Governor Dead Band Research Articles

Kharitonov theorem-based robust control approach for sustainable microgrid against DoS cyber-attack

With the inclusion of cyber-physical systems (CPS) in the power system, the security of the power system is jeopardized. The application of communication channels facilitates the exchange of information, but at the cost of increasing the vulnerability of the system. This paper presents an application of the Kharitonov Theorem-based proportional-integral (KT-PI) control technique for load frequency control (LFC) of a microgrid subjected to cyber-attacks. The microgrid is composed of renewable energy sources (RESs), controllable energy sources, and energy storage systems (ESSs). The microgrid is subjected to a cyber-attack, namely a denial-of-service (DoS) attack. The robustness and effectiveness of the proposed control technique is examined by considering the effect of parametric uncertainties and nonlinearities namely generation rate constraint (GRC) and governor dead-band (GDB). The quantitative comparative analysis is determined in terms of various performance indices such as integral square error (ISE), integral absolute error (IAE) and integral of time absolute error (ITAE) using proposed KT-PI and ZN-PI controllers. The stability of the microgrid subjected to the aforementioned cyber-attack using the proposed KT-PI and existing ZN-PI techniques is analyzed using Eigenvalue approach. The simulation results presented in the end clearly establishes the better performance of KT-PI approach as compared to ZN-PI controller in handling DoS attacks.

Effective Load Frequency Control of Power System with Two-Degree Freedom Tilt-Integral-Derivative Based on Whale Optimization Algorithm

Nowadays, the operation and control of power systems are a big challenge. An essential part of the power system (PS) control is load frequency control (LFC). Different secondary controllers are implemented for the frequency control problem. Hence, cascaded two-degree freedom and a tilt-integral-derivative controller having a filter (2DOFTIDF) are intended in this paper and implemented for load frequency control. In order to determine the efficiency of the 2DOFTIDF controller, a well-known non-reheat thermal system with/without a governor dead band is considered. A new whale optimization algorithm (WOA) is used to enhance the suggested controller parameters. The predominance of the presented method is exhibited by comparing the consequences with different heuristic techniques tuned to controllers published recently. Further, the simulation results for two test cases indicate that system enactments are enhanced by introducing the suggested controller and are also best suited in the presence of system nonlinearity. Finally, random load fluctuation along with noise and changing the system parameters are also used to determine the reliability of the suggested controller. Compared to the WOA-tuned TIDF controller, the settling time of ΔF1, ΔF2, and ΔPTie is improved by 45.45%, 56.77%, and 20.26%, respectively, with the WOA-tuned 2DOFTIDF controller and by 40%, 48.27%, and 20%, respectively, with the DE-tuned TIDF controller. Experimental validation using the hardware-in-the-loop real-time simulation based on OPAL-RT has been carried out to confirm the viability of the proposed approach.

Concerted voltage frequency control and superconducting magnetic energy storage operation using optimal adaptive model predictive control for improved frequency response of power system

SummaryActive power equilibrium is analogous to frequency control. A hypothesis of maintaining this balance with voltage regulation is slightly less instinctive, notwithstanding the contribution it can make to the overall stability of the power system. This idea in synergism with the utilization of superconducting magnetic energy storage (SMES) technology in a colossal multi‐machine power network, is exercised in this paper. The main focus of this work is to make a small‐rated SMES more providential in large power systems with the aid of voltage frequency control (VFC). This study proposes an adaptive model predictive control (AMPC) equipped small capacity SMES as well as VFC operation, to ensure load frequency control of a wind power penetrated system. While assuming the plant as an autoregressive discrete mode system with exogenous input, the determination of both the plant model and controller parameters are effectuated online using a recursive least squares (RLS) identification algorithm. Detailed mathematical modeling of SMES is presented in addition to the discrete mode automatic generation control (d‐AGC) and governor dead band non‐linearity at the synchronous power source ends. A compact doubly fed induction generator (DFIG) model architecture harmonizing the maximum power point tracking (MPPT) mode using the standard two‐dimensional look‐up table with turbine characteristics is also discussed. Simulations in MATLAB/Simulink domain reveals a percentage improvement of 82.6% in the frequency nadir under load disturbance with the proposed VFC‐SMES scheme. Furthermore, an average percentage improvement of 82% in peak frequency deviations under turbulent wind scenario is attained. These results are validated in real‐time, employing the real‐time digital simulator OPAL‐RT (OP4510).

