Improved particle swarm optimization based load frequency control in a single area power system

Since a Superconducting Magnetic Energy Storage (SMES) unit with a self–commutated converter is capable of controlling both the active and reactive powers simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This paper presents a novel control method of SMES with a self-tuned Fuzzy Proportional Integral (FPI) controller associated with the Automatic Generation Control (AGC) for improving Load Frequency Control (LFC) in a single area power system. Boiler dynamics and nonlinearities such as governor dead band (DB) and generator rate constraints (GRC) are considered in the developed comprehensive mathematical model of a single area isolated power system. The effects of the self–tuning configuration of FPI controller in AGC on SMES control is compared with that of fixed gain PI controlled AGC. It is seen that with addition of FPI controller, SMES can perform a more effective primary frequency control for single area power system. Key words: Load frequency control; single area power system; automatic generation control; superconducting magnetic energy storage unit; fuzzy proportional integral controller

This paper aims at hardware-in-loop (HIL) implementation of load frequency control (LFC) and automatic voltage regulation (AVR) schemes for a single area power system. The single area power system consists of a synchronous generator based non-reheat thermal area unit serving linear loads. In order to minimize the power mismatch between the generation and load, LFC & AVR control strategies have been developed considering the dynamics of thermal area power system. The control strategies have been developed to operate in a continuous mode of operation using conventional Proportional-Integral (PI) controller. 3%, 8% & 10% variations of load has been considered to validate system performance at various loading levels. HIL implementation has been achieved using dPSACE MicroLabBox which interfaces the controller developed in MATLAB/Simulink platform to the hardware components.

This paper presents the comparative study of parameter tuning of proportional-integral-derivative controller in load frequency control in a single area multi-source power system as well as multi-source multi-area power system. It is shown that simple particle swarm optimization (SPSO), due to its premature convergence to a local minimum, is not able to provide an optimum value of the controller parameters. As a solution to this problem, a modified version of SPSO (MPSO) is proposed and discussed. The idea is to avoid particles from converging prematurely to a local minimum and cover the entire search space in an efficient way. MPSO provides far better result than the SPSO. Initially, a multi-source single area power system having integral controllers for each i.e., thermal, hydro and gas is examined and controller parameters are obtained using MPSO algorithm. Then a multi-source multi-area power system in presence of AC-DC tie-lines is studied. Results obtained by these algorithms are compared with the other existing optimization algorithm such as differential evolution and method based on optimal control theory.

The modern power systems with industrial and commercial loads need to operate at constant frequency with reliable power. The load frequency control of an interconnected power system is being improved over the last few years. The goals of the LFC are to maintain stability improvement of power system. Fuzzy logic controller application of load frequency control (LFC) of a single area power system by using a fuzzy logic is presented. The study has been designed for a single area interconnected power system. The comparison between a conventional Proportional and Integral (PI) controller and the proposed artificial neural networks controller is showed that the proposed controller can generate the best dynamic response for a step load change. For this application, MATLAB-Simulink software is used.

This paper deals with the importance of load frequency control (LFC) for single and interconnected power system. It is important to keep the frequency of the system and the inter area tie power stable. The goal of LFC is to maintain the frequency, the desired power output and to control the change in tie line power between control areas in an interconnected power system. Two different techniques have been implemented in this paper which are model predictive controller MPC and conventional proportional plus integral controller PI for LFC of single area power system as well as two area system. To investigate the powerful and robustness of model predictive control (MPC) technique for LFC problems in electric power system, time simulations is performed. The obtained results indicate that the MPC provide better damping to the single area system as well as two-area system in case of load disturbance compared with conventional PI controller. The studied single-area and two-area systems are modelled and simulated using Simulink/Matlab software.

This paper presents a novel control method of Superconducting Magnetic Energy Storage (SMES) unit with a self-tuned Fuzzy Frequency Controller (FFC) associated with the Automatic Generation Control (AGC) for improving Load Frequency Control (LFC) in a single area power system. Boiler dynamics and nonlinearities such as governor dead band (DB) and generator rate constraints (GRC) are considered in the developed comprehensive mathematical model of a single area isolated power system. The effects of the self-tuning configuration of fuzzy frequency controller in AGC on SMES control is compared with that of optimized fixed gain PI controlled AGC. It is seen that with addition of self-tuned fuzzy frequency controller, SMES can perform a more effective primary frequency control for single area power system.

This paper considers the problem of load frequency control (LFC) of power systems when the states of the system are not available for implementation and in the presence of unknown disturbances. Conventional proportional observer (PO) fails to solve this problem unless the disturbances are known or can be modeled. Therefore, we provide a detailed analysis of the generalized proportional integral observer (GPIO) for load frequency control of a single area power system. This study demonstrates that the proposed observer can reliably be used. Since the suggested observer is able to estimate both the states and unknown disturbances, it can be integrated in LFC with disturbance accommodation to ensure system stability and satisfy specified performance measures. Numerical examples are given to illustrate the advantage of GPI observer-based LFC for a single area power system model.

