PI-tuned UPFC damping controllers design for multi-machine power system

This paper presents an adaptive multi-objective algorithm based Unified Power Flow Controller (UPFC) tuned for damping oscillations in two-area multi-machine system formulated as multi- objective optimization problem. The algorithms such as, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Modified Non-dominated Sorting Genetic Algorithm-II (MNSGA-II) are proposed for tuning the damping controller with speed deviation and control input as conflicting objectives. The proposed algorithm is implemented in the two area multi-machine system using MATLAB Simulink model, and the simulation results were obtained with respect to the characteristics of damping oscillations and the dynamic stability of power systems. The performance measures such as Integral Time Squared Error (ITSE) and Integral Squared Error (ISE) are considered as the objective functions. The results of the two proposed algorithm has been compared and the outcome shows that the MNSGA-II algorithm performs better compared to the NSGA-II algorithm

Innovative Approach to Enhance Stability: Neural Network Control and Aquila Optimization Integration in Single Machine Infinite Bus Systems

This paper highlights the need to improve the stability of single-machine infinite-bus (SMIB) systems, which is crucial for maintaining the dependability, efficiency, and safety of electrical power systems. The changing energy environment, characterized by a growing use of renewable sources and more intricate power networks, is challenging established stability measures. SMIB systems exhibit dynamic behavior, particularly during faults or unexpected load variations, requiring sophisticated real-time stabilization methods to avert power failures and provide a steady energy supply. This paper suggests a complex approach that combines power system stability analysis with a neural network controller enhanced by the Aquila optimization algorithm (AOA) to address the dynamic issues of SMIB systems. The study shows that the AOA-optimized neural network (AOA-NN) controller outperforms in avoiding disruptions and attaining speedy stabilization by exhaustively examining electrical, mechanical, and rotor dynamics. This method improves power system resilience and operational efficiency as demands and technology expand

Advanced Modeling, Design, and Control of ac-dc Microgrids

An interconnected dc grid that comprises resistive and constant-power loads (CPLs) that is fed by Photovoltaic (PV) units is studied first. All the sources and CPLs are connected to the grid via dc-dc buck converters. Nonlinear behavior of PV units in addition to the effect of the negative-resistance CPLs can destabilize the dc grid. A decentralized nonlinear model and control are proposed where an adaptive output-feedback controller is employed to stabilize the dc grid with assured stability through Lyapunov stability method while each converter employs only local measurements. Adaptive Neural Networks (NNs) are utilized to overcome the unknown dynamics of the dc-dc converters at Distributed Energy Resources (DERs) and CPLs and those of the interconnected network imposed on the converters. Additionally, the use of the output feedback control makes possible the utilization of other measured signals, in case of loss of main signal, at the converter location and creates measurement redundancy that improves reliability of the dc network. The switching between measurement signals of different types are performed through using the NNs without the need to further tuning. Then, in a small-scale ac grid, PV-based Distributed Generation (DG) units, including dc/dc converters and inverters, are controlled such that mimic a synchronous generator behavior. While other control schemes such as Synchronverters are used to control the inverter frequency and power at a fixed dc link voltage, the proposed approach considers both the dc-link voltage and the inverter ac voltage and frequency regulation. The dc-link capacitor stores kinetic energy similar to the rotor of a synchronous generator, providing inertia and contributes to the system stability. Additionally, a reduced Unified Power Flow Controller (UPFC) structure is proposed to enhance transient stability of small-scale micro grids. The reduced UPFC model exploits dc link of the DG unit to generate appropriate series voltage and inject it to the power line to enhance transient stability. It employs optimal control to ensure that the stability of the system is realized through minimum cost for the system. A neural network is used to approximate the cost function based on the weighted residual method

Load Frequency Control (LFC) Strategies in Renewable Energy‐Based Hybrid Power Systems:A Review

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments

Microgrid, Its Control and Stability: The State of The Art

Some of the challenges facing the power industries globally include power quality and stability, diminishing fossil fuel, climate change amongst others. The use of distributed generators however is growing at a steady pace to address these challenges. When interconnected and integrated with storage devices and controllable load, these generators operate together in a grid, which has incidental stability and control issues. The focus of this paper, therefore, is on the review and discussion of the different control approaches and the hierarchical control on a microgrid, the current practice in the literature concerning stability and the control techniques deployed for microgrid control; the weakness and strength of the different control strategies were discussed in this work and some of the areas that require further research are highlighted

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

Strategy to reduce transient current of inverter-side on an average value model high voltage direct current using adaptive neuro-fuzzy inference system controller

Growing-up of high voltage direct current (HVDC) penetration into modern power systems (PS) makes difficulty on the PS operation. The HVDC produces high and slow transient current (TC) at start-time, especially for higher up-ramp rate (Urr>20 pu/s). Its condition makes the HVDC cannot be linked and synchronized into the PS rapidly. A strategy to reduce the TC is proposed by an adaptive network based fuzzy inference system (ANFIS) control on inverter HVDC-link to cope up this problem. The ANFIS control is tuned with the help of conventional control in various train-data by using offline mode. Response of ANFIS scheme is improved by suppressing TC at the values of 3.75% for the both phases (A and C), and 3.95% for phase B, for the Urr=30 pu/s. While the conventional control achieved at 9.1% for the both phases (A and B), and 9.2% for the phase C. The ANFIS control gives shorter settling time (0.553 s) than the conventional control (0.584 s) for all phases. The proposed control is more effective than the conventional control at all the scenario

Investigation of the application of UPFC controllers for weak bus systems subjected to fault conditions. An investigation of the behaviour of a UPFC controller: the voltage stability and power transfer capability of the network and the effect of the position of unsymmetrical fault conditions.

In order to identify the weakest bus in a power system so that the Unified Power Flow Controller could be connected, an investigation of static and dynamic voltage stability is presented. Two stability indices, static and dynamic, have been proposed in the thesis. Multi-Input Multi-Output (MIMO) analysis has been used for the dynamic stability analysis. Results based on the Western System Coordinate Council (WSCC) 3-machine, 9-bus test system and IEEE 14 bus Reliability Test System (RTS) shows that these indices detect with the degree of accuracy the weakest bus, the weakest line and the voltage stability margin in the test system before suffering from voltage collapse. Recently, Flexible Alternating Current Transmission systems (FACTs) have become significant due to the need to strengthen existing power systems. The UPFC has been identified in literature as the most comprehensive and complex FACTs equipment that has emerged for the control and optimization of power flow in AC transmission systems. Significant research has been done on the UPFC. However, the extent of UPFC capability, connected to the weakest bus in maintaining the power flows under fault conditions, not only in the line where it is installed, but also in adjacent parallel lines, remains to be studied. In the literature, it has normally been assumed the UPFC is disconnected during a fault period. In this investigation it has been shown that fault conditions can affect the UPFC significantly, even if it occurred on far buses of the power system. This forms the main contribution presented in this thesis. The impact of UPFC in minimizing the disturbances in voltages, currents and power flows under fault conditions are investigated. The WSCC 3-machine, 9-bus test system is used to investigate the effect of an unsymmetrical fault type and position on the operation of UPFC controller in accordance to the G59 protection, stability and regulation. Results show that it is necessary to disconnect the UPFC controller from the power system during unsymmetrical fault conditions.Libyan Governmen