Load Disturbance Research Articles

Takagi-Sugeno fuzzy gain controller for Vehicle-to-Grid (V2G) load frequency control

Load Frequency Control (LFC) has gained more importance with the introduction of deregulated Renewable Energy Sources (RES) connectivity with the grid. Electrical Vehicles (EVs) can feed electricity back into the grid in Vehicle-to-Grid (V2G) mode to maintain stability. However, the increasing number of EVs penetrating the grid causes frequency instability in the power system. If required, EVs may utilize bi-directional chargers to transfer power back to the grid in the V2G mode while they are charging or in a grid-connected state, restoring the frequency instability of the grid. The frequency restoration response time is important to reset the grid frequency fluctuations in the shortest time possible to avoid shutting down the power system. This paper presents a Takagi-Sugeno (T-S) fuzzy linear output controller for LFC in two-area systems with tie-line control. This work models EV batteries as a single lump of large-capacity battery energy storage systems. The EV's battery system provides ancillary power to the two-area power system to reset it to a steady state after a load disturbance. The T-S fuzzy controller's linear output dependency on its inputs enables it to respond efficiently to load variations in the nonlinear two-area power systems. The proposed controller parameters are evaluated from stability analyses and its robustness is tested with sensitivity analysis. It is compared with other fuzzy controllers, and it demonstrates a fast-settling time and reduced frequency deviation response.

Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration

Concerns over fossil fuel emissions and their hazardous effects have led to a shift away from conventional power plants and focus more on the expansion of renewable energy sources. This shift has resulted in reduced inertia and resulted in poor frequency control within electrical power systems. Hybrid Energy Storage Systems (HESS) have been proposed as an effective solution to enhance frequency stability and address the reduced inertia issue. This research evaluates three distinct control models for HESS, Incorporating Supercapacitor Energy Storage (SCES) and Battery Energy Storage Systems (BESS). To optimize the control parameters with the best objectives, all possible sets of objectives with four different optimization algorithms are studied. The three control models considered for the HESS incorporate Virtual Synchronous Generator (VSG) or Virtual Inertia (VI) control with independent or simultaneous optimization of control parameters. The performances of the three control models are evaluated based on three test scenarios incorporating uncertainties, reduced inertia, and uniform and random load disturbances. The findings indicate that the Independently Optimized Virtual Synchronous Generator HESS (IO VSG-HESS) achieves the best settling time post-contingency but offers the least improvement in frequency nadir with an average of 0.31 %. Conversely, the Simultaneously Optimized Virtual Inertia And Virtual Synchronous Generator Controlled HESS (SO VI-VSG-HESS) excel in mitigating small frequency fluctuations with an average improvement in frequency standard deviation of 87.65 %. The Simultaneously Optimized Virtual Synchronous Generator Controlled HESS (SO VSG-HESS) provides the best frequency nadir, with an average improvement of 0.63 %, but with a slight increase in settling time.

Enhanced frequency control of a hybrid microgrid using RANFIS for partially shaded photovoltaic systems under uncertainties

Nowadays environmental concerns and fossil fuel limitations, as well as economic benefits and technical issues such as reliability lead conventional distribution networks to smart microgrids, where the renewable energy resources are merged with the grids. Nevertheless, the systems face new challenges due to the intermittent nature and uncertainties in the distributed generations, which cause frequency fluctuations in the microgrid. The photovoltaic cells are the main part of the contemporary microgrids. Although the photovoltaic (PV) systems depend on solar irradiance, and temperature and are affected by the partial shading phenomenon they could contribute to improving the microgrid frequency stability with a proper control scheme. In this paper, the frequency control strategy is designed for a hybrid stand-alone microgrid, which is robust against load disturbances, variations in weather conditions, and uncertainties in the microgrid parameters. The proposed intelligent control scheme relies on the Recurrent Adaptive Neuro Fuzzy Inference System (RANFIS). The Whale Optimization Algorithm (WOA) is employed to optimize the RANFIS controller structure and generate the parameters of membership functions. In this multi-objective optimization, the objectives are settling time (ST), overshoot (Osh), and Integral Square Error (ISE). The simulation results verify the high robustness and performance of the proposed RANFIS controller, compared to other controllers, during various operational circumstances, as well as the sporadic behavior of renewable energy resources (RES) such as fluctuations in solar radiation and certain uncertainties in the microgrid parameters.

