence speed, premature convergence, and accuracy, as it is possible. The proposed system is performed to a real-world case study in Yantai, China. Simulation results are put in comparison with several latest methods.
Rolando Simoes
Abstract
The off-grid electricity production is a method of supplying energy to commercial, industrial, residential, and rural or remote regions, which is often the grid connecting is unfeasible because of its difficult regional location and the staggering transmitting cost. In cases like this, the application ...
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The off-grid electricity production is a method of supplying energy to commercial, industrial, residential, and rural or remote regions, which is often the grid connecting is unfeasible because of its difficult regional location and the staggering transmitting cost. In cases like this, the application of local energy help to develop these regions. However, there is always need to a diesel generator to increase the electricity reliability. Hence, in the new method, diesel generators (DG) are coupled with renewable energy techniques like solar photovoltaics which may also use an energy storage system (ESS). The main idea in this paper is to propose a new optimum form for a hybrid battery/PV/diesel generator/ energy storage tool to resolve the load demand in a distant region in Changsha of China. Three main objectives are considered for minimization: annualized system cost, load probability loss, and value of CO2 emissions. To reduce the complexity of the system, ε-constraint technique is used. Here, a new modified bio-inspired algorithm, which is Chaotic Thermal Exchange Optimization algorithm is also applied to solve the optimization problem. Simulation achievements of the proposed system were put in comparison with the achievements of two latest methods to indicate the method effectiveness. The achievements indicated that the total production for the suggested method, PSO-based method, and HOMER are achieved 44051 kWh/yr, 44532 kWh/yr, and 43560 kWh/yr, respectively.
Saleh Mobayen
Abstract
Several methods have been proposed for sale and payment mechanisms in electricity markets; but, appropriate evaluation of this mechanisms is so difficult. The offer cost minimization (OCM) has been presented previously for solving this problem which minimizes the total offer cost through the evaluation ...
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Several methods have been proposed for sale and payment mechanisms in electricity markets; but, appropriate evaluation of this mechanisms is so difficult. The offer cost minimization (OCM) has been presented previously for solving this problem which minimizes the total offer cost through the evaluation by locational marginal prices (LMPs). In recent years, payment cost minimization (PCM) method is suggested which directly minimizes the consumer payments and is more complicated than OCM in terms of framework and converting to single-level linearized optimization problem as well as computational burden. In the current study, a new meta-heuristic optimizer has been proposed for to PCM through solving the joint energy-reserve PCM problem. The achievements are put in comparison with conventional model based offer cost minimization through various studied cases.
Huahui Li; Haoran Fu
Abstract
A hybrid PV/battery/DG energy production system is configured and optimized in this study for powering a network of a remote rural of china. The target of system design is to minimize the system’s fuel costs subject to the load demanded (LD) and several limitations. Thus, the concept comprises ...
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A hybrid PV/battery/DG energy production system is configured and optimized in this study for powering a network of a remote rural of china. The target of system design is to minimize the system’s fuel costs subject to the load demanded (LD) and several limitations. Thus, the concept comprises a problem of optimization which has been solved by a new optimization method using the Sequential Quadratic Programming (SQP) and a modified version of Sparrow Search Optimizer (MSSO). The achievements of the suggested technique are evaluated in various seasons and also in weekends and weekdays to indicate their impact on the operating cost of the PV/Diesel BESS system. The achievements show that in summer and winter, the costs of weekday are lower toward costs of weekend fuel. Moreover, the fuel cost of summer is lower than the fuel costs of winter that is due to lower demand in summer and also the more summer radiation levels mean less usage of auxiliary sources.