Voltage and frequency regulation in smart grids via a unique Fuzzy PIDD2 controller optimized by Gradient-Based Optimization algorithm

This paper proposes a maiden intelligent controller design that consists of a Fuzzy Proportional–Integral–Derivative–Double Derivative (FPIDD2) controller whose parameters are fine-tuned using the Gradient-Based Optimization algorithm (GBO). The proposed FPIDD2 regulator is employed as a secondary regulator for stabilizing the combined voltage and frequency loops in a two-area interconnected power system. It has been shown that the GBO optimization algorithm outperforms other optimization strategies such as the Chimp Optimization Algorithm (ChOA), the Whale Optimization Algorithm (WOA), and the Gorilla Troops Optimization algorithm (GTO). The proposed FPIDD2 controller is tested in a conventional two-area power system. Then, the investigation is expanded to a two-area hybrid system, with each area comprising a mix of traditional (thermal, gas, and hydraulic power plants) and renewable generation units (wind and solar power). Additionally, the proposed controller takes into account system nonlinearities (such as generation rate limitations, governor deadband, and communication time delays), system uncertainties, and load/renewables fluctuations. In the two tested systems, the dynamic responses of each system demonstrate that FPIDD2 has a superior ability to attenuate the deviations in voltage and frequency in both areas of the system. In the studied conventional system, the proposed FPIDD2 controller is compared with a PID controller tuned by the Multi-Objective Non-Linear Threshold Accepting Algorithm (MONLTA), which has been presented in the literature, and a Fuzzy PID (FPID) controller tuned by GBO. In the investigated hybrid system, the suggested FPIDD2 regulator is compared to a GBO-tuned Integral Derivative-Tilted (ID-T) controller and FPID controller. As a fitness function (FF) for the GBO, the criteria of minimizing the integral time absolute error (ITAE) are applied. The results are presented in the form of MATLAB/SIMULINK time-domain simulations.

A Novel Jaya Based Automatic Generation Control of Two Area Interconnected Power System with nonlinearity

Background: This paper presents a novel approach to design and optimize Proportional-Integral-Derivative (PID) controller for Automatic Generation Control (AGC) of two-area interconnected power system with different energy sources. Methods: The two area interconnected power system consists of thermal, hydro and wind energy sources in the area-1 and area-2 comprises thermal, hydro and diesel energy sources. The recently developed Jaya Optimization technique is explored to optimize PID controller parameters for the interconnected power system by Matlab. Findings: The dynamic responses of power system is studied including the non-linearities like Governor Dead band (GDB), Generation Rate Constraint (GRC) and boiler dynamics under 1% step load perturbation. Novelty and applications The beauty of Jaya algorithm is that it works with only few control parameters as compared with other algorithms which help in improving dynamic responses and performance values of power system with non-linearities. Hence, the frequency stability is achieved at faster convergence at loads. The comparative analysis of proposed technique with other techniques like Differential Evolution (DE) algorithm and Teaching Learning Based Optimization (TLBO) algorithm for the same power system justify the effectiveness of proposed approach. Keywords: Automatic Generation Control; PID Controller; Nonlinearities; Renewable Sources; Jaya Algorithm

Design of event trigger based multirate sliding mode load frequency controller for interconnected power system

This paper proposes an event triggered (ET) multi-rate output feedback sliding mode control technique for load frequency control (LFC) in multi-area interconnected power systems. Uncertainties and disturbances are commonly found in LFC problem. The designed controller attains quasi sliding mode in discrete time (DT) for linear time invariant (LTI) interconnected power executing system with limited matched variability. Event-triggered control is used to minimalize the control updates resulting in reduced utilization of resources. The ET rule is designed using Lyapunov stability analysis. The efficacy of the presented controller in the presence of generation rate constraint (GRC) and governor dead band (GDB) is authenticated through simulation results. A comparative study of the proposed controller and the reported ET control scheme for power executing system is also presented for a peer-reported two-area power executing system.

