Power System Controller Research Articles

Application of Pattern Search Algorithm based Automatic Generation Control of an Interconnected Power System

This paper demonstrates the advantage of the selection of the Pattern Search algorithm (PS) in the design of a Proportional-Integral controller used in Automatic Generation Control for a two area non-reheat interconnected thermal system. The design problem involves the implementation of PS algorithm to find out the value of parameters of the controller of the proposed power system. Here we have implemented three objective functions by using ITAE, damping ratio of dominant eigenvalues and settling time with weight coefficients for the design problem to get an optimized parameter of the Proportional Integral controller. The robustness of the designed PI controller using the Pattern search algorithm has been demonstrated after comparing other PI controllers using various optimization techniques like Genetic Algorithm, Bacteria Foraging Optimization Algorithm for the system under study. Further, best objective function uses the PS optimization algorithm in PI/PID controller parameters, tunning is obtained in presence of physical constraints like governor dead band non linearity of the proposed two area power system. The modified model to test the sensitivity analysis of PI/PID controller by using different loading condition to show the PID controller performance of frequency and tie line power deviation improved better as compared to the PI controller of the same power system. Further, it is extended to multi-area multi-source power for effectiveness and robustness of the system under different disturbances to check the transient stability.

Using a fuzzy logic controller in photovoltaic power systems for maximizing PV array efficiency

The goal of this work is to design a high-efficiency photovoltaic system (PV) with a fuzzy logic controller. This PV system consists of a PV panel, DC/DC Buck-Boost converter with a 24V DC load, and a fuzzy logic controller. Because the efficiency of normal solar PV modules is very low, we implemented the fuzzy logic controller. In this paper, we have proposed a system that is designed and simulated in MATLAB Simulink. In the fourth section of the paper are shown obtained results which show that using the fuzzy logic controller for photovoltaic systems has better performance. This controller can facilitate the PV array to reach the MPPT faster and provide more stable output power.

Dynamic Voltage Restorer to Mitigate Voltage Sag/Swell using Black Widow Optimization Technique with FOPID Controller

The efficiency with which electrical equipment use electricity is essential for several reasons. First, superior power quality (PQ) improves efficiency and facilitates peak performance in electronic equipment. This article's goal is to make the advantages of installing a Dynamic Voltage Restorer (DVR) to enhance PQ for energy users clearer. To improve DVR dependability and user friendliness, the suggested technique uses a hysteresis voltage control system that works with variable switching frequency. Simulation findings show that voltage compensation is successful under disturbances when a black widow optimization (BWO) based Factional order proportional derivative (FOPID) controller is used. This paper proposed is to improve PQ using a BWO- FOPID controller and compare the outcomes to those achieved from a previously developed PI controller in a distribution power system using MATLAB.

Designing an Intuitive Algorithm Based Load Frequency Controller for Electrical Power Systems

In the interconnected system, changes in energy consumption and random energy generation by renewable energy sources cause an increase or decrease in frequency and bus voltages. Load frequency control (LFC) that cannot be controlled within certain limits may cause serious problems. Therefore, LFC is required to keep the interconnection frequency and power sharing of the interconnection line at a certain value. Due to the importance of this issue, researchers have been working on numerous studies to improve LFC. In this article, a cascaded FOPID+(III) controller consisting of a fractional-order PID and three integrators is designed for a two-zone power system, including thermal power plants, electric vehicles using the vehicle-to-grid (V2G) technique and renewable energy sources such as wind farms and photovoltaic panels. Particle Swarm Optimization and Gray Wolf Optimization are used to determine the gain parameters in our new design. The effectiveness and efficiency of the FOPID+(III) controller are tested with load variation, parameter variation in the designed model and RES power variation. As a result of the experiments, it was observed that the PSO-based FOPID+(III) controller provided a 54% improvement in settling time and a 55% improvement in maximum frequency overshoot compared to other controllers.

