Voltage and frequency regulation based DG unit in an autonomous microgrid operation using Particle Swarm Optimization (original) (raw)
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Power quality improvement in autonomous microgrid operation using particle swarm optimization
2011 IEEE PES Innovative Smart Grid Technologies, 2011
This paper presents an optimal power control strategy for an autonomous microgrid operation based on a realtime self-tuning method. The purpose of this work is to improve the quality of power supply where Distributed Generation (DG) units are connected to the grid. Dynamic response and harmonics distortion are the two main performance parameters which are considered in this work, particularly when the microgrid is islanded. The controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the system. The results show that the proposed controller provides an excellent dynamic response with acceptable harmonics level.
International Journal of Electrical and Computer Engineering (IJECE), 2021
In this study, a control strategy based on the self-tuning method and synchronous reference frame (SRF) with PI regulator is proposed to achieve optimum quality of power in an autonomous microgrid (MG). The MGS is based on multiple distributed generation (DG) connected with 120 kV power grid. The proposed system is first simulated with fixed gain values for PI controller which are not optimal for sudden changes in the system i.e. transition of MG to islanding mode, load variations. So, the particle swarm optimization (PSO) has been utilized for tuning of PI controller parameters which ensure flexible performance and superior quality of power. The principal parameters considered in this study are, regulation of voltage and frequency, steady-state and dynamic response and harmonic distortion, mainly when microgrid is islanded. The performance of PI and PI-PSO is compared in this study by simulating AC microgrid in the MATLAB/Simulink environment. Summarized results of the system are provided to authenticate viability of proposed arrangement. The proposed controller performs intelligently while regulating voltage and frequency of the MGS and utility system. Keywords: Autonomous microgrid Current controller Islanding mode PSO This is an open access article under the CC BY-SA license.
Stability analysis of an autonomous microgrid operation based on Particle Swarm Optimization
2012 IEEE International Conference on Power System Technology (POWERCON), 2012
This paper presents the stability analysis for an in verter based Distributed Generation (DG) unit in an autonomous microgrid operation. The small-signal model of the controlled Voltage Source Inverter (VSI) system is developed in order to investigate the dynamic stability for the given operating point and under the proposed power controller. This model includes all the details of the proposed controller, while no switching actions are considered. System oscillatory modes and the sensitivity to the control parameters are the main performance indices which are considered, particularly when the micro grid is islanded or under the load change condition. In this work, the proposed power controller is composed of an inner current control loop and an outer power control loop, both based on a synchronous reference frame and conventional PI regulators. These controllers also utilize the Particle Swarm Optimization (PSO) for real-time self-tuning in order to improve the quality of the power supply. The complete small-signal model is linearized and used to define the system state matrix which is employed for eigenvalue analysis. The results prove that the stability analysis is fairly accurate and the controller offers reliable system's operation.
IEEE Access
An efficient power control technique for inverter-based distributed generation (DG) in an islanded microgrid is investigated in this work. The objective is to raise the caliber of the electricity pumped from network-connected DGs. The characteristics that are taken into consideration include voltage and frequency control, dynamic response, and steady-state response, particularly when the microgrid is operating in island mode or when there is a load change. The control method consists of an internal current control loop and an external power control loop based on a synchronous reference frame and a conventional PI controller. The power controller is designed based on voltage-frequency (VF) control. In addition, an intelligent search technique that combines Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is utilized to automatically modify power controller parameters. The control technique in this research is that the DG modifies its control mode to modify the system voltage and frequency when the microgrid is islanded or load conditions change. The simulation results in MATLAB/SIMULINK software show that the proposed control system has been able to improve the power quality well.
PSO Algorithm for an Optimal Power Controller in a Microgrid
IOP Conference Series: Earth and Environmental Science
This paper presents the Particle Swarm Optimization (PSO) algorithm to improve the quality of the power supply in a microgrid. This algorithm is proposed for a real-time selftuning method that used in a power controller for an inverter based Distributed Generation (DG) unit. In such system, the voltage and frequency are the main control objectives, particularly when the microgrid is islanded or during load change. In this work, the PSO algorithm is implemented to find the optimal controller parameters to satisfy the control objectives. The results show high performance of the applied PSO algorithm of regulating the microgrid voltage and frequency.
