Evaluating Degree of Success in Power Plant Construction Project Based on Fuzzy Neural Network

2008 ◽  
Author(s):  
Yuansheng Huang ◽  
Qingchao Liu ◽  
Zilong Qiu ◽  
Mingyan Wang
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Fuzzy Neural Network ◽  
Construction Project ◽  
Plant Construction ◽  
Fuzzy Neural

scholarly journals Intelligent PV Power Smoothing Control Using Probabilistic Fuzzy Neural Network with Asymmetric Membership Function

2017 ◽  
Vol 2017 ◽  
pp. 1-15
Author(s):  
Faa-Jeng Lin ◽  
Su-Ying Lu ◽  
Jo-Yu Chao ◽  
Jin-Kuan Chang
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Membership Function ◽  
Fuzzy Neural Network ◽  
Storage System ◽  
Minimum Energy ◽  
Energy Storage System ◽  
Smoothing Methods ◽  
Power Smoothing ◽  
Fuzzy Neural

An intelligent PV power smoothing control using probabilistic fuzzy neural network with asymmetric membership function (PFNN-AMF) is proposed in this study. First, a photovoltaic (PV) power plant with a battery energy storage system (BESS) is introduced. The BESS consisted of a bidirectional DC/AC 3-phase inverter and LiFePO4 batteries. Then, the difference of the actual PV power and smoothed power is supplied by the BESS. Moreover, the network structure of the PFNN-AMF and its online learning algorithms are described in detail. Furthermore, the three-phase output currents of the PV power plant are converted to the dq-axis current components. The resulted q-axis current is the input of the PFNN-AMF power smoothing control, and the output is a smoothing PV power curve to achieve the effect of PV power smoothing. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the PV power smoothing control using PFNN-AMF. In addition, a personal computer- (PC-) based PV power plant emulator and BESS are built for the experimentation. From the experimental results of various irradiance variation conditions, the effectiveness of the proposed intelligent PV power smoothing control can be verified.

Research of Power Plant Boiler Control System Based on Compensatory Fuzzy Neural Network

2014 ◽  
Vol 614 ◽  
pp. 203-206 ◽  
Author(s):  
Guo Qiang Hou ◽  
Wei Jie Zhao ◽  
Si Lan Li
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Fuzzy Neural Network ◽  
Fuzzy Inference ◽  
Thermal Power ◽  
Network Control ◽  
Neural Network Control ◽  
Simulation Tools ◽  
Fuzzy Neural ◽  
Fuzzy Network

Considering thermal power plant boiler’s nonlinear, large delay and time-varying, the paper proposes a compensatory fuzzy neural network control based on fuzzy control and neural network control. The compensatory fuzzy neural network is better than the PID controller and general fuzzy network controller in properties by using fuzzy inference and compensatory arithmetic. The paper makes a preliminary simulation using simulation tools of Matlab. And, the superiority of the compensatory fuzzy neural network control is proved by comparing the two kinds of simulation.

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