Robust Frequency Control Research Articles

Robust finite frequency control for MRF damper-based semi-active suspension systems subject to time delay and hysteresis nonlinearity

Robust finite frequency control for MRF damper-based semi-active suspension systems subject to time delay and hysteresis nonlinearity

Robust frequency control based on sliding mode control with LMI in an island microgrid

Robust frequency control based on sliding mode control with LMI in an island microgrid

Investigations on application of curve fitting in power system inertia estimation

ABSTRACT As the share of renewable energy sources in the power system keeps growing, a new issue with frequency stability – diminishing and changing inertia – has emerged. Estimating power system inertia has received a lot of attention lately in order to market design of synthetic inertia as an additional service and implement timely corrective steps for robust frequency control. Curve fitting technique has emerged as one of the promising techniques for estimation of power system inertia, however, many challenging aspects need to be addressed for its practical applications. This study aims to systematically assess the effectiveness of the curve fitting method under a range of operational parameters and conditions, such as the curve fitting order, the length of data to be used for curve fitting after an event begins, and the length of the moving average filter applied to the frequency data to remove oscillatory and noise from the frequency transient. The simulation studies have been performed on DIgSILENT and MATLAB platforms. The results show that very high and very low order curve fitting results are high errors and the 5th order model with mean error in estimated value of inertia less than 1% has outperformed others. The analysis on various window width of moving average filter found that increasing the window width results in more error. For IEEE-9 bus system, a filter up to 850 ms width has a mean percentage error below 1%. The analysis also revealed that the duration of the data used for curve fitting is not significant. For variation of the duration of the data used for the curve fitting from 50 ms to 500 ms, the estimated inertia values are found to be in a close range of 2.4881 s to 2.5262 s, for the single machine system with H = 2.5 s. The analysis presented in this study will be useful for effective application of curve fitting method in inertia estimation.

Optimized robust control for improving frequency response of delay dependent AC microgrid with uncertainties

Converter-interface-based renewable energy incorporated into modern power systems causes deterioration in power system stability and it is proving to be a main challenge for operators using sluggish traditional generation with a growing share of converter-interface generation, and there is a need for an alternative means to deliver rapid frequency control. This paper proposes two control loops as secondary frequency control, first is an improved optimized delay-dependent frequency control to ensure robust frequency control under daily changes in system parameters that may occur in prospective, renewable-rich future AC microgrids. For a variety of operating conditions, the design process employs a mixed H2/H∞ robust control based on linear matrix inequality (LMI). In second, a speedy-acting improved power stability control loop is utilized as the proposed secondary frequency control, because demand response aggregators can be beneficial for frequency control. Robustness is evaluated against several perturbations and communication delay attacks through dynamic simulation and stability is evaluated by small-signal analysis. Different case studies subject to generation\\load loss, multiple time delay and parameter uncertainties are demonstrated on an interconnected AC microgrid system to verify the performance of the proposed control technique.

Robust Frequency Control of Additive Manufacturing Based Microgrid Considering Delayed Fuel Cell Dynamics

Robust Frequency Control of Additive Manufacturing Based Microgrid Considering Delayed Fuel Cell Dynamics

Recent Trends in High Reliability Timing and Frequency Control Devices for Extreme Environment Applications

Performance requirements for higher reliability extreme environment timing and Frequency control (TF) components have continued to evolve in the recent years. Bulk of this demand has been focused on specific performance attributes governed by system applications. Enhanced performance requirement has become the mainstream of requirements where SWaP (size, weight and power) improvement is interleaved with other critical parameters such as temperature range, frequency tolerance and long-term effects and in some cases the output spectral purity. Trendlines set by customer demand continues to be the main guide for more efficient solutions. Frequency Management International (FMI) has been in the forefront of advancing the performance attributes for Hi-Rel extreme environment components. We continue to proactively respond to the pressing needs and challenges for robust frequency control components that operate under extreme environmental conditions including extreme temperatures ranging from -200ºC to + 500ºC. The material in this writeup covers the more recent performance achievements tied to specific products and form-factors for high temperature applications.

Robust Frequency Control of Provisional Microgrid by Using of a Combined Fuzzy Reset Approach

Robust Frequency Control of Provisional Microgrid by Using of a Combined Fuzzy Reset Approach

Leveraging blockchain technology for resilient and robust frequency control in a renewable-based hybrid power system with hydrogen and battery storage integration