An Amplified Salp Swarm Optimization Algorithm for Maximum Power Point Tracking Control of Proton Exchange Membrane Fuel Cells

The proton exchange membrane fuel cell (PEMFC), one of the many fuel cell varieties on the market, is distinguished by its low temperatures of operation, high reliability, and extended lifespan. The fuel cell system's maximum output can only be achieved at one specific operating point under varying operating circumstances. Hence, it is essential to get the most power possible from the PEMFC for improved functioning and optimal exploitation of grid systems. Thus, the design of a maximum power point tracking (MPPT) controller for a PEMFC power system using an amplified salp swarm optimization (AS2O) algorithm is focused on. Here, an interleaved Luo converter is also used to produce a regulated output voltage with less switching stress and frequency. Moreover, the proposed work intends to effectively satisfy the energy demand of grid systems by obtaining the maximum electrical energy from the PEMFCs with less harmonics and low system complexity. The simulation and performance results of the proposed AS2O‐MPPT controlling model are validated and compared using several parameters using MATLAB/Simulink tool. Using the proposed controlling technique, the total harmonics distortion is reduced up to 1.16%, with the settling time of 0.0062 s, rise time of 0.0010 s, and peak overshoot of 0.255 W.

Distributed Generation Based WADC for Inter-Area Oscillations Considering Unknown Inputs

Inter-area oscillations (IAOs) are one of the main problems for contemporary power systems because of their low-damping characteristics. Additionally, the damping behaviors of IAOs might be further deteriorated by the addition of low inertial distributed generation (DG) to the power system. Therefore, a novel wide-area damping controller (WADC) for DG-integrated power systems is developed utilizing a modal linear quadratic regulator (LQR) technique that only targets essential IAOs without degrading other local modes. The states participated in linear combination from modal LQR are generally unavailable and need to be estimated. Full order observers are frequently used in literature, although they may not function if some inputs are unavailable. Hence, an unknown input observer (UIO) is suggested in this paper to estimate the states despite certain inputs being unknown. The proposed methodology is then tested on a DG-integrated 4-machine, 11-bus system and 10-machine, 39-bus system to validate the overall proposed design process. Results show that the proposed WADC successfully dampens the crucial IAO modes by 10% and 15% while not degrading other modes of the system.

Application of inertia emulation control strategy with energy storage system in multi-area hydro -thermal system using a novel metaheuristic optimized tilt controller

This article presents the application of a novel artificial hummingbirds’ algorithm (AHA) based tilt-integral second order of double-derivative controller (TIDD2) in a three-area hydro-thermal power system. Also, the inertia emulation control strategy has been incorporated using various energy storage systems (ESS) to established the frequency in interconnected power system. The supremacy of the proposed controller is established by comparing the system dynamic response with some existing controllers, such as proportional-integral-derivative (PID), tilt-integral-derivative (TID) and cascade of IDD - PID controllers. The fruitfulness of proposed AHA has also been evaluated with system dynamic and convergence characteristics comparison over some of existing metaheuristic optimization techniques such as harris hawk's optimization (HHO) and bird swarm algorithm (BSA). Further, effect of random load pattern (RLP), communication time delay (CTD) and variable CTD on the system dynamic is analyzed. The study of inertia emulation control strategy in a multi-area interconnected power system revealed that, when inertia is emulated with superconducting magnetic energy storage (SMES), the system dynamic exhibits better performance over battery energy storage (BES) and ultra-capacitor (UC). Furthermore, the proposed systems are validated in a real-time environment using OPAL-RT lab software. Also, the scalability of the proposed method is evaluated by using eigenvalue analysis.

A Gershgorin Circle Theorem Inspired Controller for Renewable Energy Source Integrated Power Systems and Multimicrogrids

Increasing load demands, variations in the operating conditions, continuous integration of the renewable energy sources constitute a multifarious challenge for the researchers to maintain the quality in performances of a load frequency controller. To contemplate such issues, a Gershgorin circle theorem inspired controller assimilated with the particle swarm optimization is proposed for multiarea power systems. The proposed method ensures system stability while abating the frequency variations in the operational areas and the power deviations in the interconnected tie-lines. The present analysis is substantiated through an interconnected photovoltaic (PV) integrated thermal power systems. Furthermore, the competence of the proposed method against increasing complexities is validated by considering an interconnected multimicrogrid systems consisting of renewable and nonrenewable energy sources. The performances of the proposed controller are demonstrated considering fixed and time-varying load disturbances, and fluctuations in renewable energy sources. Results corroborate that the proposed method is successful in maintaining the system stability while mitigating the frequency and the power deviations in all such operating conditions. A comparative analysis of the proposed method with prevalent control techniques (e.g., PI and PID-based controllers, tilt–integral–derivative, integral–tilt–derivative) and optimization algorithms (e.g., genetic algorithm, gravitational search algorithm, imperialist competitive algorithm) is presented to highlight the substantial performance improvements in the considered systems.

