scholarly journals Voltage Stability Enhancement for Microgrid Using an SVC

2020 ◽  
Vol 18 (4.2) ◽  
pp. 39
Author(s):  
Dinh-Nhon Truong ◽  
Mi Sa Nguyen Thi ◽  
Van-Tri Bui ◽  
Thanh-Liem Tran
Keyword(s):  
Voltage Stability ◽  
Fuzzy Inference ◽  
Operating Conditions ◽  
Small Scale ◽  
Solar Photovoltaic ◽  
Inference System ◽  
Damping Characteristics ◽  
Voltage Stability Enhancement ◽  
Simulation Results ◽  
Stability Enhancement

This paper presents comparative simulation results of a Microgrid (MG) system using a Static Var Compensator (SVC) for improving the voltage stability of the studied system. An Adaptive Neural Fuzzy Inference System (ANFIS) controller is designed based on the feedback signals to control the proposed SVC. For simplicity, the studied MG system can be modeled as an equivalent small scale wind turbine generator (WTG) combine with a Solar Photovoltaic (PV) and a Battery that connected to the common AC bus. A time-domain approach based on nonlinear model simulations is systematically performed. By observing the simulation results it can be concluded that the designed ANFIS controller for SVC can offer better damping characteristics of the studied MG system under severe operating conditions

scholarly journals Application of An Adaptive Network-based Fuzzy Inference System to Control a Hybrid Solar and Wind Grid-Tie Inverter

2021 ◽  
Vol 11 (5) ◽  
pp. 7673-7677
Author(s):  
D. N. Truong ◽  
V. T. Ngo ◽  
M. S. N. Thi ◽  
A. Q. Hoang
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Short Circuit ◽  
Operating Conditions ◽  
Maximum Power ◽  
Pv System ◽  
Adaptive Network ◽  
Inference System ◽  
Simulation Results ◽  
Power Point

In this paper, the application of an Adaptive Network-based Fuzzy Inference System (ANFIS) to control a hybrid solar and wind grid-tie inverter in order to reduce power oscillations and enhance power quality is presented. To extract the maximum power from the PV system, a Perturb and Observe (P&O) algorithm is presented that tracks the Maximum Power Point (MPP). Time-domain simulation results of the studied system are performed in MATLAB/SIMULINK under different operating conditions such as changing irradiation and short-circuit faults in the power grid. From the simulation results, it can be concluded that the designed ANFIS controller and the proposed P&O algorithm perform better than the traditional PI controller and improve transient responses under severe operating conditions.

An Intuitionistic Fuzzy Based Novel Approach to CPU Scheduler

2020 ◽  
Vol 16 (4) ◽  
pp. 316-328
Author(s):  
Supriya Raheja
Keyword(s):  
Fuzzy Inference ◽  
The Other ◽  
Simulation Environment ◽  
Inference System ◽  
Intuitionistic Fuzzy ◽  
Novel Approach ◽  
Continuous Feedback ◽  
Simulation Results ◽  
Effectiveness And Efficiency ◽  
Unique Capability

Background: The extension of CPU schedulers with fuzzy has been ascertained better because of its unique capability of handling imprecise information. Though, other generalized forms of fuzzy can be used which can further extend the performance of the scheduler. Objectives: This paper introduces a novel approach to design an intuitionistic fuzzy inference system for CPU scheduler. Methods: The proposed inference system is implemented with a priority scheduler. The proposed scheduler has the ability to dynamically handle the impreciseness of both priority and estimated execution time. It also makes the system adaptive based on the continuous feedback. The proposed scheduler is also capable enough to schedule the tasks according to dynamically generated priority. To demonstrate the performance of proposed scheduler, a simulation environment has been implemented and the performance of proposed scheduler is compared with the other three baseline schedulers (conventional priority scheduler, fuzzy based priority scheduler and vague based priority scheduler). Results: Proposed scheduler is also compared with the shortest job first CPU scheduler as it is known to be an optimized solution for the schedulers. Conclusion: Simulation results prove the effectiveness and efficiency of intuitionistic fuzzy based priority scheduler. Moreover, it provides optimised results as its results are comparable to the results of shortest job first.

