Showing papers on "Automatic frequency control published in 2023"

Solar and Wind Energy Integrated System Frequency Control: A Critical Review on Recent Developments

Abstract: A paradigm shift in power systems is observed due to the massive integration of renewable energy sources (RESs) as distributed generators. Mainly, solar photovoltaic (PV) panels and wind generators are extensively integrated with the modern power system to facilitate green efforts in the electrical energy sector. However, integrating these RESs destabilizes the frequency of the modern power system. Hitherto, the frequency control has not drawn sufficient attention due to the reduced inertia and complex control of power electronic converters associated with renewable energy conversion systems. Thus, this article provides a critical summary on the frequency control of solar PV and wind-integrated systems. The frequency control issues with advanced techniques, including inertia emulation, de-loading, and grid-forming, are summarized. Moreover, several cutting-edge devices in frequency control are outlined. The advantages and disadvantages of different approaches to control the frequency of high-level RESs integrated systems are well documented. The possible improvements of existing approaches are outlined. The key research areas are identified, and future research directions are mentioned so that cutting-edge technologies can be adopted, making the review article unique compared to the existing reviews. The article could be an excellent foundation and guidance for industry personnel, researchers, and academicians.

A New Intelligent Fractional-Order Load Frequency Control for Interconnected Modern Power Systems with Virtual Inertia Control

Abstract: Since modern power systems are susceptible to undesirable frequency oscillations caused by uncertainties in renewable energy sources (RESs) and loads, load frequency control (LFC) has a crucial role to get these systems’ frequency stability back. However, existing LFC techniques may not be sufficient to confront the key challenge arising from the low-inertia issue, which is due to the integration of high-penetration RESs. Therefore, to address this issue, this study proposes an optimized intelligent fractional-order integral (iFOI) controller for the LFC of a two-area interconnected modern power system with the implementation of virtual inertia control (VIC). Here, the proposed iFOI controller is optimally designed using an efficient metaheuristic optimization technique, called the gray wolf optimization (GWO) algorithm, which provides minimum values for system frequency deviations and tie-line power deviation. Moreover, the effectiveness of the proposed optimal iFOI controller is confirmed by contrasting its performance with other control techniques utilized in the literature, such as the integral controller and FOI controller, which are also designed in this study, under load/RES fluctuations. Compared to these control techniques from the literature for several scenarios, the simulation results produced by the MATLAB software have demonstrated the efficacy and resilience of the proposed optimal iFOI controller based on the GWO. Additionally, the effectiveness of the proposed controller design in regulating the frequency of interconnected modern power systems with the application of VIC is confirmed.

Automatic Generation Control with Virtual Synchronous Renewables

Abstract: As synchronous generators (SGs) are gradually displaced by renewable energy sources (RESs), the frequency stability of power systems deteriorates because RESs, represented by utility-scale solar and wind power sources, do not provide the inertial response, primary frequency response, secondary frequency response, and tertiary frequency regulation. As a result, the remaining SGs may not be sufficient to maintain the power balance and frequency stability. The concept and control strategies of virtual synchronous generators (VSGs) enable the inverter-based wind and solar power sources to emulate the outer characteristics of traditional SGs and participate in the active power and frequency control of power systems. This paper focuses on the automatic generation control (AGC) with virtual synchronous renewables (VSRs). First, the VSR strategy that enables the RESs to participate in AGC is introduced. Second, based on the interval representation of uncertainty, the output of RES is transformed into two portions, i.e., the dispatchable portion and the stochastic portion. In the dispatchable portion, the RESs can participate in AGC jointly with SGs. Accordingly, a security-constrained economic dispatch (SCED) model is built considering the RESs operating in VSR mode. Third, the solution strategy that employs the slack variables to acquire deterministic constraints is introduced. Finally, the proposed SCED model is solved based on the 6-bus and 39-bus systems. The results show that, compared with the maximum power point tracking (MPPT) mode, VSRs can participate in the active power and frequency control jointly with SGs, increase the maximum penetration level of RESs, and decrease the operating cost.

Frequency Restoration of Grid-Forming Inverters in Pulse Load and Plug-in Events

Abstract: This article presents a restoration technique using grid-forming inverters in an islanded microgrid during pulse load and plug-in events. In a microgrid powered by droop-controlled inverters, frequency is the variable that is accessible to all inverters for adjusting their power contributions. The problem is that the microgrid frequency deviates from its nominal value after a load change. The presented method enables the inverters to restore the frequency to the nominal value and regulate their bus voltage amplitudes. The frequency and voltage restorations are performed without communication while achieving the desired power-sharing between grid-forming inverters. The restoration is activated after detecting any active or reactive power changes. In this article, the dynamic model of an inverter equipped with enabled restoration paths is developed to verify the stability of the inverter controller under various conditions. The frequency and voltage restorations are examined during pulse load and plug-in events. This study is performed using a laboratory-scale islanded microgrid powered by two 208 V, 60 Hz, 5 kVA inverters.