Implementation of Digital Twin for Increasing Efficiency of Renewable Energy Sources

This paper presents an analysis of the instability of the electricity generation of renewable energy sources (RESs), specifically Digital Twins of RESs. The first part deals with the analysis of RES electricity generation around the world and Ukraine. The following chapter describes features of functioning power grids in modern conditions in Ukraine and ways to ensure the balance reliability in the power system for conditions of high-grade RES integration. The rapid increase in electricity generation RESs causes control problems of distributed power supply in the power grid. A mathematical model of the parameter controls in normal mode electric power systems for conditions with high integration of RESs is proposed in the second part. The study investigates components of the optimality criterion at the control of normal mode parameters of the electric power system with RESs. In general, digital transformation helps decarbonize the energy supply, decrease dependency on fossil fuels, and integrate renewables into power systems. A model Digital Twin (DT) of a photovoltaic system, or an exact 3D visualization, analyzing the accumulator system depending on load and generation, are presented. The problems of Digital Twin are very widely discussed, but many papers and studies are general without any practical implementations. The main part of this paper focuses on research and deals with daily electricity generation from different kinds of RESs, namely mini-hydropower stations, photovoltaic power stations, and wind power stations. Measured data of electricity generation from photovoltaic power plants, wind power plants, and mini-hydropower plants and obtained meteorological factors were used for the calculation of Spearman’s, Kendall’s, and Pearson’s correlation rank coefficients. The main contribution of this research is to determine the main metrological factors for each kind of studied RES. In the future, it will help to decide the task of forecasting power generation more presciently. Additionally, the presented model of DT RESs allows the installation and operation of grids with higher efficiency, because it can help to predict all influences, from shading up to the optimization of the battery storage system.

An optimal initialisation for robust model reference adaptive PI controller for grid-tied power systems under unbalanced grid conditions

This paper presents an Optimal Robust Model Reference Adaptive Proportional–Integral controller for grid-tied power systems, which is automatically parametrised using a Genetic Algorithm. The task of choosing the adaptation rate and the controller’s initial gains set is now performed in a computational and automatic way, saving design time and ensuring satisfactory transient regimes.The use of a Genetic Algorithm for complete parametrisation of robust adaptive controllers applied to renewable energy power generation systems with LCL filter is first here explored. Five cost functions are considered in the optimisation process. A comparison of simulation results applying the optimised controller in a grid-tied Voltage Source Inverter with LCL filter points out the benefits and drawbacks of using each cost function. A framework for performance analysis and an in-depth discussion are provided. The function determined as the best one, which is integral of absolute error, is used in the controller implemented experimentally, ensuring suitable tracking of grid current references and rejection of grid voltage harmonics, even under unbalanced grid voltage conditions. An experimental comparison in a three-phase 6.75 kW power converter with the non-optimised controller is also provided, where the optimised controller obtains a reduction in the overshoot in all transient regimes and smaller tracking error, resulting in a reduction in the mean error of 14.31% and 60.30% in α and β coordinates, respectively. In addition, the optimised controller reduces total harmonic content, improving energy quality. This parametrisation procedure can be immediately extended to the control of any other power converter systems.

Real-time co-simulation of transmission and distribution networks integrated with distributed energy resources for frequency and voltage support

This paper proposes a real-time co-simulated framework to experimentally validate the dynamic performance of network-level controllers in power systems. The experiment setup includes the coordinated emulation of a transmission network linked to a distribution feeder and real distributed energy sources, working in a multi-platform and multi-manufacturer environment. The operation of an optimal hierarchical controller for voltage and frequency support of the transmission network, which exploits the power injection from battery energy storage systems (BESS), is investigated to demonstrate the feasibility, accuracy and effectiveness of the proposed setup based on a co-simulation environment. The results of different study cases implemented in the laboratory are presented, where a successful interconnection between real-time emulators and real hardware from different manufacturers was realised. The fast and timely response of the controller to disturbances caused by sudden load changes, three-phase faults and renewable generation losses is experimentally validated. Finally, the robustness of the developed test bench against noise and harmonic distortion of real signals is also demonstrated.