Study on the time delay failure characteristics of sandstone unloading under dynamic disturbance

The rockburst caused by underground engineering excavation exhibits a significant lag effect. Studies have shown that the occurrence of lag-type rockburst is closely related to the delayed failure of rocks. This paper focuses on the delayed failure characteristics of unloading-damaged sandstone under the combined action of static load and dynamic disturbance. Numerical simulations are utilized to analyze the delayed failure evolution characteristics and failure mechanisms of sandstone. The results indicate that in triaxial unloading delay failure tests, the duration of loading decreases exponentially with the increase of initial unloading damage. Compared to static load conditions, the duration of loading under dynamic disturbance decreases by more than 43 %, and the average strain rate significantly increases. The number of cracks at the endpoint of triaxial unloading delay failure increases as initial unloading damage decreases, with a substantial increase in the number of cracks under dynamic disturbance. These findings provide a valuable reference for the timeliness and delayed rockburst analysis and interpretation of rock damage and failure under high-stress levels.

Effects of impedance-boundary-controlled casing treatment on the fan performance with eccentric inlet swirl

An eccentric inlet swirl, a source of circumferential non-uniformity in aero-engines, can compromise the stable operational range of the compression system and potentially jeopardize the safety of the entire flight vehicle. This study experimentally examined the additional effects of an eccentric inlet swirl on an axial fan in comparison with a concentric inlet condition. Then, the effectiveness of an impedance-boundary-controlled (IBC) casing treatment (CT) in extending the stable operating range of the fan under eccentric inlets is evaluated. Steady-state loading and prestall disturbance analyses were conducted using a five-hole probe and high-frequency response pressure transducers to elucidate the instability mechanisms of fans exposed to eccentric inlets. The findings indicate that the eccentric swirl generates localized over-loading regions around the circumference, where abnormal prestall disturbances amplify in amplitude across a frequency range of 0.3 to 0.5 times the blade passing frequency. These characteristics were mitigated when IBC CT was applied over the rotor tip, allowing the fan to operate under concentric inlet conditions. The IBC CT enhances the stall margin of the fan by 9.3–19.6% in response to a range of swirl inlet conditions, suggesting its potential to address the irregularity problems in fans/compressors. The mechanisms by which IBC CT extends the stall margin are discussed from the unique perspective of evaluating steady loading and system damping.

Enhancing disturbance rejection in boost converter for CPL: A controller design approach with partial pole placement and approximate model matching

In DC microgrids, the cascade operation of the DC-DC converters leads to a constant power load fed by the boost converter, resulting in unstable behavior in addition to the non-minimum phase dynamics. An enhanced load disturbance rejection control scheme based on partial pole placement and an approximate model matching technique is proposed. This approach is inspired by the well-known direct synthesis method to achieve optimal load disturbance rejection performance. The effectiveness of the proposed control scheme has been validated through hardware implementation, demonstrating its capability in setpoint tracking and load disturbance rejection under variations in load power and input voltage. The robust stability of the suggested scheme has been investigated through the Kharitonov theorem and Monte-Carlo simulation, considering different performance matrices. The suitability of the presented scheme has been established by analyzing the comparative performance of recently reported works. The proposed controller reduces peak overshoot and settling time by ∼50%, handles system uncertainties up to 75%, and outperforms FOPID controllers tuned with particle swarm optimization, queen bee genetic algorithm, and chaos game optimization methods.