Resilient Load Frequency Control of Islanded AC Microgrids Under Concurrent False Data Injection and Denial-of-Service Attacks

Abstract: Due to malicious cyber attacks, the frequency regulation of an islanded microgrid (MG) with load changes and wind/solar power fluctuations may not be guaranteed and the overall system may even be destabilized. The MG frequency control thus faces new challenges. In response to these challenges, this paper addresses a resilient load frequency control (LFC) problem for islanded AC-MGs under simultaneous false data injection (FDI) attacks and denial-of-service (DoS) attacks. Toward this aim, a new piecewise observer is constructed to provide the real-time estimates of the unavailable system state and the unknown FDI attack signal. Furthermore, a resilient $\mathcal {H}_{\infty }$ LFC scheme is developed to suppress the attack impacts. The novelty of this study lies in the development of an attack-parameter-dependent time-varying Lyapunov function approach to achieve stability analysis and resilient observer/controller design against concurrent FDI attacks and intermittent DoS attacks. Specifically, a tractable observer design criterion is first derived such that the estimation error is exponentially stable under a specified $\mathcal {H}_{\infty }$ performance level. Then a design criterion on the existence of the resilient controller is presented to guarantee the exponential stability of the resulting closed-loop system in the presence of the attacks, while preserving the anticipated $\mathcal {H}_{\infty }$ performance level. Finally, comparative simulation studies in various attack scenarios and different parameter settings are presented to verify the efficiency of the obtained theoretical results.

Cyberattack-Resilient Secondary Frequency Control Scheme for Stand-Alone Microgrids

Abstract: This article proposes a cyberattack-resilient secondary frequency control (SFC) scheme for a stand-alone microgrid (MG) system. The proposed scheme is based on a hybrid system that employs an unknown input observer for state estimation, cyberattack detection and reconstruction, and a Type-2 fuzzy logic system for minimization of frequency deviation that may be caused by cyberattacks on the MG system. A cyberattack on the MG’s frequency measurement disrupts the operation of the SFC system and eventually compromises the frequency stability of the MG. The proposed approach shows an accurate estimation of the MG states and maintains the frequency of the MG within operating limits during various cyberattack scenarios. The practicability of the proposed hybrid scheme is validated using the Speedgoat real-time digital system simulator.

Coordinated Participation of Electric Vehicles and Generating Units in Primary Frequency Control in the Presence of Renewables

Abstract: With the integration of renewables into the grid, the ability to perform primary frequency control (PFC) by the conventional generating units decreases in terms of frequency quality and stability. Also, the wear and tear of the generating units responsible for the PFC increases. In this article, a hierarchical PFC scheme is proposed that combines the coordinated actions of hydro-generation units and electric vehicles (EVs) such that the stability is maintained for large and small disturbances, while at the same time, frequency quality is improved and wear and tear of the generating units is reduced. The control parameters of the proposed scheme are tuned by solving the proposed optimization problem with proper objective functions and constraints that are representative of frequency stability and quality, wear and tear of the generating units, and comfort of EVs owners. The scheme is complemented by a new combination of frequency filters for EVs and generating units to more effectively reduce the effect of small frequency fluctuations on the wear and tear of generating units. Comparative simulation studies show the effectiveness of the proposed method in ameliorating the problems raised by the integration of renewables.

Virtual Inertia Response and Frequency Control Ancillary Services From Hydrogen Electrolyzers

Abstract: This article presents the modeling foundations to study the capabilities of hydrogen electrolyzers (HEs) to provide frequency control ancillary services (FCAS), including virtual inertia and primary and secondary frequency response. To do so, we propose a general, unified HE dynamic model for the electrolyzer stack circuit, power-electronics interface (PEI), and relevant converter-level control loops. The equivalent circuit of the stack is derived from its current transfer function, with poles and zero obtained from its step response characteristics (e.g., rise/settling time). The stack model also considers relevant physical nonlinearities and downstream hydrogen buffer/process operational constraints. The PEI control loops account for stack model parameters, hydrogen production operational constraints, stack temperature dynamics, and active power reference generation strategy for contingency and regulation frequency support services. Further, we propose a virtual synchronous machine (VSM) control approach to study the VSM HE capabilities to also provide virtual inertia response. We apply the modeling to both alkaline and proton exchange membrane (PEM) technologies, including design of appropriate control schemes. Finally, we assess the FCAS performance of alkaline and PEM HEs via dynamic simulation of the Australian south-east interconnection in a 50%-renewable scenario, also discussing comparison and cooperation with battery energy storage systems.