Optimal model predictive control of energy storage devices for frequency stability of modern power systems

Load Frequency Control (LFC) has become a more challenging issue, especially with the increases in generation's unpredictability, inconsistency, and load variations leading to reduced system stability and reliability. This paper presents a novel application of the transient search optimization (TSO) upon Model Predictive Control (MPC) based regulators to solve the LFC problem for multiple zones power networks with hybrid renewable generators and storage devices. An exact model with a governor's dead band, generator's rate constraint, and measurement communication delay are employed. Renewable energy sources (RESs), such as wind and solar systems, in addition to fuel cell generators with different storage elements, such as superconducting magnetic energy storage (SMES) and battery energy storage (BES), are incorporated into the power system investigated in this study. To assess the effectiveness of the TSO-MPC controllers in nonlinear conditions due to renewable energy generation and storage ambiguities, actual wind speed measurements are incorporated into the wind generation model and real solar irradiance and temperature data for the photovoltaic system to achieve an extra credible analysis. Furthermore, the performance of the TSO-MPC regulator is compared with the performance of other optimization techniques based on proportional-integral-derivative (PID) controllers under different conditions, and the results of the proposed controller outperform other controllers by >10 % of the transient specifications. The transient response of the power system is significantly enhanced with the controller proposed in this study.

A New Fractional-Order Load Frequency Control for Multi-Renewable Energy Interconnected Plants Using Skill Optimization Algorithm

Connection between electric power networks is essential to cover any deficit in the generation of power from any of them. The exchange powers of the plants during load disturbance should not be violated beyond their specified values. This can be achieved by installing load frequency control (LFC); therefore, this paper proposes a new metaheuristic-based approach using a skill optimization algorithm (SOA) to design a fractional-order proportional integral derivative (FOPID)-LFC approach with multi-interconnected systems. The target is minimizing the integral time absolute error (ITAE) of frequency and exchange power violations. Two power systems are investigated. The first one has two connected plants of photovoltaic (PV) and thermal units. The second system contains four plants, namely, PV, wind turbine, and two thermal plants, with governor dead-band (GDB) and generation rate constraints (GRC). Different load disturbances are analyzed in both considered systems. Extensive comparisons to the use of chef-based optimization algorithm (CBOA), jumping spider optimization algorithm (JSOA), Bonobo optimization (BO), Tasmanian devil optimization (TDO), and Atomic orbital search (AOS) are conducted. Moreover, statistical tests of Friedman ANOVA table, Wilcoxon rank test, Friedman rank test, and Kruskal Wallis test are implemented. Regarding the two interconnected areas, the proposed SOA achieved the minimum fitness value of 1.8779 pu during 10% disturbance on thermal plant. In addition, it outperformed all other approaches in the case of 1% disturbance on the first area as it achieved ITAE of 0.0327 pu. The obtained results proved the competence and reliability of the proposed SOA in designing an efficient FOPID-LFC in multi-interconnected power systems with multiple sources.

A novel computational technique using coefficient diagram method for load frequency control in an interconnected power system

This paper proposes a novel load frequency control (LFC) approach formulated on an optimal structure of the coefficient diagram method (CDM) in a two-area thermal power system. As part of a realistic analysis, nonlinearities related to governor dead band (GDB) and generation rate constraint (GRC) have been considered. In this article, a hybrid CDM method is combined with the optimization of its mathematical equations to achieve an innovative controller. Furthermore, a new metaheuristic optimization technique called the water cycle algorithm (WCA) is used to determine the optimal coefficients of the CDM controller. For the purpose of demonstrating the validity of the proposed scheme, a wide range of uncertainties in the dynamic parameters of a nonlinear power system were tested. In addition, a comparative study is presented between the results obtained from a classical integral, CDM alone, optimized fuzzy, optimized PID, and the suggested controller. In this new approach to improved control, algebraic support provides a robust and responsive controller that can provide fast and stable dynamic responses and effectively overcome the detrimental effects of nonlinearities and uncertainties in the parameters of the power system.

