Stability analysis of an autonomous microgrid operation based on Particle Swarm Optimization (original) (raw)

Voltage and frequency regulation based DG unit in an autonomous microgrid operation using Particle Swarm Optimization

International Journal of Electrical Power & Energy Systems, 2013

This paper presents an optimal power control strategy, for an inverter based Distributed Generation (DG) unit, in an autonomous microgrid operation based on real-time self-tuning method. This research seeks to improve the quality of power supplied by DG units connected to the grid. Voltage and frequency regulation, dynamic response, steady-state response, and harmonic distortion are the main performance parameters considered, particularly when the microgrid is islanded or under the load change condition. The controller scheme comprises an inner current control loop and an outer power control loop based on a synchronous reference frame and conventional PI regulators. The power controller is designed for voltage-frequency (Vf) power control mode. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that when the microgrid is islanded or under load change condition, the DG unit adopts the Vf control mode in order to regulate the system voltage and frequency. The simulation results show that the proposed controller provided an excellent response to satisfy the power quality requirements and proved the validity of the proposed strategy.

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.

Stability Analysis and Dynamic Behavior Improvement of a Stand-alone AC Microgrid

Distributed generations have been playing an important role in smart power grids to improve grid's performance, reliability and efficiency and greenhouse gas issues. Stability analysis for voltage source inverters is proposed in this paper to investigate microgrid's stability. In first step, pole placement is implemented in order to find controllers parameters. Particle swarm optimization is applied to find controller parameters. It is shown that although the system is stable for wide area of load variations, the system performance is not that good; therefore, an objective function is proposed to address both stability and performance improvement over wide range of load changes.

IMPROVING POWER SYSTEM STABILITY IN MICRO-GRID SYSTEM USING PARTICLE SWARM OPTIMIZATION (PSO) TECHNIQUE

International Journal of Engineering and Scientific Research, 2016

Among many problems in micro-grids is the voltage and frequency control in isolated mode especially during islanding process. Neural networks have been successfully used for character recognition, image compression, and stock market prediction, but there is no direct application related to controlling distributed generations of Micro-grid. For this reason, this work was decided on, with the aim of controlling diesel generator outputs. Firstly primary controlling quickly provides the required power of micro-grid in isolated mode. Then in next step controllable distributed generations play the role of secondary controllers. This work uses Artificial Neural Network (ANN) for considering of active and reactive power inter-effect onvoltage and frequency. It examines the neural network algorithm that can be utilized for alleviating voltage and frequency issues of Micro-grid. MATLAB and Particle Swarm Optimization (PSO) are used for training neural network and simulating the Micro-grid model respectively. The Feed forward Back-propagation algorithm is used in this study and the Microgrid consists of wind, solar, and diesel power generations, and battery energy storage system(BESS). Neural network indicates how much real and reactive power needed from each generator so as to improves the stability in the system..

Control parameter optimization for multiple distributed generators in a microgrid using particle swarm optimization

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 PI Based Secondary Control for Autonomous Micro-grid via Particle Swarm Optimization Technique

2018 Twentieth International Middle East Power Systems Conference (MEPCON), 2018

Hybrid micro-grids require harmony operation of renewable energy resources based voltage source inverters (VSIs) in grid-tied as well as islanded modes. In this paper, the modeling, analysis, and control strategy of VSIs based autonomous micro-grid are developed. An integrated control system for autonomous micro-grid is carried out including two control levels. The primary control level is comprised of the current and voltage inner control loops, the virtual inductor loops, and the droop control loops. This control level is necessary to regulate voltage and frequency, and also to achieve accurate power sharing among the paralleled distributed generators (DGs). However, the secondary control level is employed to eliminate the voltage magnitude and angular frequency deviations produced by primary control level. The parameters of secondary controllers are optimized using particle swarm optimization technique to achieve good dynamic and steady state performance for micro-grid voltage and frequency. Two micro-grid structures are modeled and simulated in MATLAB environment to accomplish this study. The first structure consists of only one distributed generation unit, while the second contains four DGs. Each structure is tested with and without secondary control level under the load variations to confirm the robustness of the control system. The results of the traditional and optimized secondary controllers are compared.

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.

Hybrid Microgrid based on PID Controller with the Modified Particle Swarm Optimization

Intelligent Automation & Soft Computing, 2022

Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate such issues. The power is extracted from Renewable Energy Resources (RER), such as Photovoltaic (PV), Micro-Hydro (MH), and Wind Energy Conversation System (WECS). For tracking the power more efficiently, Maximum Power Point Tracking (MPPT) techniques are employed. Boost Converters (BC) are used and inverters are employed to convert DC to the AC. Here, the power flow is managed by the PIDC. If the Firing Angle (FA) is not properly determined, it results in instability and steady-state stability issues. To address this, the optimum tuning parameters are chosen for PIDC, by utilizing the MPSO. Finally, through experimentation analysis, the proposed system's performance is analyzed and compared with the existing algorithms and validated.

IJESR IMPROVING POWER SYSTEM STABILITY IN MICRO-GRID SYSTEM USING PARTICLE SWARM OPTIMIZATION (PSO) TECHNIQUE

Mgbachi C.A.C. (Ph.D)

Among many problems in micro-grids is the voltage and frequency control in isolated mode especially during islanding process. Neural networks have been successfully used for character recognition, image compression, and stock market prediction, but there is no direct application related to controlling distributed generations of Micro-grid. For this reason, this work was decided on, with the aim of controlling diesel generator outputs. Firstly primary controlling quickly provides the required power of micro-grid in isolated mode. Then in next step controllable distributed generations play the role of secondary controllers. This work uses Artificial Neural Network (ANN) for considering of active and reactive power inter-effect on voltage and frequency. It examines the neural network algorithm that can be utilized for alleviating voltage and frequency issues of Micro-grid. MATLAB and Particle Swarm Optimization (PSO) are used for training neural network and simulating the Micro-grid model respectively. The Feed forward Back-propagation algorithm is used in this study and the Micro-grid consists of wind, solar, and diesel power generations, and battery energy storage system (BESS). Neural network indicates how much real and reactive power needed from each generator so as to improves the stability in the system..

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.