Reinforcement Learning for Optimal Primary Frequency Control: A Lyapunov Approach

Abstract: As more inverter-connected renewable resources are integrated into the grid, frequency stability may degrade because of the reduction in mechanical inertia and damping. A common approach to mitigate this degradation in performance is to use the power electronic interfaces of the renewable resources for primary frequency control. Since inverter-connected resources can realize almost arbitrary responses to frequency changes, they are not limited to reproducing the linear droop behaviors. To fully leverage their capabilities, reinforcement learning (RL) has emerged as a popular method to design nonlinear controllers to optimize a host of objective functions. Because both inverter-connected resources and synchronous generators would be a significant part of the grid in the near and intermediate future, the learned controller of the former should be stabilizing with respect to the nonlinear dynamics of the latter. To overcome this challenge, we explicitly engineer the structure of neural network-based controllers such that they guarantee system stability by construction, through the use of a Lyapunov function. A recurrent neural network architecture is used to efficiently train the controllers. The resulting controllers only use local information and outperform optimal linear droop as well as other state-of-the-art learning approaches.

A New Virtual Inductance Control Method for Frequency Stabilization of Grid-Forming Virtual Synchronous Generators

Abstract: Frequency stabilization is the premise of guaranteeing grid-friendly integration of virtual synchronous generator (VSG). Based on that premise, this article, focused on frequency stability, establishes the small signal model of grid-forming VSG system. At first, the mechanism of frequency oscillation occurring in system of active- and reactive-power coupling is analyzed by the defined feedback effect factor in this article. Besides, a new dynamic model is established for identifying dynamic interaction of voltage magnitudes and frequency by means of feedback effect. The analytical results of established models agree with that of eigenvalue analysis. Furthermore, a new virtual inductance control strategy is proposed to mitigate the unstable oscillation of frequency and powers, enhance damping performance, and improve stability margins. Unlike the conventional virtual inductance control, which is reliable on dual-loop control framework, the proposed virtual inductance control in this article is based on principle of energy conservation and can be applicable for the grid-forming inverter without inner dual-loop control structure. Finally, the proposed modeling as well as virtual inductance control method is experimentally verified.

A New Communication-Free Grid Frequency and AC Voltage Control of Hybrid LCC-VSC-HVDC Systems for Offshore Wind Farm Integration

Abstract: We propose frequency and voltage control method for a hybrid high-voltage direct current (HVDC) system for integrating an offshore wind farm into transmission networks. Conventionally, DC voltage level is maintained as constant regardless of the wind velocity and the grid frequency, so AC voltage fluctuates with active power variation in a hybrid HVDC system due to the innate reactive power absorption of inverter side line-commutated converter (LCC). However, in the proposed method, the DC voltage changes according to the wind velocity. Furthermore, DC voltage is simultaneously regulated to participate in frequency control in a communication-free manner. These two characteristics can be achieved by using five droop control methods proposed here. Additionally, by determining droop constants using the proposed determination methods, AC voltage can be maintained as constant during active power fluctuations. Therefore, using the proposed method, an offshore wind farm can be stably connected to mainland transmission networks and successfully used as frequency supporting resources, because voltage characteristics of the AC network are not destabilized. A small-signal state-space (SS) model of the target system was also developed to investigate stability of the proposed control. The utility of the proposed method is demonstrated by case studies using PSCAD and SS models.

Cascaded Fractional Model Predictive Controller for Load Frequency Control in Multiarea Hybrid Renewable Energy System with Uncertainties

Abstract: The rapid utilization of electricity has forced the stability of the power system for continuous operation. Due to difference in demand and generation, the frequency reference point changes that needs to be restored to its locus point for the stable operation of the power system. Therefore, a novel efficient control design is propounded to counter the phenomena of load frequency control. The designing of cascaded fractional model predictive controller coupled with fractional-order PID controller (CFMPC-FOPID) is designed for an efficient response of the power system under load disruption and system parameter variations. The controller is optimized by sooty tern optimization algorithm to identify the optimal parameters of the controller. The controller is tested under power mixing of renewable energy sources (i.e., PV and wind) and under varying load scenarios in multiarea hybrid power system. The proposed controller has effectively handled the frequency disruption under distinct load change by stabilizing it in 1.34 sec, 0.60 sec, and 0.41 sec for area-1 with an average time of 0.78 sec, and for area-2, the stabilizing time is 1.40 sec, 0.89 sec, and 0.56 sec with an average time of 0.95 sec, whereas the average time for MPC/PI, DSA-FOPID, GWO: PI-PD, and SCA: FOPI-FOPID is 7.67 sec, 4.68 sec, 1.77 sec, and 4.72 sec, respectively, for area-1 and 6.47 sec, 5.13 sec, 3.45 sec, and 5.02 sec, respectively, for area-2. The outcome result justifies the superiority of the studied technique.