This paper introduces the blockchain-assisted frequency regulation mechanism for achieving resiliency and robustness in a renewable-based hybrid power system (HPS) powered by multiple sources, including wind turbine generators (WTG), hydrogen fuel cells (FC) with aqua electrolyzer (AE), diesel engine generators (DEG) and battery energy storage systems (BESS). Frequency fluctuations are exacerbated by load uncertainties paired with energy-generating source uncertainties resulting from integrating multiple distributed energy resources (DERs) into the national electric power grid. In the event of energy generation loss, efficient load frequency control (LFC) techniques are considered essential for frequency restoration in DER-integrated HPS. In addition, active power regulation data in LFC need secure data storage mechanisms for ensuring cyber-resilience, a transparent cash payout mechanism for the stakeholders in LFC market operation, and related sustainability services. A novel resilient blockchain framework for realizing LFC is proposed for addressing the power resilience and the false-data injection issue. Moreover, a parameter sensitivity algorithm (PSA) constrained optimization methodology using the genetic algorithm (GA) withstands the energy generation loss and uncertainties. A consensus algorithm-based blockchain methodology acts as an enabler for strategic decision-making and secures the data flow to the market operator. The proposed framework-driven methodology is implemented using a Blockchain network developed in python for securing LFC transactions by developing a case study for HPS. Numerous simulation scenarios demonstrate the proposed methodology's effectiveness in establishing a synergistic operative framework for the resilient and robust operation of the hybrid energy system with multiple sources, even in the event of uncertainties.

Robust trajectory-constrained frequency control for microgrids considering model linearization error

Grid supportive modes integrated within inverter-based resources can improve the frequency response of renewable-rich microgrids. The synthesis of grid supportive modes to guarantee frequency trajectory constraints under a predefined disturbance set is challenging but essential. To tackle this challenge, a numerical optimal control (NOC)-based control synthesis methodology is proposed. Without loss of generality, a wind-diesel fed microgrid is studied, where we aim to design grid supportive functions in the wind turbine. In the control design, linearized models are used, and the linearization-induced errors are quantitatively analyzed by reachability and interval arithmetics and represented in the form of interval uncertainties. Then, the NOC problem can be formulated into a robust mixed-integer linear program. The control structure is strategically configured into two levels to realize online deployment. The proposed control is verified on the modified 33-node microgrid with a full-order three-phase nonlinear model in Simulink. The simulation results show the effectiveness of the proposed control paradigm and the necessity of considering linearization-induced uncertainty.

Designing optimized PID controller using improved bacterial foraging optimization algorithm for robust frequency control of islanded microgrid

Designing optimized PID controller using improved bacterial foraging optimization algorithm for robust frequency control of islanded microgrid

H ∞ Robust Frequency Control of Wind Turbine Generators and Electric Vehicles in Isolated grid

Wind turbine generators (WTGs) occupy an increasingly larger share in power system. WTGs in isolated grid lead to fluctuation in power and decrease system inertia. To reduce frequency deviation due to power fluctuation or wind speed change, model of WTGs is established based on deloading control. Considering that WTGs will have institutional wear because of frequent frequency regulation, which would short the life of WTGs, a robust frequency control strategy is proposed. WTGs and electric vehicles (EVs) are used in this control strategy. To suppress disturbances due to wind speed and uncertainty of system parameters, a H ∞ robust controller is solved using linear matrix inequality (LMI) methodology. Time-domain simulation results shows that the adopted control methodology can decrease frequency deviation during power fluctuations and wind speed changes.

Adaptive fractional-order sliding-mode disturbance observer-based robust theoretical frequency controller applied to hybrid wind–diesel power system

This work presents design and theoretical analysis of an adaptive fractional-order sliding-mode disturbance observer (FO-SM-DOB)-aided fractional-order robust controller for frequency regulation of a hybrid wind–diesel based power system, considering endogenous/exogenous system disturbances. Adaptive FO-SM-DOB is designed to estimate unknown/uncertain lumped system disturbances, including parametric uncertainty and exogenous disturbances. Afterwards, an improved fractional-order sliding mode controller (FOSMC) augmented with the estimated output of FO-SM-DOB is designed and applied to accelerate system dynamics with minimum chattering in the control effort. The Mittag-Leffler stability theorem affirms the finite-time convergence of disturbance estimation error. Moreover, the closed-loop asymptotic stability of the overall control system has been guaranteed by applying Lyapunov argument. The effectiveness of the suggested resilient fractional-order nonlinear frequency controller is theoretically validated by performing an extensive comparative study with SMC, FOSMC (without DOB), state observer-based SMC (SOB-SMC), second-order SMC (without DOB), and conventional integer/fractional-order controllers. Simulation results establish the supremacy of the proposed resilient fractional-order nonlinear frequency controller over its other counterparts concerning fast disturbance rejection, weaker chattering, and a high degree of robustness against unknown lumped system disturbances. Further, to demonstrate the practicability and validate the effectiveness of the proposed control strategy, magnetic levitation system and IEEE 39-bus New England power system are considered and successfully tested on MATLAB platform.