Novel Fractional-Order Proportional-Integral Controller for Hybrid Power System with Solar Grid and Reheated Thermal Generator

This paper presents a new fractional-order proportional-integral, (PI)λ (FO[PI]) type structure to investigate the load frequency control (LFC) problem. In the literature, some controllers’ extensive tuning options may slow or complicate the optimization process. Due to the intricacy of the tuning, even if there are fewer tuning parameters, a robust structure can be obtained. The (PI)λ structure deviates from the standard FOPI, integer PID, or PI-PD controllers with the same or fewer tuning parameters. The efficacy of a tri-parametric fractional-order controller is examined on a two-area interconnected hybrid power system comprising a photovoltaic (PV) grid and a Reheated Thermal Generator (RTG). In order to obtain optimal performance with lower control efforts, a novel dual-performance index is developed for the LFC problem. Various analyses are also proven to perform better than other optimized controllers from the recent literature. The presented scheme is significantly robust to disturbance interruptions, non-linearities, and parameter perturbations. It is also observed that there are no stability issues due to communication time delays. It is highlighted that the improvement can be obtained without adding complex structure or controller parameters.

A Review of Load Frequency Control Schemes Deployed for Wind-Integrated Power Systems

Load frequency control (LFC) has recently gained importance due to the increasing integration of wind energy in contemporary power systems. Hence, several power system models, control techniques, and controllers have been developed to improve the efficiency, resilience, flexibility, and economic feasibility of LFC. Critical factors, such as energy systems, resources, optimization approaches, resilience, and transient stability have been studied to demonstrate the uniqueness of the proposed design. This paper examines the most recent advances in LFC techniques for wind-based power systems. Moreover, the use of classical, artificial intelligence, model predictive control, sliding mode control, cascade controllers, and other newly designed and adopted controllers in the LFC area is thoroughly examined. Statistical analysis and a comparison table are used to evaluate the advantages, disadvantages, and applications of various controllers. Finally, this paper presents a comprehensive overview of contemporary and other widely used soft computing tools for the LFC issue. This detailed literature review will assist researchers in overcoming the gap between current progress, application, limitations, and future developments of wind energy in LFC.

Squirrel search algorithm based intelligent controller for interconnected power system

ABSTRACT In this paper, a novel controller, namely fractional order fuzzy proportional-integral-derivative (FOFPID) has been proposed for the dual area power system of hydro-thermal-gas units (DAHTG). The squirrel search algorithm (SSA) is implemented to achieve the optimal values of the controller tuning parameters. Further, various non-linearity constraints, such as governor dead band (GDB), generation rate constraint (GRC) and communication time delays (CTDs) have also been considered to test the effectiveness of the proposed controller in a real-time environment. The step load of 10% is provided as the disturbance under the regulation. In addition, the coordinated strategy of a static synchronous series compensator (SSSC) device and superconducting magnetic energy storage (SMES) is employed in the proposed system to enhance the system’s performance. Further, the accuracy, effectiveness and robustness of the proposed controller are revealed through the comparative analysis with classical PID and traditional fuzzy PID controllers. Furthermore, presented controller efficacy is revealed with the other recently reported control techniques by implementing it on the two-area thermal system with GDB. The comparative analysis shows the better performance of the proposed controller than these two. Finally, the sensitivity analysis is performed to check the controller robustness.