Multi-Area Load Frequency Control in Power System Integrated With Wind Farms Using Fuzzy Generalized Predictive Control Method

Abstract: Frequency security is critical for the power systems’ stability and reliability. The integration of renewable energy resources brings new challenges to the frequency security of power systems. To provide a more robust control method for controlling the frequency and tie-line power flow of an interconnected power system integrated with wind farms (IPSWF), a load frequency control (LFC) controller of generalized predictive control (GPC) based on the Takagi-Sugeno (T–S) fuzzy model (fuzzy-GPC) is proposed in this paper. First, the T–S fuzzy model of the IPSWF is constructed. Then, the GPC is used to design the controller. Lastly, to validate the proposed scheme, an LFC strategy is established for a two-area interconnected power system integrated with a wind farm in power systems computer aided design (PSCAD). The control performance of proportional-integral, GPC, and fuzzy-GPC controller are compared under two faulty operating conditions. The simulation results show that the performance indicators and the dynamic behavior when the fuzzy-GPC controller is used are better than the performance when the PI controller and GPC controller are used. The proposed fuzzy-GPC used in the LFC of the IPSWF can regulate the frequency deviation and tie-line power deviation adaptively and achieve minimum frequency deviation and tie-line power deviation in a multi-area IPSWF.

Distributed Event-Triggered Hierarchical Control of PV Inverters to Provide Multi-Time Scale Frequency Response for AC Microgrid

Abstract: With the increasing penetration of inverter-interfaced photovoltaic (PV) systems in AC microgrids, the system inertia is increasingly deficient and the frequency response ancillary service provided by PV systems will be inevitable. In this paper, in order to make the PV systems provide multi-time scale frequency response, a novel distributed event-triggered hierarchical control (DEHC) of PV inverters is proposed, which includes a primary frequency response (PFR) control loop and a secondary frequency response (SFR) control loop. For the PFR, the PV inverters that operate in frequency regulation (FR) mode can arrest the frequency deviation in sub-seconds time-scale by an automatic deloading strategy, which is with low cost and easy to implement as no requirements for a storage system, irradiance sensors, and MPP estimators. For the SFR, the PV inverters that operate in FR mode can respond to the reference instruction assigned by a high-level AGC control center in seconds time-scale based on a novel distributed control strategy, which can converge within a fixed-time that independents to the initial conditions of the system. Furthermore, a novel event-triggered mechanism is designed to reduce the communication costs between PV inverters. Finally, case study results verify the effectiveness and improved performance of the proposed method.

Distributed Cooperative Control of Offshore Wind Farms Integrated via MTDC System for Fast Frequency Support

Abstract: This article proposes a distributed cooperative control (DCC) scheme of offshore wind farms integrated via the multiterminal direct current system for fast frequency support. The DCC scheme employs the consensus algorithm to share the frequency support burden among offshore wind turbines (WTs) suitably. The proposed DCC scheme can exploit the kinetic energy of all WTs adequately, while ensuring the security by employing the consensus state index and changing droop control coefficients adaptively. After the frequency support, the asymptotic recovery scheme is proposed at the leader WT for smooth rotor speed restorage, and other WTs will follow the leader to recover and reduce the second frequency drop. Besides, to realize the fast frequency support, the communication-free estimator is employed to estimate the onshore dc voltage using offshore local measured signals. Case studies are carried out on MATLAB and OPAL-RT real-time simulation platforms, respectively. Different control schemes are compared to elaborate the performance of the proposed DCC scheme considering the parameter uncertainty and noise disturbance.