Flywheel energy storage system based microgrid controller design and PHIL testing

Microgrids consisting of renewable energy based distributed generators have become popular as a way of energizing off-grid systems. Due to their low-inertia, these distributed generators require a robust frequency control system to maintain it. This problem is amplified by the fact that there is no centralized grid that anchor the system voltage and frequency. For this reason, such off-grid microgrid employs storage systems and diesel generators to provide some flexibility. Flywheel energy storage systems (FESSs) have very quick reaction time and can provide frequency support in case of deviations. To this end, this paper develops and presents a microgrid frequency control system with FESS. The system performance tests are performed with real-equipment where FESS is connected to digital real time simulator. Several frequency events are triggered and the frequency profile is observed to compare microgrid’s performance with and without the developed frequency control. Results show that flywheel energy storage system provides a much smoother frequency profile with less deviations.

Insights on designing effective and efficient frequency control arrangements from the Australian National Electricity Market

For restructured electricity industries undergoing energy transition, designing effective and efficient frequency control arrangements is a complex and ongoing task that requires appropriate configuration of controllers, generator technical connection requirements, market arrangements and wider policy settings. In this paper, we provide an overview and assessment of these arrangements in Australia’s National Electricity Market - a useful case study given its long-standing frequency control ancillary services markets, yet recent challenges in maintaining secure frequency control. We assess the performance of these evolving arrangements in delivering improved frequency control outcomes, with particular regard to growing renewable penetrations and evident tensions between mandatory requirements and market-based incentives. Based on this assessment, we draw out four key insights on designing frequency control arrangements as power system capabilities and needs change: (1) Understanding control action interactions, (2) Implementing efficient price formation and cost-allocation mechanisms, (3) Monitoring and assessing service provision to better align participant remuneration with service quality, and (4) Considering both regulatory and market mechanisms and their consequences and interactions. In particular, we discuss the trade-offs between effective and efficient outcomes, and provide arguments for more robust and forward-looking frequency control arrangements during energy transition.

Pinning Decision in Interconnected Systems with Communication Disruptions under Multi-Agent Distributed Control Topology

In this study, we propose a decision-making strategy for pinning-based distributed multi-agent (PDMA) automatic generation control (AGC) in islanded microgrids against stochastic communication disruptions. The target microgrid is construed as a cyber-physical system, wherein the physical microgrid is modeled as an inverter-interfaced autonomous grid with detailed system dynamic formulation, and the communication network topology is regarded as a cyber-system independent of its physical connection. The primal goal of the proposed method is to decide the minimum number of generators to be pinned and their identities amongst all distributed generators (DGs). The pinning-decisions are made based on complex network theories using the genetic algorithm (GA), for the purpose of synchronizing and regulating the frequencies and voltages of all generator bus-bars in a PDMA control structure, i.e., without resorting to a central AGC agent. Thereafter, the mapping of cyber-system topology and the pinning decision is constructed using deep-learning (DL) technique, so that the pinning-decision can be made nearly instantly upon detecting a new cyber-system topology after stochastic communication disruptions. The proposed decision-making approach is verified using a 10-generator, 38-bus microgrid through time-domain simulation for transient stability analysis. Simulations show that the proposed pinning decision making method can achieve robust frequency control with minimum number of active communication channels.

Adaptive constrained population extremal optimisation‐based robust proportional‐integral‐derivation frequency control method for an islanded microgrid

The expected penetration of renewable sources is driving the islanded microgrid towards uncertainties, which have highly influence the reliability and complexities of frequency control. To alleviate the influence caused by load fluctuations and inherent variability of renewable sources, this article proposes an optimised robust proportional-integral-derivation (PID) frequency control method by taking full advantage of a robust control strategy while simultaneously maintaining the basic characteristics of a PID controller. During the process of iterated optimisation, a weighted objective function is used to balance the tracking error performance, robust stability and disturbance attenuation performance. Then, the robust PID frequency (RPIDF) controller is determined by an adaptive constrained population extremal optimisation algorithm based on self-adaptive penalty constraint-handling technique. The proposed control method is examined on a typical islanded microgrid, and the control performance is evaluated under various disturbances and parametric uncertainties. Finally, the simulation results indicate that the fitness value of the proposed method is 1.7872, which is lower than 2.9585 and 3.0887 obtained by two other evolutionary algorithms-based RPIDF controllers. Moreover, the comprehensive simulation results fully demonstrate that the proposed method is superior to other comparison methods in terms of four performance indices on the most considered scenarios.

