Frequency Control Research Articles

Robust Distributed Load Frequency Control for Multi-Area Power Systems with Photovoltaic and Battery Energy Storage System

The intermittent power generation of renewable energy sources (RESs) interrupts the balance between power generation and demand load due to the increased frequency fluctuation, which challenges the frequency stability analysis and control synthesis of power generation systems. This paper proposes a robust distributed load frequency control (DLFC) scheme for multi-area power systems. Firstly, a multi-area power system is constructed by integrating photovoltaic (PV) and battery energy storage systems (BESSs). Then, by employing the linear matrix inequality (LMI) technique, the sufficient condition capable of ensuring that the proposed controller satisfies H∞ robust performance in the sense of asymptotic stability is derived. Finally, testing is conducted on a four-area renewable power system, and results verify the strong robustness of the proposed controller against load disturbance and intermittence of RESs.

Enhanced Frequency/Voltage Control in Multi-Source Power System Using CES and SSA-Optimized Cascade TID-FOPTID Controller

The stability and reliability of modern power systems, especially those with several renewable energy sources, strongly rely on load frequency control (LFC) and automatic voltage regulation (AVR) for frequency and voltage control under inconstant load demands. In this study, a new cascade tilt integral derivative-fractional order proportional tilt integral derivative (TID-FOPTID) controller is presented that is polished through the salp swarm algorithm (SSA) for LFC of a multi-area power system with AVR in all control areas. The system integrates capacitive energy storage (CES) and deals with governor dead-band and generation rate constraint nonlinear effects in a thermal-hydro-gas three-area multi-source power system (TAMSPS). The analysis of results, due to the SSA-based TID-FOPTID controller compared to TID-FOTID and TID-FOTID + 1 shows a positive outcome. Integrating CES brings additional improvement in the system performance, the overshoot/undershoot, and settling time are minimized. Finally, the sensitivity analysis reveals that the suggested controller will be effective and reliable for enhancing the frequency stability of the complex power system with a high RES integration level.

Study on improved control strategy of virtual synchronous generator

Virtual synchronous generator (VSG) control technology for photovoltaic, energy storage, wind power, and other new energy to provide flexibility in the grid interface characteristics, is conducive to improving the stability of the power system, and has been widely considered by many scholars. Firstly, an improved VSG control method is proposed through simulation and analysis, which realizes the complete decoupling of the frequency response time constant and the inertia quantity of the active power control loop and reduces the complexity of the parameter design of the VSG system. Secondly, to avoid the frequent action of the VSG system caused by small-scale frequency change perturbation, this study proposes a VSG frequency optimization control method for VSG frequency control with rated angular velocity ωset feedforward composed of multivariate factors when considering a primary frequency regulation dead zone. Thirdly, the impact of VSG parameter design on the system is investigated through the system response characteristics of power scheduling, primary frequency regulation at the grid connection, and the small-signal dynamic characterization of the improved VSG. Finally, Simulation and experimental verification yielded an active power overshoot of 7% and a maximum frequency deviation of 0.17 Hz for the improved system. The improved control method resulted in an improvement of 0.1 s in the frequency response time and a reduction of 0.15 Hz in the oscillation amplitude. The response speed of the improved control method is much better, while the oscillation amplitude is reduced to meet the grid's regulation requirements. The simulation and experimental analysis verify the feasibility of the improved VSG control method.

Optimization of emergency frequency control strategy for power systems considering both source and load uncertainties

With the increasing integration of renewable energy sources and the presence of numerous controllable loads such as electric vehicles and energy storage in the modern power system, higher nonlinearities and uncertainty both sources and loads are introduced. These factors pose challenges in achieving fast and accurate emergency frequency control. Therefore, this paper addresses the issue of dual source-load uncertainties in power system and presents an optimization strategy based on the Soft Actor Critic (SAC) algorithm that involves the participation of controllable loads in emergency frequency control. Firstly, the spatio-temporal uncertainties of wind farm power output on power supply side and power demand on the load side are described using Weibull and normal probability distributions, respectively. Secondly, an improved Markov Decision Process (MDP) model for emergency frequency control is established, which considers the characteristics of the dual source-load uncertainties. Finally, an optimization of the SAC algorithm is conducted based on Deep Reinforcement Learning (DRL), aiming to achieve rapid system frequency recovery and minimize the cost of removing controllable loads. The presented approach in the paper enhances the emergency frequency control strategy for uncertain power systems and effectively addresses the issue of source-load uncertainty compounded by fault power shortages.