Apply Honey Barger Algorithm to double integral sliding mode observer for stable load frequency in multi-area power system

A randomness of load demand and plant uncertainties causes frequency deviation in linked power plants. Based on the double-integral sliding mode observer (DISMO) integrated Honey Badger algorithm (HBA), a novel LFC for a multi-area power plant (MAPP) is introduced in this article. The main aim is to minimize frequency offset, finite time, and aggregate instability of controllable loads subject to the balance of the power on the MAPP. Firstly, the suggested observer is developed to ensure an exact estimation of the actual signal for the controller input signal. Secondly, a double-integral sliding surface (DISS) is introduced based on estimated signals the designed observer gains. Then, a new SMC rule is designed to ensure finite time reachability and eliminate the chattering and oscillating troubles. Thirdly, in this regard, the proposed sliding surface is designed with four selected parameters. Regarding this, to maximize the ability of the suggested SMCer, the optimized controller parameters are determined by HBA. The robustness of the suggested scheme is examined by various case studies on the LFC models in a single-area power plant (SAPP) and MAPP under different load disturbances and parameter uncertainties.

A Robust Super Twisting Controller Algorithm for Dual Star Induction Motor Based on Particle Swarm Optimization Algorithm

This research introduces an optimized control approach for a dual star induction motor (DSIM) using a combination of the Super Twisting Algorithm (STA) and Particle Swarm Optimization Algorithm (PSO) within the framework of indirect field-oriented control (IFOC) and two pulse width modulation (PWM) voltage sources. The primary aim of this study is to reduce torque fluctuations, minimize variations in stator current, and enhance the precision of speed control. The DSIM consists of two sets of three-phase windings with separate neutrals and a 30-degree electrical phase shift. The utilization of the STA control method addresses issues related to response time, steady-state error, and the impact of load disturbances, ultimately improving speed control. The Simulation conducted in MATLAB/SIMULINK are used to compare the performance of the proposed STA-PSO controller against a conventional Proportional-Integral (PI) controller. The outcomes demonstrate the substantial enhancements achieved by the STA-PSO controller in speed control, including reduced response time, improved steady-state error, and increased resilience against external disturbances. The proposed STA-PSO control strategy effectively mitigates torque and stator currents fluctuations in DSIM’s while offering superior speed control performance. These findings underscore the potential of the STA controller for enhancing control in various DSIM applications.

Modeling of dynamic characteristics and μ-synthesis control of piezoelectric positioning platform

Abstract The dynamic hysteresis nonlinearity and various uncertainties of the piezoelectric positioning platform are critical factors limiting its high-precision applications. To address this, the dynamic characteristics of the piezoelectric positioning platform under various loads are identified based on the linearization of the Prandtl-Ishlinskii inverse model. The inverse compensation error and load disturbances are attributed to model uncertainties, which are modeled in the frequency domain. A μ-synthesis controller is designed to improve the tracking accuracy of the piezoelectric positioning platform under uncertainty disturbances. Experimental results indicate that with the μ-synthesis controller, the piezoelectric positioning platform achieves a relative error (RE) of less than 2.71% when unloaded. The RE is less than 6.03% for load disturbances of 100g, 200g, and 300g, respectively. These results demonstrate that the designed controller meets the high-precision positioning performance requirements under various load disturbance conditions.

Modeling of genetic algorithm tuned adaptive fuzzy fractional order PID speed control of permanent magnet synchronous motor for electric vehicle

