A fuzzy based control method for isolated power utility connected PV-diesel hybrid system to reduce frequency deviation

2008 ◽  
Author(s):  
Manoj Datta ◽  
Tomonobu Senjyu ◽  
Atsushi Yona ◽  
Toshihisa Funabashi ◽  
Chul-Hwan Kim
Keyword(s):  
Hybrid System ◽  
Control Method ◽  
Frequency Deviation ◽  
Power Utility

scholarly journals Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

2015 ◽  
Vol 64 (2) ◽  
pp. 291-314 ◽  
Author(s):  
Maziar Izadbakhsh ◽  
Alireza Rezvani ◽  
Majid Gandomkar
Keyword(s):  
Fuzzy Logic ◽  
Wind Speed ◽  
Dynamic Response ◽  
Wind Turbine ◽  
Hybrid System ◽  
Pitch Angle ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Control Technique ◽  
Power Curves

Abstract In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator

Multivariable predictive functional control of a compound power-split hybrid electric vehicle

2021 ◽  
pp. 095440702110466
Author(s):  
Ji Gao ◽  
Diming Lou ◽  
Tong Zhang ◽  
Liang Fang ◽  
Yunhua Zhang
Keyword(s):  
Hybrid System ◽  
Hybrid Electric Vehicle ◽  
Control Method ◽  
Multiple Input Multiple Output ◽  
Area Network ◽  
Control Effect ◽  
Decoupling Method ◽  
Input Multiple Output ◽  
Objective Control ◽  
Pure Delay

The Corun hybrid system (CHS) is a deeply coupled multiple-input–multiple-output (MIMO) hybrid system. The two inputs are the torques of the two motors. The two outputs are the carrier speed and transmission output torque. Using the traditional control method, the multi-objective control quality cannot be guaranteed because of the adopted static decoupling method and proportional–integral–derivative (PID) controllers. In this paper, the problems of the traditional control method are carefully analyzed, and a new control method is proposed. Instead of static decoupling, dynamic decoupling is adopted to improve the decoupling control effect. A predictive functional controller instead of a PID controller is adopted to deal with the pure delay caused by controller area network (CAN) communication. The tracking effect of the target value is further improved by predictive functional controllers. For the two decoupled subsystems, that is, the integral system and the second-order underdamped system, two predictive functional controllers are designed. The new control method was verified by simulations and tests. The results show that the new control method is superior to the traditional control method for CHS.

scholarly journals An Optimal Hybrid Control Method for Energy-Saving of Chilled Water System in Central Air Conditioning

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Yan Zhang ◽  
Xiaoli Chu ◽  
Yongqiang Liu
Keyword(s):  
Energy Saving ◽  
Hybrid System ◽  
Air Conditioning ◽  
Control Method ◽  
System Modeling ◽  
Water System ◽  
Variable Frequency ◽  
Optimum Control ◽  
Central Air Conditioning ◽  
Frequency Behavior

Chilled water system of central air conditioning is a typical hybrid system; variable frequency behavior with amplitude limited of pumps reflects continuous and discrete dynamic characteristics. The way of energy-saving is variable water volume, via variable frequency behavior of pumps to gain adjustment of power consumption. Facing the situation of the variable frequency pumps with parallel operation, single continuous or discrete modeling cannot reflect the hybrid features. Thus, the control method will have some questions, such as bad energy-saving effect, difficult accurate adjustment of cold capacity, and low running energy efficiency. However, hybrid system modeling can reflect hybrid dynamic behavior of pumps, which is combining continuous and discrete features. The questions of nonlinear and multiparameters can be solved by control method based on hybrid system. Here, an optimum control method is proposed with the principle of the minimum, by setting the minimum power consumption as the performance function in fixed time, which realizes variable control of pumps and accurate adjustment of temperature inside room. At last, it shows the system characteristics and energy-saving affection by hybrid system modeling and the optimum control method.

scholarly journals Frequency regulation strategy of photovoltaic system based on system identification

2021 ◽  
Vol 252 ◽  
pp. 02082
Author(s):  
Li Zhenjie ◽  
Hou Guangsong ◽  
Cheng Zhaolong ◽  
Niu Wenhui ◽  
Hu Guohua
Keyword(s):  
Power Generation ◽  
System Identification ◽  
Large Scale ◽  
Control Method ◽  
Power Grid ◽  
Frequency Deviation ◽  
Photovoltaic System ◽  
Frequency Regulation ◽  
Photovoltaic Power ◽  
System Frequency

The large-scale grid connection of photovoltaic power generation results in the power system frequency fluctuation and frequency regulation capacity decline, which endangers the dynamic security of power grid frequency. In order to reduce the frequency deviation of power grid and tap the potential of photovoltaic power generation participating in frequency regulation, a control method of photovoltaic power participating in frequency regulation of power grid is proposed in this paper. The maximum allowable power of photovoltaic power is predicted through system identification, and the load shedding rate is determined based on this, and the output power is corrected according to the system frequency deviation to participate in frequency regulation of power grid. The model based on MATLAB Simulation results shows the effectiveness of the proposed method.

scholarly journals Optimal Energy Control of Battery Hybrid System for Marine Vessels by Applying Neural Network Based on Equivalent Consumption Minimization Strategy

2021 ◽  
Vol 9 (11) ◽  
pp. 1228
Author(s):  
Seongwan Kim ◽  
Jongsu Kim
Keyword(s):  
Neural Network ◽  
Hybrid System ◽  
Control Method ◽  
The State ◽  
State Of Charge ◽  
Energy Control ◽  
Optimal Energy ◽  
The Neural Network ◽  
Equivalent Consumption Minimization Strategy ◽  
Hidden Layer

This paper introduces an optimal energy control method whose rule-based control employs the equivalent consumption minimization strategy as the design standard to support a neural network technique. Using the proposed control method, the output command values for each power source based on the load of the ship and the state of charge of the battery satisfy the target of energy optimization. Based on the rules, the load of the ship and the state of charge of the battery were the input in the neural network, and the outputs of two generators were recorded as the output values of the neural network. To optimize the weights of the neural network and reduce the error between the predicted values and results, the Bayesian regularization method was employed, and a single hidden layer with 20 nodes, 2 input layers, and 2 output layers were considered. For the hidden layer, the tansigmoid function was applied, and for the activation functions of the output layers, linear functions were adopted considering the correlation between the input and output data used for training the neural network. The propulsion motor was fitted with a speed controller to ensure a stable speed, and a torque load was applied on the propulsion motor. To verify the accuracy of the neural network learning, a generator–battery hybrid system simulation was conducted using MATLAB Simulink, and the neural network learned values were compared with the generator output command values obtained based on the load of the ship and the battery state of charge. Additionally, it was confirmed that the generator command values were consistent with the neural network learned values, and the stability of the system was maintained by controlling the speed, voltage, and current control of the propulsion motor under various loads of the ship and different battery charge statuses.

Sign in / Sign up

Export Citation Format

Share Document