scholarly journals Optimal PID Tuning of PLL for PV Inverter Based on Aquila Optimizer

2022 ◽  
Vol 9 ◽  
Author(s):  
Zhengxun Guo ◽  
Bo Yang ◽  
Yiming Han ◽  
Tingyi He ◽  
Peng He ◽  
...  
Keyword(s):  
Low Complexity ◽  
Optimization Techniques ◽  
Maximum Deviation ◽  
Phase Detection ◽  
Power Fluctuation ◽  
Proportional Integral ◽  
Pid Tuning ◽  
Pv Inverter ◽  
Grid Connection ◽  
Differential Element

Phase-locked loop (PLL) is a fundamental and crucial component of a photovoltaic (PV) connected inverter, which plays a significant role in high-quality grid connection by fast and precise phase detection and lock. Several novel critical structure improvements and proportional-integral (PI) parameter optimization techniques of PLL were proposed to reduce shock current and promote the quality of grid connection at present. However, the present techniques ignored the differential element of PLL and did not acquire ideal results. Thus, this paper adopts Aquila optimizer algorithm to regulate the proportional-integral-differential (PID) parameters of PLL for smoothing power fluctuation and improving grid connection quality. Three regulation strategies (i.e., PLL regulation, global regulation, and step regulation) are carefully designed to systematically and comprehensively evaluate the performance of the proposed method based on a simulation model in MATLAB/Simulink, namely, “250-kW Grid-Connected PV Array”. Simulation results indicate that PLL regulation strategy can effectively decrease power fluctuation and overshoot with a short response time, low complexity, and time cost. Particularly, the Error(P) and the maximum deviation of output power under optimal parameters obtained by PLL strategy are decreased by 418 W and 12.5 kW compared with those under initial parameters, respectively.

Optimized Dynamic Operation of Fixed-Speed Wind Farms Using Classical and Advanced Controllers

2020 ◽  
Vol 21 (2) ◽  
Author(s):  
Othman A. Omar ◽  
Niveen M. Badra ◽  
Mahmoud A. Attia ◽  
Ahmed Gad
Keyword(s):  
Renewable Energy ◽  
Output Power ◽  
Pitch Angle ◽  
Wind Farm ◽  
Wind Farms ◽  
Optimization Techniques ◽  
Energy Resources ◽  
Voltage Regulator ◽  
Renewable Energy Resources ◽  
Proportional Integral

AbstractElectric power systems are allowing higher penetration levels of renewable energy resources, mainly due to their environmental benefits. The majority of electrical energy generated by renewable energy resources is contributed by wind farms. However, the stochastic nature of these resources does not allow the installed generation capacities to be entirely utilized. In this context, this paper attempts to improve the performance of fixed-speed wind turbines. Turbines of this type have been already installed in some classical wind farms and it is not feasible to replace them with variable-speed ones before their lifetime ends. A fixed-speed turbine is typically connected to the electric grid with a Static VAR Compensator (SVC) across its terminal. For a better dynamic voltage response, the controller gains of a Proportional-Integral (PI) voltage regulator within the SVC will be tuned using a variety of optimization techniques to minimize the integrated square of error for the wind farm terminal voltage. Similarly, the controller gains of the turbine’s pitch angle may be tuned to enhance its dynamic output power performance. Simulation results, in this paper, show that the pitch angle controller causes a significant minimization in the integrated square of error for the wind farm output power. Finally, an advanced Proportional-Integral-Acceleration (PIA) voltage regulator controller has been proposed for the SVC. When the PIA control gains are optimized, they result in a better performance than the classical PI controller.

scholarly journals Demystifying the Random Feature-Based Online Multi-Kernel Learning

2021 ◽  
Author(s):  
Songnam Hong ◽  
Jeongmin Chae
Keyword(s):  
Online Learning ◽  
Low Complexity ◽  
Optimization Techniques ◽  
Streaming Data ◽  
Kernel Learning ◽  
Expert Advice ◽  
Theoretical Contribution ◽  
Learning Tasks ◽  
Feature Based ◽  
Regret Bound