This study presents a novel Genetic Algorithm-optimized Adaptive Fuzzy Fractional Order Proportional Integral Derivative (GA-AFFFOPID) controller for enhancing the speed control performance of permanent magnet synchronous motor (PMSM) drives in Electric Vehicles. The proposed GA-AFFFOPID controller, which combines the advantages of genetic algorithm optimization and adaptive fuzzy fractional-order PID control, represents a unique and innovative approach to address the control challenges associated with PMSM drives. Permanent magnet synchronous motor technology, known for its efficiency, compactness, reliability, and versatility in motion control applications, is increasingly adopted in electric vehicle drive systems. However, the inherent non-linearity, dynamics, and uncertainties of permanent magnet synchronous motors pose significant control challenges. The exceptional performance of the GA-AFFFOPID controller, demonstrated through its superior system dynamics, precise speed tracking, and robustness against parameter variations and sudden load disturbances, underscores the significant advancements enabled by the genetic algorithm optimization technique in improving the control performance of PMSM drives for electric vehicle applications. Comparative analysis with traditional control methods demonstrates the exceptional performance of the Genetic Algorithm-optimized Adaptive Fuzzy Fractional Order Proportional Integral Derivative controller. These findings highlight the significant performance improvements facilitated by the genetic algorithm optimization technique in enhancing the control performance of the adaptive fuzzy fractional order PID controller in PMSM drives for electric vehicle applications.

A Novel Feedforward Scheme for Enhancing Dynamic Performance of Vector-Controlled Dual Active Bridge Converter with Dual Phase Shift Modulation for Fast Battery Charging Systems

This paper proposes a novel feedforward control scheme to achieve a very smooth transition from Constant Current (CC) to Constant Voltage (CV) charging modes, the commonly used method for electric vehicle charging applications. Furthermore, a three-loop model-independent Linear Active Disturbance Rejection Control (LADRC)-based system is proposed, replacing the traditional two-loop Proportional-Integral (PI) control system. The extra loop performs a decoupled dq vector control of the inductor current, which is typically not used in single-phase Dual Active Bridge (DAB) systems. This additional loop not only facilitates the optimal determination of both internal and external phase shift angles of a Dual-Phase Shift (DPS) modulator but also lowers the peak input current of the converter, allowing for lower-rated switches. Numerical simulations using MATLAB/Simulink demonstrate the robustness of the proposed control strategy against both input voltage disturbances and load disturbances during the transition from CC to CV charging modes. Hence, the dynamic performance of the charging system is significantly improved with minimal controller effort.

A Decoupled Feedback and Fast Norm Optimal Control approach for Normal and Superconducting RF Cavity disturbances compensation

Iterative learning controller (ILC)s of different types have been used in various engineering applications for system control in presence of repetitive disturbance, often encountered in batch control systems. A particle accelerator usually comprising of Radiofrequnecy (RF) cavities, when operated in pulsed mode processes particle beam similar to that in batch systems. However, an injected particle beam disturbs electric field inside RF cavity. In additions to beam loading disturbance encountered in all types of RF cavities, a superconducting cavity also encounters disturbance due to Lorentz force detuning. Under presence of such persisting disturbance/s, a Fast Norm Optimal ILC (FNOILC), helps achieve specified amplitude and phase stability of electric field, which results in beam of specified quality. A sophisticated control system helps achieve this objective. In this paper, FNOILC technique is explored for this purpose. Though, it has been reported for few accelerator facilities, in this work, a decoupling strategy is used in a feedback control loop, resulting into overall enhancement of control performance. Behavioral model of RF cavity is represented as dual input dual output system exhibiting two loops, found interacting due to nonzero cavity detuning. A decoupler is designed based on well known technique/s used in process control applications. Relative gain array element values are used to quantify interaction. In presence of beam loading disturbance, a FNOILC demonstrates an excellent control performance. A standard performance index has been used to assess control performance. It is found that use of decoupler in main feedback loop of RF cavity, enhances the resulting performance index. Besides, an ILC performance needs assessment with practical issues like model uncertainty, sensing delays, high detuning and observation noise. In this paper, most of conclusions are drawn based on large number of modeling and simulation studies carried out for lab prototype 650MHz cavity. Interesting studies like effects of low controller sampling frequency, feedback controller gain tuning, severe detuning, etc. are presented using a novel state plane representation. A zero phase filtering is simulated and proposed as an effective strategy when measurements have noise. This paper forms a case study which can be applied to any general system encountering repetitive disturbance. Additionally, paper also elaborates on FNOILC algorithm application for Lorentz force detuning compensation often encountered in superconducting cavity during pulse mode of operation.