Energy Storage Assisted Conventional Unit Load Frequency Control Strategy Using Deep Reinforcement Learning

Energy Storage Assisted Conventional Unit Load Frequency Control Strategy Using Deep Reinforcement Learning

Dynamic Energy Management and Control of Networked Microgrids based on Load to Grid Services and Incentive-Based Demand Response Programs: A Multi-Agent Deep Reinforcement Learning Approach

This study has presented the energy management paradigm in a networked microgrid structure based on L2G services and considering incentive-based load response (IBDR) programs and energy market requirements to reduce operating costs, control and restore voltage and frequency index, providing the benefits of subscribers and distribution system operators. In this study, multi-objective functions such as optimal operation based on IBDR structure and energy market requirements, risk assessment, and L2G service approach are configured in the framework of central and local controllers. Optimal operation and risk assessment are analyzed by a multi-task learning algorithm based on multi-objective function and L2G service policies are evaluated based on multi-agent deep reinforcement learning. Control policies are sent by the communication system to the components affecting the optimal power distribution as well as the voltage and frequency controllers. L2G services have been evaluated in different scenarios such as plug-and-play operating conditions, load fluctuations, and operating in island mode. The results of optimal operation based on L2G services show that the IBDR program implementation reduces the total operation cost by 21%. Also, the total operating cost of the proposed framework is 13.97% less than the RL method and 27.8% less than the ANN method.

The output flexibility optimization control of load-side wind turbine considering client demand response

Abstract This study focuses on optimizing the output flexibility control of load-side wind turbines considering client demand response. Considering the potential and role of client demand response, a load-side wind turbine output objective function was constructed, client demand response constraints were designed, and a two-layer model for flexible optimization control of load-side wind turbine output was constructed. The top is the power allocation hierarchy, and the core objective of this layer is to achieve power optimization distribution of wind turbines under various constraint conditions. The lower layer is the frequency control layer, which optimizes and controls the dynamic frequency of load-side wind turbine output. The experimental results show that the optimized control strategy not only enhances the efficiency of wind turbines, but also effectively reduces energy loss and enhances the stability and reliability of the power grid. Through precise calculation and real-time adjustment of the double-layer model, we can more accurately predict and control the output of wind turbines, thereby ensuring the supply-demand balance of the power grid and reducing potential risks caused by frequency fluctuations and power offsets.

Multi-objective design of fractional frequency-load control for hydro-thermal system considering nonlinear models and uncertainty

One of the crucial quantities in the power system problem is frequency, which should never exceed its nominal value. In normal conditions of load changes, the frequency is adjusted by automatic generation control. Still, in the face of special conditions, such as logging of the downstream network from the main network or a significant amount of generated power leaving the circuit, the power imbalance between generation and consumption causes a rapid frequency drop. In this case, the automatic generation control cannot stop the frequency drop, so the frequency tends toward instability. In this paper, to automatically produce a water-thermal system in two zones of discrete and continuous modes, the design of a fractional controller is discussed and investigated in different functional conditions and uncertainties. The proposed NSGA-II multi-objective method is used in this article to optimize each area’s load frequency control parameters for various goals. The ideal response for the entire network will be obtained by modifying these responses using a multi-factor method. This paper defines a multi-zone frequency load control based on time objective functions and eigenvalues. Based on the speed changes for the proposed algorithm and the novel approachfunction method employed in the control design. The simulation performed and analyzed in different working conditions with different comparative criteria has been discussed and investigated. Compared to more contemporary techniques, the simulation results show that the system’s performance is guaranteed. The main successes of the suggested method in comparison to earlier methods have been the reduction of overshoot, undershoot, and settling time.

