This paper presents an optimal control of steady-state disturbances in the power flow of microgrids. In microgrid operations, the variation in loads induces instability in line-parameters such as voltage and frequency...
This paper presents an optimal control of steady-state disturbances in the power flow of microgrids. In microgrid operations, the variation in loads induces instability in line-parameters such as voltage and frequency, resulting in a decrease in power quality and overall system stability. To address these challenges, a Smell Agent Symbiotic Organism Search (SASOS) algorithm, which integrates Smell Agent Optimizer (SAO) and Symbiosis Organism Search (SOS) algorithms, was codified in the design of an optimized controller to improve power quality control. The SASOS, SAO, and SOS algorithms were applied in the Microgrid’s Centralized controller (MCC) for the control of steady-state disturbances. The simulation results showed the viability of the MCC-SASOS technique compared to the MCC-SOS, MCC-SAO, and MCC techniques.
Today's world is the world of BIG DATA, and this issue is inevitable regarding the processes of teaching-learning and its analysis. In particular, we know that the amount of reliable data has grown significantly d...
Today's world is the world of BIG DATA, and this issue is inevitable regarding the processes of teaching-learning and its analysis. In particular, we know that the amount of reliable data has grown significantly due to the exponential use of online education tools such as LMS and LCMS in the teaching and learning processes. Based on this, the current research seeks to use these data in learning analytics. For this purpose, this research has tried to convert the data of the Moodle system with the help of Microsoft Power BI into dynamic and interactive visualized reports for the decision-making of the three main stakeholders of education, i.e., managers, professors, and students. To examine these results realistically, all cases were made in the e-learning course at the University of Tehran.
Automated visual inspection of on-and offshore wind turbines using aerial robots provides several benefits, namely, a safe working environment by circumventing the need for workers to be suspended high above the groun...
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In this paper, an automated design procedure of a cascoded-inverter-based charge-sensitive amplifier (CSA) using the g m /I D method and particle swarm optimization (PSO) is presented. Assuming certain fixed values, ...
In this paper, an automated design procedure of a cascoded-inverter-based charge-sensitive amplifier (CSA) using the g m /I D method and particle swarm optimization (PSO) is presented. Assuming certain fixed values, such as transistors' length, supply voltage, feedback resistance, and input, output and feedback capacitances, the algorithm is able to find the proper transistors' width and cascode biasing voltages, to meet specified requirements, such as power consumption, gain, bandwidth, input/output DC level and input-referred noise. A CSA designed in 28 nm CMOS technology using the presented method achieves 500 V/V gain, 3.7 MHz bandwidth and 71e − ENC, consuming 2.2 μW of power from a 1.1 V supply.
Fractional-order models have been used in recent years to model the number of processes and applications like boilers, supercapacitors, power electronic devices, permanent magnet synchronous motor (PMSM) speed servo s...
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The article examines the use of Gaussian Process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian Pro...
The article examines the use of Gaussian Process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian Process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working point or faulty power measurements. The article discusses the characteristics and benefits of Gaussian Process Models and how they can be utilized to improve: the reliability and accuracy of nuclear power plant anomaly detection, fault diagnosis and decision making process in states of emergency. Overall, this paper highlights the capabilities of Gaussian Process Models to enhance the safety, reliability and efficiency of nuclear power plants. The results of this study are expected to provide valuable insights for engineers and researchers in the fields of controlengineering and nuclear power.
Email classification is essential to the trouble of email and pattern recognition. Nowadays, a number of unsolicited messages are circulated over the internet. While plenty of machine learning techniques are a success...
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We study dynamic wireless charging for Electric Vehicles (EVs) on electrified highways where EVs are charged while in motion. Our focus is on the cost-minimization scheduling of EV charging based on EV mobility states...
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ISBN:
(数字)9798350381832
ISBN:
(纸本)9798350381849
We study dynamic wireless charging for Electric Vehicles (EVs) on electrified highways where EVs are charged while in motion. Our focus is on the cost-minimization scheduling of EV charging based on EV mobility states, charging demands, travel plans, available distributed renewables, and power constraints of the distribution systems. As a Markov decision process with uncountable action space that couples stochasticities in charging demands, vehicle mobilities, and renewable resources, standard dynamic programming and approximation approaches face exponentially growing complexity and modeling uncertainties. By exploiting the linear network topology when EVs are on a highway, this work reveals a threshold structure of the optimal charging policy and develops a reinforcement learning approach for uncertainty models, resulting in a scalable EV charging solution. The proposed EV charging algorithm outperforms multiple charging benchmarks by 4.7-52.4% cost reduction.
In this article, we compare LabVIEW, Matlab, and Python in the scope of data acquisition. We built a simple sine wave generator and used the USB-6361 multifunctional I/O device from NI to measure. We will measure the ...
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Various control methods have been presented to prevent the occurrence of instability in power systems, among which, it seems that methods based on the special protection system (SPS) are more effective and efficient t...
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Various control methods have been presented to prevent the occurrence of instability in power systems, among which, it seems that methods based on the special protection system (SPS) are more effective and efficient than other ones. In this article, a SPS using the capabilities of large-scale photovoltaic power plants (LSPVPPs) is presented to prevent frequency increase and instability in power systems. According to the presented algorithm, when frequency increases, the proposed SPS uses the ability of photovoltaic power plants to quickly change their generation powers based on the operating point and frequency changes to prevent frequency instability. To confirm the proposal, LSPVPPs along with their controllers are modeled in the DSL environment of DIgSILENT PowerFactory software. The proposed SPS is implemented and tested on the IEEE 39-bus test system and the results of dynamic simulations show that this SPS prevents frequency instability in different conditions by taking timely measures.
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