Output speed control for hydro-mechanical continuously variable transmission of tractor.

In order to improve the speed stability of tractors equipped with hydro-mechanical continuously variable transmission (HMCVT) during field operations, the speed regulation characteristics, torque characteristics, and power diversion characteristics of HMCVT are analyzed. And a comprehensive control strategy for HMCVT output speed is proposed by analyzing the factors affecting the fluctuation of output speed, which combines engine speed control and displacement ratio control of hydraulic speed control system. This strategy adopts fuzzy control to regulate the engine speed to maintain the stability of engine operation. Moreover, adopting feed forward compensation control for speed compensation enhances the anti-interference ability of the hydraulic speed control system. And combined with model predictive control, adjust the swash plate swing angle of the variable pump to reduce the fluctuation of HMCVT output speed. By establishing joint simulation model, the effectiveness of the control strategy was verified using tractor acceleration mode and step load disturbance mode. The results show that the strategy can reduce the fluctuation rate of engine speed and impact degree, shorten the adjustment time, and improve the stability of tractor operating speed.

The mechanism and prevention of rockburst induced by the instability of the composite hard-roof coal structure and roof fractures

Despite the implementation of prevention and control measures, rockburst still occur. The characteristics of composite coal were analyzed by combining monitoring and early warning means. Two types of composite coal in the hard roof were distinguished based on their distinct initiation and destruction processes despite experiencing the same rockburst event. Rockburst caused by structural instability was studied in different mining stages, and the following conclusions were considered. 1) The mechanical model of the instability of composite coal in hard roof was established for different mining stages to reveal rockburst mechanisms. The high-speed advance of working faces changed the fractured structure of upper hard rocks in the pressure-relief protection range. The sudden fracture of long cantilever structures caused dynamic load disturbance to high-stress coal, which resulted in rockburst in the insufficient mining stage. The failure and deformation of coal under high-stress static loads created conditions for the instability and fractures of roof. The disturbance of low hard rock strata aggravated the deformations of damaged coal. Therefore, rockburst appeared in the full mining stage. 2) Structural instability and roof fracture caused by different factors were the main causes of rockburst for composite coal in hard roof in different mining stages. Relevant prevention and control measures were formulated to ensure the safety of working faces, which provided references for the prevention and control of rockburst in working faces under similar conditions.

FOPDT model and CHR method based control of flywheel energy storage integrated microgrid

The main causes of frequency instability or oscillations in islanded microgrids are unstable load and varying power output from distributed generating units (DGUs). An important challenge for islanded microgrid systems powered by renewable energy is maintaining frequency stability. To address this issue, a proportional integral derivative (PID) controller is designed in this article. Firstly, islanded microgrid model is constructed by incorporating various DGUs and flywheel energy storage system (FESS). Further, considering first order transfer function of FESS and DGUs, a linearized transfer function is obtained. This transfer function is further approximated into first order plus time delay (FOPTD) form to design PID control strategy, which is efficient and easy to analyze. PID parameters are evaluated using the Chien-Hrones-Reswick (CHR) method for set point tracking and load disturbance rejection for 0% and 20% overshoot. The CHR method for load disturbance rejection for 20% overshoot emerges as the preferred choice over other discussed tuning methods. The effectiveness of the discussed method is demonstrated through frequency analysis and transient responses and also validated through real time simulations. Moreover, tabulated data presenting tuning parameters, time domain specifications and comparative frequency plots, support the validity of the proposed tuning method for PID control design of the presented islanded model.