H∞- Static Output Feedback based Load Frequency Control of an Interconnected Power System with Regional Pole Placement

H∞- Static Output Feedback based Load Frequency Control of an Interconnected Power System with Regional Pole Placement

A frequency control strategy with DC microgrid systems for EV stations

ABSTRACT Fluctuations in power supply and demand lead to frequency deviations, which have detrimental effects on the operation of electrical devices and equipment. Therefore, the implementation of effective frequency control mechanisms is essential for enhancing the strength and dependability of microgrid systems. Research aims to develop a frequency control mechanism for an electrical grid system that integrates both wind and photovoltaic (PV) energy sources. The proposed system utilises a Doubly Fed Induction Generator (DFIG) system with frequency controller for regulating frequency and balancing source and demand of power in the grid. To optimise the solar power output, a Luo converter is implemented, which offers high efficiency with improved conversion of power. Additionally, an adaptive neuro fuzzy inference system (ANFIS) maximum power point tracking (MPPT) controller is engaged to ensure optimal regulation of photovoltaic system. DC link obtained from the PV system is then utilised for powering DC loads and charging electric vehicles (EVs) effectively. In order to accomplish this, a bidirectional converter is used, which permits power flow in both ways and facilitates effective EV charging from the microgrid system. The validation of research is conducted on MATLAB software, and the results proves greater converter efficiency of 94.93%, with reduced total harmonic distortion (THD) of 1.24%.

A multi-energy inertia-based coordinated voltage and frequency regulation in isolated hybrid power system using PI-TISMC

This paper proposes novel multi-energy inertia support for simultaneous frequency and voltage control of an isolated hybrid power system (IHPS). Multi-energy storage (gas inertia – hydrogen storage, thermal inertia – solar thermal storage, hydro inertia – gravity hydro storage, chemical inertia – battery energy storage) supported by demand side management (DSM) for simultaneous voltage and frequency regulation and backed by biodiesel generators, are the essential elements of IHPS. A novel control strategy of concurrent virtual droop control, virtual damping control, virtual inertia control, and virtual negative inertia control is proposed to utilise multiple inertia sources and to improve LFC and AVR performance effectively. The effective coordination of inertia sources in eradicating oscillations in IHPS, is aided by a developed cascaded proportional integral-tilt-integral-sliding mode (PI-TISMC) controller. The performance of PI-TISMC is compared with PID, PI-PID, and PI-SMC controllers. A maiden attempt has been done by training five diverse classes of optimization techniques to optimize the parameters of controllers in the present work. The results are evaluated in MATLAB and it is evident from the results that the performance of frequency control is improved by 6.5%, 7.8% and 3.4 s (over shoot, undershoot, and settling time). The performance of frequency control is improved by 6.5%, 7.8% and 3.4 s (over shoot, undershoot, and settling time). Similarly, the performance of voltage control is improved by 6.7%, 4.8% and 2.3 s (over shoot, undershoot, and settling time) by employing developed PI-TISMC controller and proposed concurrent inertia control. The combination exhibits superior performance in minimizing oscillations in IHPS due to variations in loading and solar insolation.

Bridging piezoelectric and electrostatic effects: a novel piezo-MEMS pitch/roll gyroscope with sub 10°/h bias instability

This paper proposes a novel piezo-MEMS pitch/roll gyroscope that co-integrates piezoelectric and electrostatic effects, for the first time achieves electrostatic mode-matching operation for piezoelectric gyroscopes. Movement of operated out-of-plane (OOP) mode (n = 3) and in-plane (IP) mode (n = 2) are orthogonal, ensuring that the OOP amplitude is not significantly limited by parallel plates set at nodes of IP mode. Therefore, a large OOP driving amplitude actuated by piezoelectric and frequency tuning in the IP sense mode trimmed by electrostatic can be achieved together with a low risk of pull-in, hence releases the trade-off between the tuning range and the linear actuation range. At a tuning voltage of 66 V, the frequency split decreased from 171 Hz to 0.1 Hz, resulting in a 167x times improvement in sensitivity. The mode-matched gyroscope exhibits an angle random walk (ARW) of 0.41°/√h and a bias instability (BI) of 8.85°/h on a test board within a customized vacuum chamber, marking enhancements of 68x and 301x, respectively, compared to its performance under mode-mismatch conditions. The BI performance of the presented pitch/roll gyroscope is comparable to that of the highest-performing mechanically trimmed piezo-MEMS yaw gyroscopes known to date, while offering the unique advantage of lower cost, better mode-matching resolution, and the flexibility of real-time frequency control.