A Dual-Stage Controller for Frequency Regulation in a Two-Area Realistic Diverse Hybrid Power System Using Bull–Lion Optimization

In this article, a dual-stage proportional integral–proportional derivative with filter (PI–PDF) controller has been proposed for a hybrid two-area power system model having thermal-, hydro-, gas-, wind-, and solar-based power generating sources. Superconductor magnetic energy storage (SMES) units to cope with the transient power deviations have been incorporated in both areas. Governor dead-band (GDB) is considered in the governor model of thermal, and a generation rate constraint (GRC) is considered in the thermal and hydro turbine models to analyze the impact of system nonlinearity. The parameters of the proposed control strategy are optimally tuned by deploying a newly developed bull–lion optimization (BLO) to maintain optimal frequency and power response during system load deviations. Variations in wind speed and PV solar irradiance data have been included to examine the effectiveness of the BLO-based PI–PDF controller with system uncertainties and variability of renewable energy sources. The obtained results are validated by comparison with recently developed existing optimization techniques. The results revealed that the proposed control strategy is efficient for regulating the frequency and tie-line power of renewable integrated power systems. Further, the BLO-based PI–PDF control strategy improved the performance in terms of performance indices like settling time and peak overshoot/undershoot in wide scale.

A maiden robust FPIDD2 regulator for frequency-voltage enhancement in a hybrid interconnected power system using Gradient-Based Optimizer

This paper proposes a maiden intelligent controller design that consists of a fuzzy proportional-integral-derivative-double derivative (FPIDD) controller whose parameters are fine-tuned using the Gradient-Based Optimization algorithm (GBO). The proposed FPIDD2 regulator is employed as a secondary regulator for stabilizing the combined voltage and frequency loops in a two-area interconnected power system. The proposed FPIDD2 controller is tested in a two-area hybrid system, with each area comprising a mix of traditional (thermal, gas, and hydraulic power plants) and renewable generation units (wind and solar power). Additionally, the proposed controller takes into account system nonlinearities (such as generation rate limitations and governor deadband), system uncertainties, and load/renewables changes. The dynamic responses of the system demonstrate that FPIDD2 has superior ability to attenuate the deviations in voltage and frequency in both areas of the system. In the investigated hybrid system, the suggested FPIDD2 is compared to a GBO-tuned integral derivative tilted (ID-T) controller and FPID controller. As a fitness function for the GBO, the criteria of minimizing the integral time absolute error (ITAE) are applied. The results are presented in the form of MATLAB/SIMULINK time-domain simulations. The simulation outcomes prove that the presented controller has an outstanding performance compared with the other control strategies in the dynamic response of the system in terms of rising and settling times, maximum overshoot, undershoot values and ITAE. The ITAE value of the FPIDD2 regulator tuned by the GBO technique was enhanced by 90.9% with the GBO-based ID-T and 55.4% with GBO-based FPID controllers.

Fractional order control strategy for superconducting magnetic energy storage to take part effectually in automatic generation control issue of a realistic restructured power system

Keeping frequency regulation (FR) while fulfilling bilateral contracts and pool-co transactions simultaneously in a competitive environment become a challenging task for solitary automatic generation control (AGC) owing to inherent nonlinear limitations like generation rate constraint (GRC), governor dead band (GDB), and communication time delay (CTD) in realistic power systems. An effective solution to help AGC is employing rapid-response energy storage devices (ESDs) like superconducting magnetic energy storage (SMES). It is an appropriate choice for applications like AGC which need to deliver a large amount of power within such little time. Although employing the SMES in the AGC issue has been addressed widely in literature, however, the considered SMES models have fundamental weak points which are explained thoroughly in this paper. A comprehensive literature review reveals that the lack of an efficient control strategy implemented on the real dynamics of the SMES unit remains unsolved and needs further investigation. In this paper, a maiden supplementary control approach based on fractional order controllers (FOCs) is put forward for the SMES per its real dynamics to take part effectually in the deregulated AGC. The concurrent design of the proposed SMES and AGC is treated as a nonlinear minimization issue wherein an appropriate performance index is minimized utilizing different meta-heuristic algorithms. To achieve realistic and reliable results, a fully competitive two-area various-GENCOs multiple-DISCOs power system is taken into consideration for examinations with taking into account the nonlinearity sources of GDB and GRC. Detailed investigations are conducted under different contract violation scenarios and different CTDs to assess the competency of the suggested SMES model. The robust behavior of the proposed SMES-AGC coordinated control is verified using sensitivity analyses. The simulation results confirm the superiority of the presented SMES model and control strategy over the former models to enhance AGC performance.