<div>The random feature-based online multi-kernel learning (RF-OMKL) is a promising framework in functional learning tasks. This framework is necessary for an online learning with continuous streaming data due to its low-complexity and scalability. </div><div>In RF-OMKL framework, numerous algorithms can be presented according to an underlying online learning and optimization techniques. The best known algorithm (termed Raker) has been proposed with the lens of the famous online learning with expert advice, where each kernel from a kernel dictionary is viewed as an expert. Harnessing this relation, it was proved that Raker yields a sublinear {\em expert} regret bound, in which as the name implies, the best function is further restricted as the expert-based framework. Namely, it is not an actual sublinear regret bound under RF-OMKL framework. In this paper, we propose a novel algorithm (named BestOMKL) for RF-OMKL framework and prove that it achieves a sublinear regret bound under a certain condition. Beyond our theoretical contribution, we demonstrate the superiority of our algorithm via numerical tests with real datasets. Notably, BestOMKL outperforms the state-of-the-art kernel-based algorithms (including Raker) on various online learning tasks, while having a lower complexity as Raker. These suggest the practicality of BestOMKL.</div>

Performance of Combined PV-Inverter System: Use of Amorphous and Crystalline Panels

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Carlos Armenta-Deu
Keyword(s):  
Theoretical Analysis ◽  
Energy Resource ◽  
Experimental Tests ◽  
Photovoltaic System ◽  
Maximum Deviation ◽  
Photovoltaic Modules ◽  
Pv Inverter ◽  
Pv Panel ◽  
System Use ◽  
Good Agreement

This paper is aimed at analyzing the performance of a combined PV-inverter system connected to an external load using either amorphous or crystalline photovoltaic modules. The analysis is based on previous theoretical analysis that uses the efficiency of the PV panel and of the DC/AC inverter as a key parameter. Different configurations using the same energy resource have been simulated to determine the efficiency of the PV panel, DC/AC inverter, and of the whole system. The theoretical process shows that the global efficiency of the photovoltaic system increased from 87.2% in the case of crystalline panels to 96% for amorphous ones. Experimental tests have been run to validate the theoretical analysis. A very good agreement between theoretical results and experimental data has been found within a standard deviation of σ = 0.633 and a maximum deviation of 1%.

A gray wolf optimized FPD plus (1+PI) multistage controller for AGC of multisource non-linear power system

2019 ◽  
Vol 16 (1) ◽  
pp. 1-13 ◽  
Author(s):  
Prakash Chandra Sahu ◽  
Ramesh Chandra Prusty ◽  
Sidhartha Panda
Keyword(s):  
Power System ◽  
Automatic Generation ◽  
Optimization Techniques ◽  
Dynamic Responses ◽  
Gray Wolf ◽  
Diesel Generator ◽  
Content Type ◽  
Physical Constraints ◽  
Interconnected Power System ◽  
Proportional Integral

Purpose The paper has proposed to implement gray wolf optimization (GWO)-based filter-type proportional derivative with (FPD) plus (1+ proportional integral) multistage controller in a three-area integrated source-type interlinked power network for achieving automatic generation control. Design/methodology/approach For analysis, a three area interconnected power system of which each area comprises three different generating units where thermal and hydro system as common. Micro sources like wind generator, diesel generator and gas unit are integrated with area1, area2 and area3 respectively. For realization of system nonlinearity some physical constraints like generation rate constraint, governor dead band and boiler dynamics are effected in the system. Findings The supremacy of multistage controller structure over simple proportional integral (PI), proportional integral, derivative (PID) and GWO technique over genetic algorithm, differential evolution techniques has been demonstrated. A comparison is made on performances of different controllers and sensitivity analysis on settling times, overshoots and undershoots of different dynamic responses of system as well as integral based error criteria subsequent a step load perturbation (SLP). Finally, sensitive analysis has been analyzed by varying size of SLP and network parameters in range ±50 per cent from its nominal value. Originality/value Design and implementation of a robust FPD plus (1 + PI) controller for AGC of nonlinear power system. The gains of the proposed controller are optimized by the application of GWO algorithm. An investigation has been done on the dynamic performances of the suggested system by conducting a comparative analysis with conventional PID controller tuned by various optimization techniques to verify its supremacy. Establishment of the robustness and sensitiveness of the controller by varying the size and position of the SLP, varying the loading of the system randomly and varying the time constants of the system.