Tunable 30 GHz laser frequency comb for astronomical spectrograph characterization and calibration.

The search for Earth-like exoplanets with the Doppler radial velocity (RV) technique is an extremely challenging and multifaceted precision spectroscopy problem. Currently, one of the limiting instrumental factors in reaching the required long-term 10-10 level of radial velocity precision is the defect-driven subpixel quantum efficiency (QE) variations in the large-format detector arrays used by precision echelle spectrographs. Tunable frequency comb calibration sources that can fully map the point spread function (PSF) across a spectrograph's entire bandwidth are necessary for quantifying and correcting these detector artifacts. In this work, we demonstrate a combination of laser frequency and mode spacing control that allows full and deterministic tunability of a 30 GHz electro-optic comb together with its filter cavity. After supercontinuum generation, this gives access to any optical frequency across 700-1300 nm. Our specific implementation is intended for the comb deployed at the Habitable-Zone Planet Finder (HPF) spectrograph and its near-infrared Hawaii-2RG array, but the techniques apply to all laser frequency combs (LFCs) used for precision astronomical spectrograph calibration and other applications that require broadband tuning.

Dynamic load frequency control in Power systems using a hybrid simulated annealing based Quadratic Interpolation Optimizer

Ensuring the stability and reliability of modern power systems is increasingly challenging due to the growing integration of renewable energy sources and the dynamic nature of load demands. Traditional proportional-integral-derivative (PID) controllers, while widely used, often fall short in effectively managing these complexities. This paper introduces a novel approach to load frequency control (LFC) by proposing a filtered PID (PID-F) controller optimized through a hybrid simulated annealing based quadratic interpolation optimizer (hSA-QIO). The hSA-QIO uniquely combines the local search capabilities of simulated annealing (SA) with the global optimization strengths of the quadratic interpolation optimizer (QIO), providing a robust and efficient solution for LFC challenges. The key contributions of this study include the development and application of the hSA-QIO, which significantly enhances the performance of the PID-F controller. The proposed hSA-QIO was evaluated on unimodal, multimodal, and low-dimensional benchmark functions, to demonstrate its robustness and effectiveness across diverse optimization scenarios. The results showed significant improvements in solution quality compared to the original QIO, with lower objective function values and faster convergence. Applied to a two-area interconnected power system with hybrid photovoltaic-thermal power generation, the hSA-QIO-tuned controller achieved a substantial reduction in the integral of time-weighted absolute error by 23.4%, from 1.1396 to 0.87412. Additionally, the controller reduced the settling time for frequency deviations in Area 1 by 9.9%, from 1.0574 s to 0.96191 s, and decreased the overshoot by 8.8%. In Area 2, the settling time was improved to 0.89209 s, with a reduction in overshoot by 4.8%. The controller also demonstrated superior tie-line power regulation, achieving immediate response with minimal overshoot.

Intelligent Control Algorithms for Enhanced Frequency Stability in Single and Interconnected Power Systems

Ensuring stable power system performance is crucial for reliable grid operation. This study assesses various Load Frequency Control (LFC) strategies, including conventional PID, pole placement, Genetic Algorithm (GA)-optimized PID, Particle Swarm Optimization (PSO)-optimized PID, and an Artificial Neural Network (ANN)-based controller, in single and interconnected power grids. The results reveal that GA- and PSO-optimized PID outperform conventional methods, offering minimal overshoot and fast settling times. Pole placement strikes a balance between response time and stability, while the ANN controller demonstrates adaptability and quick rise times but exhibits higher overshoot and longer settling times compared to the optimization techniques. Tie-line bias control aids in frequency stabilization but presents challenges with overshoot and prolonged settling times. Notably, PSO-optimized PID emerges as a promising solution, effectively mitigating overshoot and achieving rapid frequency recovery. This study underscores the importance of tailored control strategies for optimal LFC, which are essential for enhancing power system stability and efficiency. Future research should explore the potential of advanced techniques, such as deep learning and reinforcement learning, to further improve control performance.