Coordinated load frequency control of a smart hybrid power system using the DEMA-TD3 algorithm

In this paper, a novel deep reinforcement learning (DRL) algorithm is proposed for the coordination of controllers in a multi-source hybrid power system (HPS) for load frequency control (LFC). Decentralized controllers regulate the distributed sources with uncertainties in load and source power deviations to maintain the power system frequency. Coordination of decentralized controllers becomes challenging in the presence of dynamic disturbances. A novel LFC framework is introduced via a dynamic environment-based multi-agent twin delayed deep deterministic policy gradient (DEMA-TD3) algorithm to coordinate the decentralized controllers. Moreover, system stability is a concern in systems with renewable integration during islanding operations. To achieve successful islanding, a smart home inverter (SHI) based coordinated control is proposed. Virtual inertia (VI) is added to provide additional frequency support for robust control. Various simulation test scenarios are simulated to analyze the effectiveness of the proposed novel LFC architecture in different modes of operation.

The use of numerical method in an electric grid coupled to a wind farm to compare different kinds of flexible AC transmission systems

The PSAT software was used in this study to analyse and compare the performance of hybrid compensators such as SSSC-STATCOM (controllers), TCSC-SVC (compensators), and UPFC in an electric grid coupled to a wind farm. The flexible AC transmission system (FACTS) technology is used to provide a continual power flow and to provide new ways to control the electric system network. In the FACTS devices, the UPFC (Unified Power Flow Controller) is one of the most adaptable, flexible, and complicated power electric devices. The active and reactive power flows and the local voltage on the bus can be regulated by UPFC; it can also resolve the problem of harmonics. The TCSC (Thyristor-Controlled Series Capacitor) consists as a series-compensating capacitor shunted by a thyristor-controlled reactor. The SVC (Static Var Compensator) is the first shunt generation FACTS controller. We can observe that the UPFC controller has an effective power flow control, shorter setting time and a shorter overshoot. The UPFC obtained a well-known reputation for high controllability in power systems. The multilevel Unified Power Flow Controller can be operated in Static Synchronous Compensator (STATCOM), in Static Synchronous Series Compensator SSSC and exactly in the UPFC compensator. The results of this research compare the hybrid controllers and investigate the effects of TCSC-SVC, SSSC-STATCOM, and UPFC on voltage, phase angle stability, and the active and reactive power in the tested system. The purpose of this comparison is to improve dynamic voltage regulation, especially when the utilisation of nonlinear loads and the presence of fault and breaker rise. These hybrid controllers have been shown to outperform series or shunt compensators; however, when compared to hybrid compensators SSSC-STATCOM, TCSC-SVC, and UPFC, the results employing the numerical method in the UPFC are more significant. The UPFC is the best hybrid controller in this study, and the compensators SSSC-STATCOM outperform the controllers TCSC-SVC.

Implementation of Load Frequency Control Using Fuzzy Logic Controller in an Interconnected Power System

Implementation of Load Frequency Control Using Fuzzy Logic Controller in an Interconnected Power System

Discrete-Time Modeling and Control for LFC Based on Fuzzy Tuned Fractional-Order PDμ Controller in a Sustainable Hybrid Power System

Discrete-Time Modeling and Control for LFC Based on Fuzzy Tuned Fractional-Order PD^μ Controller in a Sustainable Hybrid Power System

Sub-Riemannian Approach to Design Nonlinear Optimal Controller for Multimachine Power System

Sub-Riemannian Approach to Design Nonlinear Optimal Controller for Multimachine Power System

Load frequency controller for an islanded hybrid power system using WCO

This research proposes a new metaheuristic algorithm based on World Cup Optimization (WCO) to determine the optimal values of the Proportional Integral Deviation (PID) controller for the load frequency control problem. An islanded hybrid power system consists of a Wind Turbine Generator (WTG), Diesel Generation (DEG), and an Energy Storage System (ESS), such as a Battery Energy Storage System (BESS), Super Magnetic Energy Storage (SMES), and an Ultra Capacitor (UC) unit. A single-area power system was designed as a model network for the MATLAB-Simulink simulation. Furthermore, a hybrid system was employed with Proportional-Integral (PI) controllers and PI derivative controllers with proportionate gains to the DEG, and an ESS. A comparative performance assessment of the WCP was conducted to tune the PI and PID controllers. The simulation results indicate that a renewable integrated isolated power system with an Energy Storage System (ESS) tuned with a PID controller provides better responses than the PI controller for different loading conditions. Based on time settling, transient, and overshoot analysis, it is proven that a WCO-tuned PID controller is better than a PI controller.