The world is directing its efforts towards achieving 100% renewable power generation. This paper presents frequency control of a single area power system. The power system is feeding from renewable technologies and storage facilities only which are Photovoltaics, Biogas, Biodiesel, Solar thermal, battery storage and flywheel storage systems. The paper presents models to each renewable technology and energy storage facility. The frequency is controlled by using Nonlinear PID controller (NPID), Fractional order PID controller (FOPID) and Nonlinear FOPID controller (NFOPID). The three controllers are designed by using genetic algorithm at different operating conditions. A comparison between the three controllers at different operating conditions is presented. The results show that NFOPID has better performance than the other two controllers. The simulation and optimization are performed using MATLAB / SIMULINK 2017a.

Load frequency control (LFC) is vital for balancing power generation with fluctuating power demand. It ensures that the system frequency and tie-line power are maintained at their desired levels. The design of an LFC system is crucial for the automation of power systems. This article introduces a Fuzzy Proportional-Integral-Derivative (FPID) control approach for LFC in an interconnected reheat thermal power system, utilizing a Particle Swarm Optimization (PSO) method and incorporating the Generation Rate Constraint (GRC) as nonlinearities. The proposed controller offers the advantage of effectively managing system nonlinearities while being better than classical controllers. The response of the FPID controller is contrasted with both the conventional Proportional-Integral (PI) controller and the Fractional Order PID (FOPID) controller, in scenarios both including and excluding the Generation Rate Constraint (GRC). The response of the system is analyzed by considering load disturbances in each region of the integrated power network.

Load frequency control is one of the most important issues in multi area power systems. In this context, due to growing development of wind turbines in power systems, this type of renewable power sources can be used efficiently in frequency control. This paper applies doubly-fed induction generators (DFIGs) along with other conventional generation units for frequency performance enhancement after disturbances in multi-area power systems. Proportional integral (PI) controller is the conventional controller which is used in DFIGs to contribute in frequency control. The parameters of PI controller for DFIG are optimized by improved particle swarm optimization (IPSO) method. Simulation results in a three-area power system illustrate the efficiency of the DFIGs for frequency and tie-line power oscillations improvement.

In this paper a full-order observer-based optimal control technique is implemented to control the load frequency problem for a single area power system. A state feedback controller is designed using linear quadratic regulator (LQR) and full-order state observer based design techniques. A numerical example is considered to check the capability of the developed methodology. The performance is compared between both the methods. It has been recognized through the simulation results and the tabulated data that the performance of observer based LQR controller is better both in term of transient as well as at steady state performance.

In this paper, combination of Generalized Fuzzy Model (GFM) and Gaussian Mixture Model (GMM) based controller is used to determine the optimal parameters of Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) system of single area power system. GFM combines the advantages of Takagi and Sugeno(T-S) and Mamdani -- Larsen (ML) models of fuzzy logic techniques. In the proposed controller, first membership functions are optimized by GMM and then GFM calculates the final output in single iteration i.e. with no recursions. This is highly desirable in power quality problems. The simulations demonstrate the effective and smooth performance of the power system. Comparative analysis is done between controllers based on Proportional and Integral (PI), T-S model, ML model and GMM & GFM model. Simulated results evince the superiority of the proposed hybrid controller.

Nowadays, due to vulnerability of power system and upsurge in power demand, communication network is essential for secure operation, control and monitoring of power system. Time delay exists in communication channel can worsen the dynamic performance of closed loop of power system especially in load frequency control (LFC) problem. Due to time delay or some fault present on a system, some generator outage may take place from any well connected areas. So, in this paper an attempt is made to presents an impact of communication delay on frequency regulation of two area interconnected power system with outage of generator terminal from one area. Pade method is used to model the communication delay. A Proportional integral (PI) control based particle swarm optimization (PSO) technique is used to tune the controller gains. A series of simulation results are performed for various case studies, for the effectiveness of control design method mainly for dynamic response of system

The main objective of Load Frequency Control (LFC) is to regulate the power output of the electric generator within an area in response to changes in system frequency and tie-line loading. Thus the LFC helps in maintaining the scheduled system frequency and tie-line power interchange with the other areas within the prescribed limits. Most LFCs are primarily composed of an integral controller. The integrator gain is set to a level that compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to take into account possible changes in operating conditions and non-linearities in the generator unit. Moreover, it lacks robustness. This chapter studies LFC in two areas power system using PID controller. In this chapter, PID parameters are tuned using different tuning techniques. The overshoots and settling times with the proposed controllers are better than the outputs of the conventional PID controllers. This chapter uses MATLAB/SIMULINK software. Simulations are done by using the same PID parameters for the two different areas because it gives a better performance for the system frequency response than the case of using two different sets of PID parameters for the two areas. The used methods in this chapter are: (a) Particle Swarm Optimization,(b) Adaptive Weight Particle Swarm Optimization, (c) Adaptive Acceleration Coefficients based PSO (AACPSO) and (d) Adaptive Neuro Fuzzy Inference System (ANFIS). The comparison has been carried out for these different controllers for two areas power system, the study presents advanced techniques for Load Frequency Control. These proposed techniques are based on Artificial Intelligence. It gives promising results.

In this paper, a novel meta-heuristic Colliding bodies optimization-based proportional-integral-derivative controller with derivative filter is presented to solve a single-area power system's load frequency control issues. The controller parameters are determined by employing the integral of time multiplied absolute error as the fitness function. A single-area non-reheat thermal power system is considered for establishing the efficacy of the proposed method. The robustness of the proposed controller is also ascertained by inserting perturbation in system parameters. It is observed from the simulation results that the proposed method provides improved dynamic performance over the existing methods.