Strategy for Grid-Connection Control of Photovoltaic System

2014 ◽  
Vol 1070-1072 ◽  
pp. 35-38
Author(s):  
Ju Bo Wang ◽  
Xiu Yang ◽  
Wei Bao ◽  
Wen Li Xu
Keyword(s):  
Reactive Power ◽  
Decoupling Control ◽  
Photovoltaic System ◽  
Photovoltaic Systems ◽  
Pv Inverter ◽  
Grid Connection ◽  
Active And Reactive Power ◽  
Power Decoupling ◽  
Simulation And Experiment

With more and more photovoltaic systems connected to the grid, a strategy for grid-connection control is proposed. The topology of PV inverter and photovoltaic inverter and the active and reactive power decoupling control of photovoltaic system are analyzed. The feasibility and effectiveness of the strategy for grid-connection control is verified by simulation and experiment by the case on the RTDS.

scholarly journals Analysis and Simulation of Proportional Derivative and Proportional Integral Derivative Control Systems Using Xcos Scilab

2021 ◽  
Vol 3 (1) ◽  
pp. 36-44
Author(s):  
Edi Kurniawan
Keyword(s):  
Pid Control ◽  
System Response ◽  
Response Analysis ◽  
System Control ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Pid Tuning ◽  
Proportional Integral Derivative Control ◽  
Tuning Process ◽  
Derivative Control

PID (Proportional Integral Derivative) control is a popular control in the industry and aims to improve the performance of a system. This control has controlling parameters, namely Kp, Ki, and Kd which will have a control effect on the overall system response. In this research, P, PD, and PID control simulations with the transfer function of the mass-damper spring as a plant using Xcos Scilab. The method used is the trial and error method by setting and varying the values of the control constants Kp, Ki, and Kd to produce the desired system response. The value adjustment of system control parameters is carried out with several variations, namely Kp control variation, Kp variation to constant Kd, Kd variation to constant Kp, Kp variation to Ki, constant Kd, variation of Ki to Kp, constant Kd and variation of Kd to Kp, Ki constant. The second method is automatic tuning which is done through mathematical calculations to obtain PID control constants, namely Zieglar Nichols PID tuning with the oscillation method. From the system simulation results, the best parameter is obtained through the Zieglar Nichols PID tuning process based on the results of the transient response analysis, namely when the proportional gain value (Kp) is 50. The system performance characteristics produced in the tuning process are 3.994 seconds of settling time at 2.36 seconds research time. resulting in a maximum overshoot value of 3.6% and a peaktime value of 3.994 seconds

scholarly journals Direct Usage of Photovoltaic Solar Panels to Supply a Freezer Motor with Variable DC Input Voltage

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 167
Author(s):  
Ali Farzan Moghaddam ◽  
Alex Van den Bossche
Keyword(s):  
Leakage Current ◽  
Single Phase ◽  
Pulse Width Modulation ◽  
High Efficiency ◽  
Input Voltage ◽  
Boost Converter ◽  
Solar Panels ◽  
Pv Inverter ◽  
Pv Panel ◽  
Grid Connection

In this paper, a single-phase photovoltaic (PV) inverter fed by a boost converter to supply a freezer motor with variable DC input is investigated. The proposed circuit has two stages. Firstly, the DC output of the PV panel that varies between 150 and 300 V will be applied to the boost converter. The boost converter will boost the input voltage to a fixed 300 V DC. Next, this voltage is supplied to the single-phase full bridge inverter to obtain 230 V AC. In the end, The output of the inverter will feed a freezer motor. The PV panels can be stand-alone or grid-connected. The grid-connected PV is divided into two categories, such as with a transformer and without a transformer, a transformer type has galvanic isolation resulting in increasing the security and also provides no further DC current toward the grid, but it is expensive, heavy and bulky. The transformerless type holds high efficiency and it is cheaper, but it suffers from leakage current between PV and the grid. This paper proposes a stand-alone direct use of PV to supply a freezer; therefore, no grid connection will result in no leakage current between the PV and Grid. The proposed circuit has some features such as no filtering circuit at the output of the inverter, no battery in the system, DC-link instead of AC link that reduces no-loads, having a higher efficiency, and holding enough energy in the DC-link capacitor to get the motor started. The circuit uses no transformers, thus, it is cheaper and has a smaller size. In addition, the system does not require a complex pulse width modulation (PWM) technique, because the motor can operate with a pulsed waveform. The control strategy uses the PWM signal with the desired timing. With this type of square wave, the harmonics (5th and 7th) of the voltage are reduced. The experimental and simulation results are presented to verify the feasibility of the proposed strategy.

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