All-microwave Lamb shift engineering for a fixed frequency multi-level superconducting qubit

It is known that the electromagnetic vacuum is responsible for the Lamb shift, which is a crucial phenomenon in quantum electrodynamics (QED). In circuit QED, the readout or bus resonators that are dispersively coupled can result in a significant Lamb shift of the qubit. However, previous approaches or proposals for controlling the Lamb shift in circuit QED demand overheads in circuit designs or non-perturbative renormalization of the system’s eigenbases, which can impose formidable limitations. In this work, we propose and demonstrate an all-microwave method for controlling the Lamb shift of fixed-frequency transmons. We employ the drive-induced longitudinal coupling between the transmon and resonator. By simply using an off-resonant monochromatic drive near the resonator frequency, we can control the net Lamb shift up to ±30 MHz and engineer it to zero with the drive-induced longitudinal coupling without facing the aforementioned challenges. Our work establishes an efficient way of engineering the fundamental effects of the electromagnetic vacuum and provides greater flexibility in non-parametric frequency controls of multilevel systems.

Modular high frequency resonant inverters in constant power mode

ABSTRACT In this paper, a modular resonant inverter is proposed for high frequency industrial heating applications. To maintain a uniform heating profile, the inverter is operated in constant power mode. A hybrid voltage and frequency control is proposed. Voltage control is used for active power tracking while frequency control is used to minimise circulating current due to reactive power and to achieve soft switching for the inverter switches. Analytical and test results are shown to verify the proposed approach.

Robust load frequency control in interval power systems via reduced-order generalized active disturbance rejection control

Abrupt load changes, structural discrepancies, and parametric uncertainties cause degraded performance of the high-order power systems. This situation creates a problematic endeavor while analyzing the performance of such high-order systems. Hence, a simple and efficient lower-order control methodology can be deployed to sort out the issues related to load frequency control (LFC) in such systems. This study resolves the LFC problem in parametric bounded power systems by developing a worst-case reduced-order generalized active disturbance rejection control (WRGADRC) method. The core concept of the proposed technique entails that a controller will perform well in nominal scenarios if it performs satisfactorily in worst-case conditions. Therefore, an interval system’s worst-case reduced-order model is first obtained from its different uncertain models; the reduced order controller is then designed using the GADRC technique. The proposed scheme is rigorously validated on various parametric bounded minimum and non-minimum phase single-area and multi-area power systems, instilling confidence in its ability to achieve minimum frequency deviation in multiple scenarios. The supremacy of the proposed scheme is highlighted over some well-established control techniques in the literature related to the LFC problem.

A Coordinated Emergency Frequency Control Strategy Based on Output Regulation Approach for an Isolated Industrial Microgrid

Constructing isolated industrial microgrids with wind power is beneficial for improving the economic benefits of high-energy-consuming production, such as the electrolytic aluminum industry. Due to the specialized structure of industrial microgrids and the unique characteristics of the electrolytic aluminum load (EAL), the common emergency frequency control methods do not apply to the specific operational requirements of isolated industrial microgrids. Since EALs have huge regulating capacities and fast responses, this paper proposes a coordinated emergency frequency control scheme to deal with power disturbances in isolated industrial microgrids. The coordinated frequency control model of an industrial microgrid considering demand-side participation is derived. With the help of output regulation theory, a practical, feasible coordinated frequency controller is designed by introducing frequency deviation and power disturbance as feedback control signals. The proposed control scheme achieves reserve power distribution between the generation and demand sides. The microgrid frequency can be maintained within a permitted range in the presence of large power imbalances. The simulation results conducted in an actual isolated industrial microgrid validate the effectiveness and dynamic performance of the proposed control scheme.

Adaptive disturbance compensation based finite time sliding mode frequency control considering AVR loop for low-inertia power system

Adaptive disturbance compensation based finite time sliding mode frequency control considering AVR loop for low-inertia power system