Intelligent Load Frequency Control Using Genetic Algorithms

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

BackgroundAutomatic generation control (AGC) of multi-area interconnected power system (IPS) is often designed with negligible cross-coupling between the load frequency control (LFC) and automatic voltage regulation (AVR) loops. This is because the AVR loop is considerably faster than that of LFC. However, with the introduction of slow optimal control action on the AVR, positive damping effect can be achieved on the LFC loop thereby improving the frequency control. In this paper, LFC synchronized with AVR in three-area IPS is proposed. Model predictive controller (MPC) configured in a dense distributed pattern, due to its online set-point tacking is used as the supplementary controller. The dynamics of the IPS subjected to multi-area step and random load disturbances are studied. The efficacy of the developed scheme is ascertained by simulating the disturbed system in MATLAB/Simulink.ResultsBased on the comparative analysis on the system responses, it is established that by cross-coupling the LFC loop with AVR, reductions of 66.45% and 59.09% in the frequency and tie-line power maximum deviations respectively are observed, while the respective settling times are found to be reduced by 29.68% and 22.77% when compared with the uncoordinated control scheme. In addition, the standard deviation and variance of the integral time absolute error of the system’s responses have reduced by 23.21% and 20.83% respectively compared to those obtained in a similar study.ConclusionsThe reduction in the maximum deviations and settling times in the system states indicates that introducing the voltage control via AVR loop has improved the frequency control significantly. While the lower standard deviation and variance of the integral time absolute error signify improvement in the robustness of the developed algorithm. However, this improvement is at the detriment of the controller size and computational complexity. In the uncoordinated control scheme, the control vector is one-dimensional, while in the coordinated scheme, the control vector is two-dimensional for each CA.

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.

To mitigate the frequency stability challenges induced by random power fluctuations and alterations in Load Frequency Control (LFC) parameters during large-scale wind power integration, an optimal PID controller design method based on an intelligent optimization algorithm is presented in this paper. Firstly, a PID-controlled closed-loop LFC model for interconnected power systems incorporating wind generation is established by using static output feedback control method. Secondly, the minimum value of the integral of time multiplied absolute error (ITAE) index of the time - domain output response is selected as the optimization target function, and the optimal PID controller settings are obtained by using the sine cosine algorithm (SCA) with excellent performance. Finally, simulation results confirm that the suggested LFC method has remarkable robustness, even under condions of step load and random load disturbances, wind power deviation effects, and system parameter variations. Additionally, it facilitates greater wind power penetration into the grid.

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.

In this article, the H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> dynamic triggering control design problem is concerned for a discrete-time switched control system with aperiodic and parameter uncertainty denial-of-service (DoS) attacks. First, by introducing dynamic trigger scheme, a switched delay system model under discrete-time can be established. Then, by integrating discrete piecewise Lyapunov-Krasovskii functional method with switch system method based on average dwell time (ADT), we obtain a criterion of preserving weighted H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> performance of the switched delay system. Derived from the criterion, since the DoS duration and frequency are constrained by upper/lower bounds, the dynamic output feedback control gain can be designed by solving a set of LMIs. Finally, by investigating a resilient H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> load frequency control (LFC) for a three-area power system, we verify the effectiveness of the method through numerical simulations.

For power quality enhancement, voltage, frequency, and power flow between control areas in an interconnected power system are required to be maintained. Hence, the voltage and frequency should be continuously controlled to maintain the balance of real and reactive power during load variation. Integration of renewable energy sources (RES) in the power system leads to inertia losses and mismatches between load demand and generation capacity; hence, the load frequency controller should overcome these challenges.In this paper, a Dandelion optimizer (DO)-based tilted-integral-derivative (TID) controller is introduced for load frequency control (LFC) of a single-area power system considering renwables pentration. A single-area power system with both solar and wind power plants as renewables and reheat-thermal, hydraulic, and gas power plants as conventional power plants is modeled using the Matlab toolbox. The controller-based DO optmizer is tested under different loading variations to verify its robustness. The sperm swarm and black widow optimization algorithms are compared with the introduced algorithm to verify its superior dynamic responses for loading variation.

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.

In this paper, an improved particle swarm optimization (IPSO) based load frequency control (LFC) of a single area power system is presented. Although the Particle Swarm Optimization approaches have several advantages, they can still have drawbacks like local optimal trapping due to premature convergence(i.e. exploration problem). This paper proposes an improved PSO framework adopting a crossover operation scheme to increase exploitation capability of PSO. The study has been realized for control of a single area interconnected power system with IPSO optimized self-tuning PID controller. The comparison between a conventional Proportional-Integral (PI) controller and the proposed PSO based controller showed that the proposed controller can generate a better transient response for a step load change. For this application, MATLAB-Simulink software is used.

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.

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 performance of a higher-order power system deteriorates due to the sudden load variations, structural discrepancy, and uncertainties involved in the parameters. Thus, an effective control technique must be employed to resolve the load frequency control (LFC) related issues in such systems. For the performance analysis of a higher-order system, a reduced-order controller is used for its reduced-order model because the full-order controller meets some structural and computational complexities. This paper proposes a reduced order linear active disturbance rejection control (RDLADRC) technique to deal with the LFC issues in a single-area power system. This technique successfully combines the benefits of the model order reduction (MOR) scheme and LADRC. Merits of the proposed approach are highlighted based on a deep comparative analysis of the reduced-order LADRC (RDLADRC) technique with full-order linear active disturbance rejection control (LADRC) and pre-existing two degree of freedom-internal model control (TDF-IMC) technique. The robustness of the proposed controller is investigated via system responses under parametric variations. MATLAB and simulation results confirm the effectiveness of the proposed scheme.

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.

For the load frequency control (LFC) of the interconnected power system, a two-level coordinated control frame based on multi-agent system is proposed to improve the frequency control performance of the power system. In the control frame, the upper-level agent, in a centralized manner, coordinates the lower-level LFC agents to deal with the conflict between narrowing the area control error and stabilizing the system frequency. The lower-level LFC agents, in the distributed cooperative manner, realize the mutual power support among the neighboring areas to guarantee the frequency stability in an emergency. To verify the validity of the proposed method, the numerical simulations are performed on the three-area interconnected power systems.