European Transactions on Electrical Power, 2011
Microgrids are state-of-the-art power distribution networks consisting of multiple distributed generators (DGs) and sensitive power loads. The goal of microgrid operation is to provide reliable and high-quality electric power to loads regardless of abnormal cases such as faults or loss-of-mains (islanding). This paper presents power control methods to coordinate multiple microgrid generators for both grid-connected and autonomous modes. To maintain required control performance and power quality during operating condition changes, hard toil of fine-tuning control parameters is required. This paper proposes an effective control parameter-tuning method using the particle swarm optimization (PSO) algorithm and gain-scheduling method. System requirements such as power quality regulation and load following performance are reflected in the cost function. The optimization algorithm implementation with time-domain simulation model is also explained.
Optimal Control of Islanded Micro grid Using Particle Swarm Optimization Algorithm
International Journal of Industrial Electronics, Control and Optimization (IECO), 2018
Microgrid is defined as a controllable unit which consists of Distributed Generations (DG), loads, energy storages and control devices. Microgrid has two operation modes including grid connected mode and islanding mode. In grid connected mode, voltage and frequency of microgrid is controlled by main grid and DG’s supply total or part of the loads. In the islanding mode, the microgrid is disconnected from main grid because of a fault or a preplanned switching in connecting line. In this mode, DG’s should satisfy the power demand of sensitive loads in microgrid. Since the only generation units in an islanded microgrid are existing DG units which usually are from several types. Consequently besides feeding total loads, voltage and frequency of microgrid should be controlled by these DG units. Hence, the microgrid could supply high power quality and reliability to customers. This paper presents an optimization method to optimize the parameters of the Microgrid controller in islanding mode. The controller optimal parameters have been obtained by using the particle swarm optimization (PSO). This is done based on minimization of the error in the current and voltage controllers. Finally, simulation has been carried out to verify the effectiveness of the optimized controller. Stability analysis of the controller is verified using classical approach.
The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS), 2023
Due to the increasing number of distributed generation units being used in remote regions, the need for reliable and flexible operation of these systems has led to the development of microgrid technology. When a microgrid operates in an autonomous mode, it can experience unpredictable loads and other factors that can affect its operation. An optimal control mechanism is required to maintain the system's stability. Hence, in this paper optimal control strategy of autonomous microgrid for power quality improvement is presented. A test case of single phase 3.5 kW photovoltaic (PV) system based autonomous micro grid is considered. Particle swarm optimization (PSO) and Harris hawks optimization (HHO) optimal control strategies are implemented under standard test case and variable test cases. In all the cases PV mean voltage-Vmpv (V), PV mean current-Impv (A), RMS voltage-Vrms (V), RMS current-Irms (A), mean PV power-Ppv (W), autonomous grid power-Pg (W), efficiency (%), total harmonic distortion (THD) (%), inverter losses (%) are evaluated. In all the cases HHO optimal control strategy for autonomous microgrid exhibits the best performance in comparison with PSO optimal control strategy. The inverter efficiency is improved, inverter losses are reduced and the THD is improved.
IEEE Access, 2020
The increasing penetration of Microgrids (MGs) into existing power systems and ''plug and play'' capability of Distributed Generators (DGs) causes large overshoots and settling times along with various power quality issues such as voltage and frequency flickers, current harmonics and short current transients. In this context, over the past few years, considerable research has been undertaken to investigate and address the mentioned issues using different control schemes in conjunction with soft computational techniques. The recent trends and advancements in the field of Artificial Intelligence (AI) have led the development of Swarm Intelligence (SI) based optimized controllers for smooth Renewable Energy Sources (RES) penetration and optimal voltage, frequency, and power-sharing regulation. Moreover, the recent studies have proved that the SI-based controllers provide enhanced dynamic response, optimized power quality and improved the dynamic stability of the MG systems as compared to the conventional control methods. Their importance in modern AC MG architectures can be judged from the growing number of publications in the recent past. However, literature, pertaining to SI applications to AC MG, is scattered with no comprehensive review on this significant development. As such, this study provides an overview of 15 different SI optimization techniques as applied to AC MG controls from 43 research publications including a detailed review of one of the elementary and most widely used SI based metaheuristic optimization algorithms called Particle Swarm Optimization (PSO) algorithm. This comprehensive review provides a valuable one-stop source of knowledge for the researchers and experts working on SI controller's applications for AC MG dynamic response and power quality improvements.
Processes, 2019
The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not share any connection with the utility grid. Hence, a proper control architecture of islanded MG is essential to control the voltage and frequency, including the power quality and optimal transient response during different operating conditions. Therefore, this study proposes an intelligent and robust controller for islanded MG, which can accomplish the above-mentioned tasks with the optimal transient response and power quality. The proposed controller utilizes the droop control in addition to the back to back proportional plus integral (PI) regulator-based voltage and current controllers in order to accomplish the mentioned control objectives efficiently. Furthermore, the intelligence of the one of the most modern s...