Voltage stability enhancement using thermostatically controlled appliances as a comfort-constrained virtual generator

2015 ◽  
Vol 25 (12) ◽  
pp. 3509-3522 ◽  
Author(s):  
Dan Wang ◽  
Hongjie Jia ◽  
Chengshan Wang ◽  
Ning Lu ◽  
Menghua Fan ◽  
...  
Keyword(s):  
Voltage Stability ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement

Intelligent cooperative collision avoidance via fuzzy potential fields

Robotica ◽  
2021 ◽  
pp. 1-20
Author(s):  
Daegyun Choi ◽  
Anirudh Chhabra ◽  
Donghoon Kim
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Fuzzy Inference ◽  
Potential Fields ◽  
Rule Base ◽  
Local Minima ◽  
Inference System ◽  
Aerial Vehicles ◽  
Different Shapes ◽  
Simulation Results

Summary This paper proposes an intelligent cooperative collision avoidance approach combining the enhanced potential field (EPF) with a fuzzy inference system (FIS) to resolve local minima and goal non-reachable with obstacles nearby issues and provide a near-optimal collision-free trajectory. A genetic algorithm is utilized to optimize parameters of membership function and rule base of the FISs. This work uses a single scenario containing all issues and interactions among unmanned aerial vehicles (UAVs) for training. For validating the performance, two scenarios containing obstacles with different shapes and several UAVs in small airspace are considered. Multiple simulation results show that the proposed approach outperforms the conventional EPF approach statistically.

Voltage Stability Enhancement of the Uganda Power System Network

2021 ◽  
Author(s):  
Rebeccah Kyomugisha ◽  
Christopher Maina Muriithi ◽  
Milton Edimu
Keyword(s):  
Power System ◽  
Voltage Stability ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement

scholarly journals An Adaptive Operation Strategy for Voltage Stability Enhancement in DMFCs

2018 ◽  
Author(s):  
Qinwen Yang ◽  
Xu-Qu Hu ◽  
Ying Zhu ◽  
Xiu-Cheng Lei ◽  
Xing-Yi Wang
Keyword(s):  
Voltage Stability ◽  
Optimization Method ◽  
Operation Strategy ◽  
Practical Applications ◽  
Operating Current ◽  
Voltage Stability Enhancement ◽  
Voltage Deviation ◽  
Adaptive Operation ◽  
Underlying Mechanisms ◽  
Stability Enhancement

An adaptive operation strategy for on-demand control of DMFC system is proposed as an alternative method to enhance the voltage stability. Based on a single-cell DMFC stack, a newly simplified semi-empirical model is developed from the uniform-designed experimental results to describe the I-V relationship. Integrated with this model, the multi-objective optimization method is utilized to develop an adaptive operation strategy. Although the voltage instability is frequently encountered in unoptimized operations, the voltage deviation is successfully decreased to a required level by adaptive operations with operational adjustments. Moreover, the adaptive operations are also found to be able to extend the range of operating current density or to decrease the voltage deviation according to ones requirements. Numerical simulations are implemented to investigate the underlying mechanisms of the proposed adaptive operation strategy, and experimental adaptive operations are also performed on another DMFC system to validate the adaptive operation strategy. Preliminary experimental study shows a rapid response of DMFC system to the operational adjustment, which further validates the effectiveness and feasibility of the adaptive operation strategy in practical applications. The proposed strategy contributes to a guideline for the better control of output voltage from operating DMFC systems.

scholarly journals Galerkin method-based model predictive control for mid-long term voltage stability enhancement

2020 ◽  
Vol 14 (22) ◽  
pp. 5302-5309
Author(s):  
Bingqing Xia ◽  
Hao Wu ◽  
Danfeng Shen ◽  
Xiang Zheng ◽  
Wen Hua ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Galerkin Method ◽  
Predictive Control ◽  
Voltage Stability ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement

scholarly journals Lifetime Prediction for a Cell-on-Board (COB) Light Source Based on the Adaptive Neuro-Fuzzy Inference System (ANFIS)

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
İsmail Kıyak ◽  
Gökhan Gökmen ◽  
Gökhan Koçyiğit
Keyword(s):  
Fuzzy Inference ◽  
Prediction Method ◽  
Operating Conditions ◽  
Lifetime Prediction ◽  
Statistical Characteristics ◽  
Ambient Conditions ◽  
Inference System ◽  
Initial Task ◽  
Neuro Fuzzy ◽  
A Cell

Predicting the lifetime of a LED lighting system is important for the implementation of design specifications and comparative analysis of the financial competition of various illuminating systems. Most lifetime information published by LED manufacturers and standardization organizations is limited to certain temperature and current values. However, as a result of different working and ambient conditions throughout the whole operating period, significant differences in lifetimes can be observed. In this article, an advanced method of lifetime prediction is proposed considering the initial task areas and the statistical characteristics of the study values obtained in the accelerated fragmentation test. This study proposes a new method to predict the lifetime of COB LED using an artificial intelligence approach and LM-80 data. Accordingly, a database with 6000 hours of LM-80 data was created using the Neuro-Fuzzy (ANFIS) algorithm, and a highly accurate lifetime prediction method was developed. This method reveals an approximate similarity of 99.8506% with the benchmark lifetime. The proposed methodology may provide a useful guideline to lifetime predictions of LED-related products which can also be adapted to different operating conditions in a shorter time compared to conventional methods. At the same time, this method can be used in the life prediction of nanosensors and can be produced with the 3D technique.

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