Robust frequency control in a standalone microgrid: An adaptive fuzzy based fractional order cascade PD‐PI approach

AbstractIn addition to low system inertia and stochastic nature of the load, the intermittent nature of renewable output power causes hefty frequency deviations in a standalone microgrid (SMG) that lead to weakening and blackout of SMG. Hence in the SMG, the frequency control issue is always a challenging issue for the operators. To enhance the frequency stability of MG, the control action needs to be more efficient and robust. To answer the above challenge, in this article, a novel adaptive fuzzy based fractional order cascade PD‐PI controller is proposed for frequency control of SMG. The proposed controller inherits the merits of both fuzzy and fractional order cascade PD‐PI controllers by ignoring the individual limitations. The parameters of the proposed controller are tuned using a recently developed future search algorithm. The proposed controller is tested against various load and renewable disturbances on a real‐time MG test system. The simulation outcomes reveal that the proposed controller and algorithm enhance the dynamic response of SMG significantly compared to various powerful controllers in the literature. Moreover, the proposed controller performance is more robust to the uncertainties in the MG and energy storage system as compared to the various robust controllers in the literature.

Robust and Resilient Distributed Optimal Frequency Control for Microgrids Against Cyber Attacks

The optimal frequency control of autonomous microgrids (MGs), i.e., to achieve fast frequency recovery and dynamic power adjustment of the distributed generators in proportion to predefined participation factors, can be achieved in a fully distributed way based on the subgradient consensus protocol. However, such a distributively controlled MG is susceptible to different types of cyber attacks infiltrated from different locations. In this article, a robust and resilient distributed optimal frequency control scheme is proposed to address the threat of cyber attacks. It is facilitated by introducing an auxiliary networked system interconnecting with the original cooperative control system. On condition that the cyber attacks are within certain ranges, the robust design can maintain the functionalities by significantly attenuating the impact. Otherwise, the cyber attacks can be easily detected, and resilient reactions can be taken to mitigate their influences via isolation. Simulation results in a modified IEEE 34-bus MG validate the effectiveness of the proposed approach.

Robust Secondary Frequency Control for Virtual Synchronous Machine-Based Microgrid Cluster Using Equivalent Modeling

The technology of virtual synchronous machine (VSM) is attracting interest of researchers as it controls converters mimicking the synchronous machine's response so as to provide inertial support for power electronics dominated smart grids. For the VSM-based microgrid, its slow dynamics are dominated by synchronous generators (SGs) and the VSM control loops, which makes it possible to model this microgrid into an equivalent SG (EqSG) model. This paper proposes a robust secondary frequency control design method for the VSM-based low voltage (LV) microgrid cluster (MGC) using equivalent modeling. The EqSG model is used to construct the MGC model so as to reduce the model order and the complexity of controller synthesis. Modeling errors caused by the EqSG model and different operating conditions are integrated into the MGC model as unstructured uncertainties. The proposed secondary frequency control strategy is based on the distributed-centralized hybrid control structure to coordinate frequency restoration among LV microgrids. Structured μ-synthesis is applied for tuning control parameters realizing H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> robust performance against unstructured uncertainties. To reduce the communication resource consumption, an event-triggered mechanism considering communication delay is introduced in the robust secondary frequency control strategy. The triggering condition is analyzed using a Lyapunov function to guarantee H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> robust stability. Simulation and real-time experiment results on a MGC composed of four CIGRÉ benchmark LV microgrids are presented to demonstrate the effectiveness of the proposed control strategy.

Design and implementation of fault tolerant fractional order controllers for the output power of self-excited induction generator

In this paper, a static volt-ampere-reactive compensator (SVC) composed of fixed capacitor-thyristor controlled reactor (FC-TCR) is employed to regulate the terminal voltage of self-excited induction generator (SEIG) in the purpose of controlling the output power. In addition, the speed of the generator is adjusted by robust proportional-integral-derivative (PID) in order to regulate the frequency. Fractional order PID (FOPID) and Tilt-PID (T-PID) controllers are proposed to adjust the triggering angle of FC-TCR. The objectives of the paper are to design the optimal voltage controller with a robust PID frequency controller and to maintain the output power at a desired level in case of voltage sensor faults. In this regards, nonlinear autoregressive network with exogenous inputs (NARX) and small signal models of the SEIG are constructed where triggering angle and generator speed are inputs, whereas terminal voltage and frequency are outputs, respectively. Training of the NARX model is achieved with a high regression value (R2 = 0.99) where the accuracy of the small signal voltage model is 82%. After comparing the accuracy of the models, NARX-based fault detection architecture and fault tolerant controller are designed in order to avoid incorrect control of the output power. To establish the effectiveness of proposed fault tolerant controllers, simulation studies are conducted using particle swarm optimization (PSO). The designed controllers are performed experimentally on three-phase 5.5 kW, 400 V, 50 Hz, balanced loaded SEIG to confirm the effectiveness. The system is tested with proposed controllers under the healthy sensor, faulty sensor and dynamic reference conditions. Results give good agreement with simulation results and designed fault tolerant T-PID controller performs better tracking dynamics with small deviations whether the voltage sensor is faulty or not.