An effective method based on simulated annealing for automatic generation control of power systems

In this study, a novel hybrid Simulated Annealing-Genetic Algorithm (hSA-GA) is proposed. In the hSA-GA, population-based SA is used and each solution in the population is improved using the local search operator. The information exchange between the improved solutions is provided by the crossover operator. A new selection operator is used to ensure the balance between intensification and diversification. The hSA-GA is tested first on nine benchmark functions. Then it is used for tuning proportional–integral–derivative (PID) parameters for automatic generation control (AGC) of multi-area interconnected power systems. Firstly, PID parameters are determined with hSA-GA on a two-area interconnected non-reheating thermal system (System-1) in two different generator time constants. Secondly, to demonstrate the effect of supplementary control in AGC systems, the system is simulated with hSA-GA tuned PID controller and without controller. Additionally, the performance of the proposed hSA-GA is observed on AGC system of two area thermal power system with governor dead-band (GDB) nonlinearity (System-2). Transient responses of Δf1, Δf2 and ΔPtie obtained for both System-1 and System-2 are compared with studies on the same systems in the literature and it is seen that hSA-GA exhibits better control performance on power systems than compared studies. The proposed algorithm shows the best performance in System-1 (when Tg=0.08). Accordingly, settling times of Δf1, Δf2 and ΔPtie are reduced to 2.33 s, 3.783 s and 3.11 s, respectively. Finally, the non-linear two area thermal power system is tested with a load varying between ±50% for 180 s to validation of proposed algorithm and results are compared relevant studies.

Optimal design of fuzzy-PID controller for automatic generation control of multi-source interconnected power system

This paper suggests a fuzzy logic controller (FLC) structure from seven membership functions (MFs) and its input–output relationship rules to design a secondary controller to reduce load frequency control (LFC) issues. The FLC is coupled to a proportional–integral–derivative (PID) controller as the proposed FPID controller, which is tuned by an optimized water cycle algorithm (WCA). The proposed WCA: FPID scheme was implemented with two models from the literature under the integral time absolute error cost function. Initially, a two-area non-reheat unit was implemented, and the gains of PID and FPID controllers were adjusted to verify the suitability of WCA in solving LFC issues. Then, in order to identify the robustness of the closed-loop system, sensitivity analysis is carried out. Additionally, a two-area non-reheat unit was tested under the governor dead band nonlinearity. To guarantee the suitability of the proposed FPID controller, a model with a mixture of power plants, such as reheat, hydro, and gas unit in each area was carried out with and without the HVDC link, which can increase practical issues with LFC. The proposed controller's robustness was studied for all models under numerous scenarios, step load perturbations (SLP), and different objective functions. Simulation results proved that the proposed FPID controller provided superior performance compared to recently reported techniques in terms of peaks and settling time.

Impact of electric vehicles and realistic dish‐Stirling solar thermal system on combined voltage and frequency regulation of multiarea hydrothermal system