Implementation of fuzzy logic controller for positive output LUO converter

This paper describes the fuzzy logic controller (FLC) for a positive output LUO converter (POLC), which uses a voltage controller to achieve the output voltage regulation. The fourth-order POLC DC–DC converter produces positive output voltage utilizing the voltage lift technique. Due to the converter’s switching functions and its inherently time-varying nature, it exhibits a highly nonlinear dynamic response. To enhance the dynamic performance of the converter, controllers are designed using small signal model and frequency response analysis. The closed loop is used to evaluate converter performance in the presence of variations in reference voltage, source voltage and load disturbances. The power loss analysis of the converter is performed. The comparative results show that FLC gives good dynamic response for wide range of variations than the proportional–integral (PI) controller. The prototype model is built using dsPIC (30F4011) microcontroller, and the experimental results are presented to validate the simulation results.

Design and Control of DVR Based on Adaptive Bateman Polynomial for Power Quality Improvement

ABSTRACTPower quality issues encompass a spectrum of disturbances that affect the stability and reliability of the power supply. This study explores voltage‐related anomalies, including sags, surges, flickers, unbalances, harmonics, interruptions, and swells, examining their origins, characteristics, and repercussions. These issues arise from a myriad of sources, such as load fluctuations, equipment malfunctions, and grid dynamics. The ramifications of these disturbances extend to equipment malfunctions, reduced operational efficiency, and financial losses. Dynamic voltage restorer (DVRs) are series custom power devices for mitigating these voltage‐related anomalies and use real‐time monitoring and control to quickly inject exact voltages into the grid during disruptions, restoring voltage levels to acceptable levels. This study demonstrates the capacity of DVRs to successfully alleviate power quality concerns, hence improving equipment dependability and system stability by analyzing case studies and simulation findings. The control system used to supply switching signals to the voltage source converter (VSC) of the DVR is based on adaptive Bateman polynomial (ABMP). Traditional DVR control techniques often rely on fixed or linear control strategies, which may not adequately handle varying load conditions and disturbances. ABMP offers an adaptive approach where the control parameters can adjust dynamically based on real‐time system conditions. This adaptive capability enhances the accuracy of voltage restoration, ensuring that the DVR responds optimally to varying loads and disturbances. During voltage sag and swell conditions at the grid side, the VSC injects the compensating voltage in series with the feeder with a constant switching frequency. A battery energy‐supported system (BESS) based DVR is considered for the proposed system. The supply is connected to the critical and sensitive loads. The proposed control scheme is validated through extensive simulation and experimental results.

Radial Basis Function Neural Network and Feedforward Active Disturbance Rejection Control of Permanent Magnet Synchronous Motor

A composite control strategy is proposed to improve the position-tracking performance and anti-interference capabilities of permanent magnet synchronous motors (PMSMs). This strategy integrates an active disturbance rejection controller (ADRC) and a radial basis function neural network (RBFNN) with feedforward control. Initially, the flexibility and robustness of the ADRC are utilized in the position loop control. Subsequently, the parameters of the extended state observer (ESO) within the ADRC are optimized, benefiting from the fast convergence speed and optimal approximation provided by the RBFNN. To further enhance the dynamic tracking performance, a differential feedforward link is introduced between the desired speed and the output signal. The simulation and experimental results demonstrate that when the expected electrical angle inputs are sinusoidal and pulse signals, the incorporation of the feedforward link and the adjustment of parameters in the ADRC lead to improved position-tracking capabilities and greater adaptability to load disturbances.

Voltage quality improvement method based on adaptive power control of photovoltaic inverter

Abstract With the increasing penetration rate of distributed photovoltaics in the distribution network in China, the energy pressure has been effectively alleviated. However, the voltage over-limit problem of its parallel outlets cannot be ignored. Therefore, this paper put forward a power control method with photovoltaic inverters which is adaptive. First, the principle of photovoltaic voltage overstepping the limit is analyzed, and second, an adaptive control tactic is brought up for the disturbance of the volatile load of photovoltaic output. Finally, combined with the analysis and verification of simulation examples, the results show that the proposed strategy can effectively improve the voltage quality of the grid and prove the effectiveness of the proposed strategy.

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.