AbstractThe effective and reliable operation of an interconnected power system (PS) is a major concern, because of the large amount of power contribution from the intermittent renewable energy sources to the power grid. Energy storage (ES) devices are employed to enhance the reliability of the PS operation. Electric vehicles (EVs) are a novel type of distributed ES device that may be utilized to compensate for power imbalances. This paper discusses the participation of EVs for combined frequency and voltage control under conventional PS along with a thermal, hydro, realistic dish‐Stirling solar thermal system (RDSTS). Appropriate physical constraints such as governor dead band and generation rate constraints are equipped with thermal and hydro plants, and communication delay between the generating unit and load dispatch center is considered. An aggregate EVs model, RDSTS, and a new cascade controller named fractional‐order proportional‐derivative with filter coefficient cascaded with tilt‐integral‐derivative (CFOPDN‐TID) controller are provided in all areas for various studies. An artificial flora algorithm is employed to determine the optimal value of the various controller parameters under several scenarios. The system dynamics of the CFOPDN‐TID controller outperform the proportional‐integral‐derivative (PID) and TID controllers under various conditions. The incorporation of EVs improves the system performance in terms of less settling time, and peak deviation, and reduce oscillations. The system performance degrades with increases in the communication time delay of the EVs. The integration of RDSTS into the system provides better dynamics than the dish‐Stirling solar thermal system. Numerous studies have been conducted to validate the robustness of the proposed CFOPDN‐TID controller.

Type-2 fuzzy-based branched controller tuned using arithmetic optimizer for load frequency control

ABSTRACT Frequency deviations are triggered by load changes and the inclusion of renewable energy sources. Hence, a novel type-2 fuzzy proportional derivative-integral control tactic is suggested for controlling load frequency in a deregulated power system with distributed generating (DG) units and plug-in electric vehicles (PEVs). The suggested controller is tuned with arithmetic optimizer (AO) to minimize the integrated time-squared error. Practical constraints such as boiler characteristics, governor dead bands, and generation rate constraints are incorporated into the thermal system. Simulations show the superiority of the suggested scheme compared to integral, proportional-derivative, proportional-integral, proportional-integral-derivative, and type-1 fuzzy logic proportional-derivative branched with integral controllers in rejecting step load disturbances occurring in frequency deviations and tie-line power. Furthermore, the dominance of the suggested AO over other well-known evolutionary methods is established by performing comparative studies. The robustness of the suggested strategy is also studied by considering ±30% perturbation in various system parameters. Moreover, the efficiency of the suggested scheme in rejecting random load disturbance, and the effect of integrating DG units and PEVs on the system are also studied. Finally, the suggested control scheme’s dominance is also demonstrated by comparing the results with previously reported control strategies. The maximum frequency deviation in area-1 is improved by 1.35% while that of area-2 is improved by over 6.70% as compared to reported works.

Coordinated Control of ALFC-AVR in Multiarea Multisource Systems Integrated with VRFB and TCPS Using CFPDN-PIDN Controller

The article discusses the coordinated effect of the vanadium redox flow battery (VRFB) and thyristor control phase shifter (TCPS) on combined automatic load frequency control and automatic voltage regulator of three area hydrothermal systems incorporating renewable sources. Solar thermal power plant, dish-Stirling solar thermal system, and geothermal power plant are integrated into Area-I, Area-II, and Area-III, respectively. Suitable generation rate constraint and governor dead-band are considered for both thermal and hydro plants. A new fuzzy logic-based cascaded controller named fuzzy proportional-derivative with filter coefficient cascaded with proportional-integral-derivative with filter coefficient (CFPDN-PIDN) is proposed as a secondary controller and its performance is compared with the PIDN and CPDN-PIDN controllers. Various controller parameters are optimized by the artificial flora algorithm. Simulation results reveal that the CFPDN-PIDN controller outperforms the PIDN and CPDN-PIDN controllers. Two types of control schemes are used to regulate the TCPS's phase angle variation: Type-I is a first-order lag transfer function, while Type-II includes a washout filter and lead-lag compensator along with Type-I. Analysis shows that the Type-I control strategy is better than Type-II. VRFB charging/discharging is regulated using high-pass filter (HPF) and dead-band (DB) control schemes. Investigation reveals that the BD scheme provided better system dynamics than the HPF scheme. Moreover, the system performance degrades with very high or low state-of-charge values. Further, using the best control schemes for both VRFB and TCPS, the system's dynamic performance was superior to that of the individual one. Finally, the robustness of the proposed control approach is validated through sensitivity analysis.

Novel chaos game optimization tuned-fractional-order PID fractional-order PI controller for load\u2013frequency control of interconnected power systems

In this work, chaos game optimization (CGO), a robust optimization approach, is employed for efficient design of a novel cascade controller for four test systems with interconnected power systems (IPSs) to tackle load–frequency control (LFC) difficulties. The CGO method is based on chaos theory principles, in which the structure of fractals is seen via the chaotic game principle and the fractals’ self-similarity characteristics are considered. CGO is applied in LFC studies as a novel application, which reveals further research gaps to be filled. For practical implementation, it is also highly desirable to keep the controller structure simple. Accordingly, in this paper, a CGO-based controller of fractional-order (FO) proportional–integral–derivative–FO proportional–integral (FOPID–FOPI) controller is proposed, and the integral time multiplied absolute error performance function is used. Initially, the proposed CGO-based FOPID–FOPI controller is tested with and without the nonlinearity of the governor dead band for a two-area two-source model of a non-reheat unit. This is a common test system in the literature. A two-area multi-unit system with reheater–hydro–gas in both areas is implemented. To further generalize the advantages of the proposed scheme, a model of a three-area hydrothermal IPS including generation rate constraint nonlinearity is employed. For each test system, comparisons with relevant existing studies are performed. These demonstrate the superiority of the proposed scheme in reducing settling time, and frequency and tie-line power deviations.

A Robust Fractional-Order PID Controller Based Load Frequency Control Using Modified Hunger Games Search Optimizer

In this article, a recent modified meta-heuristic optimizer named the modified hunger games search optimizer (MHGS) is developed to determine the optimal parameters of a fractional-order proportional integral derivative (FOPID) based load frequency controller (LFC). As an interconnected system’s operation requires maintaining the tie-line power and frequency at their described values without permitting deviations in them, an enhanced optimizer is developed to identify the controllers’ parameters efficiently and rapidly. Therefore, the non-uniform mutation operator is proposed to strengthen the diversity of the solutions and discover the search landscape of the basic hunger games search optimizer (HGS), aiming to provide a reliable approach. The considered fitness function is the integral time absolute error (ITAE) comprising the deviations in tie-line power and frequencies. The analysis is implemented in two networks: the 1st network comprises a photovoltaic (PV) plant connected to the thermal plant, and the 2nd network has four connected plants, which are PV, wind turbine (WT), and 2 thermal units with generation rate constraints and governor dead-band. Two different load disturbances are imposed for two studied systems: static and dynamic. The results of the proposed approach of MHGS are compared with the marine predators algorithm (MPA), artificial ecosystem based optimization (AEO), equilibrium optimizer (EO), and Runge–Kutta based optimizer (RUN), as well as movable damped wave algorithm (DMV) results. Moreover, the performance specifications of the time responses of frequencies and tie-line powers’ violations comprising rise time, settling time, minimum/maximum setting values, overshoot, undershoot, and the peak level besides its duration are calculated. The proposed MHGS shows its reliability in providing the most efficient values for the FOPID controllers’ parameters that achieve the lowest fitness of 0.89726 in a rapid decaying. Moreover, the MHGS based system becomes stable the most quickly as it has the shortest settling time and is well constructed as it has the smallest peak, overshoots at early times, and then the system becomes steady. The results confirmed the competence of the proposed MHGS in designing efficient FOPID-LFC controllers that guarantee reliable operation in case of load disturbances.

Frequency regulation of a RES integrated power system with AC/DC parallel link employing a fuzzy tuned fractional order controller

Abstract This paper demonstrates the operational efficacy of a newly proposed fuzzy tuned fractional order controller to offer an improved frequency regulation of a multi area renewable energy source (RES) integrated nonlinear power system. The effect of governor dead band nonlinearity and generation rate constraint of hydro and thermal power plants are considered in the system. Moreover, a proposed appropriate High voltage direct current (HVDC) tie line model is incorporated in this work, to verify the frequency deviation. Different test cases are applied to verify the robustness of the controllers on frequency response. The superiority of the proposed controller upon Proportional integral and derivative (PID), fuzzy logic controller and fuzzy PID controller in minimizing frequency deviation has been verified through MATLAB SIMULINK environment.