Regional Load Frequency Control of BP-PI Wind Power Generation Based on Particle Swarm Optimization

Abstract: The large-scale integration of wind turbines (WTs) in renewable power generation induces power oscillations, leading to frequency aberration due to power unbalance. Hence, in this paper, a secondary frequency control strategy called load frequency control (LFC) for power systems with wind turbine participation is proposed. Specifically, a backpropagation (BP)-trained neural network-based PI control approach is adopted to optimize the conventional PI controller to achieve better adaptiveness. The proposed controller was developed to realize the timely adjustment of PI parameters during unforeseen changes in system operation, to ensure the mutual coordination among wind turbine control circuits. In the meantime, the improved particle swarm optimization (IPSO) algorithm is utilized to adjust the initial neuron weights of the neural network, which can effectively improve the convergence of optimization. The simulation results demonstrate that the proposed IPSO-BP-PI controller performed evidently better than the conventional PI controller in the case of random load disturbance, with a significant reduction to near 10 s in regulation time and a final stable error of less than 10−3 for load frequency. Additionally, compared with the conventional PI controller counterpart, the frequency adjustment rate of the IPSO-BP-PI controller is significantly improved. Furthermore, it achieves higher control accuracy and robustness, demonstrating better integration of wind energy into traditional power systems.

Enhancing the Conventional Controllers for Load Frequency Control of Isolated Microgrids Using Proposed Multi-Objective Formulation via Artificial Rabbits Optimization Algorithm

Abstract: Isolated microgrids (IMGs) power remote areas. However, IMG may lower the frequency stability and increase frequency excursions with low system inertia. Load frequency management ensures system stability. Thus, the paper proposes a novel multi-objective tuning strategy to improve IMG’s load frequency control (LFC) and take the microgrid controller’s control signals into account. Diesel engine generator, fuel cell, battery energy storage system, and renewable energy sources (RESs) like photovoltaic and wind systems make up the IMG. Conventional controllers such as proportional-integral (PI) and proportional integral derivative (PID) are classically tuned based on the standard error criteria as a traditional single-objective tuning approach. Due to the low inertia of the system and the stochastic nature of RES, they cannot act as required under different operating scenarios. Therefore, the PI and PID controllers are tuned using the proposed multi-objective-based tuning approach to reduce the frequency deviations. In addition, anti-windup is applied to the enhanced classic controllers to keep them distant from the nonlinear zone and beyond the source’s physical constraints. The proposed tuning process also considers the maximum practical generation rates for different sources. The recent Artificial Rabbits Optimization (ARO) algorithm is applied to simultaneously adjust the controller parameters for several controlled sources in IMG. Extensive simulations in MATLAB and Simulink confirm the effectiveness of the proposed approach to keep the system stable even when facing high levels of disturbances. In addition, accomplishing sensitivity analysis, severe ±25% changes to the system’s parameters guarantee that the proposed tuning strategy keeps the system stable.

Enhanced Grid Frequency and DC-Link Voltage Regulation in Hybrid AC/DC Microgrids Through Bidirectional Virtual Inertia Support

Abstract: AC mains frequency and dc-link voltage are two of the most important parameters that determine the stability of hybrid ac/dc microgrids. Frequency and voltage deviations beyond the acceptable threshold can lead to unscheduled load curtailments, cascading failures, or even power system blackouts. To enhance the stability of hybrid ac/dc microgrids, this article proposes a hybrid microgrid with bidirectional virtual inertia support, where virtual inertia is introduced to slow down dc voltage and ac frequency changes, thus enhancing the system stability. The proposed approach allows significant reductions in voltage and frequency fluctuations. With a standard hybrid microgrid configuration, inertia is delivered to both ac and dc subgrids via the change of bidirectional interlinking converter control. Specifically, the bidirectional interlinking converter uses the dc voltage of the dc grid and ac frequency of the ac grid as inputs through a proportional-integral (PI) controller and regulates the active power between two subgrids so that inertia and other supportive functions are implemented. To validate the merits of the proposed approach, experimental results are provided. According to experimental results, the frequency nadir, rate-of-change-of-frequency, and dc bus voltage deviation can be improved by the proposed strategy of bidirectional virtual inertia support in the hybrid ac/dc microgrid.

Adaptive Dual Droop Control of MTDC Integrated Offshore Wind Farms for Fast Frequency Support

Abstract: This paper proposes an adaptive dual droop control (ADDC) scheme, it can provide the disturbed onshore system with fast frequency support from both other undisturbed onshore systems, and voltage source converter-based multi-terminal direct current (VSC-MTDC) integrated offshore wind farms (OWFs). With conventional droop control at onshore converters, the DC voltage and power flow will change once frequency events occur, it will lead to frequency variations in other undisturbed systems. The proposed ADDC scheme firstly detects the disturbed and undisturbed systems, and then makes the undisturbed onshore system provide more frequency support power, while ensuring safe operation by settling the support power limitation and regulating the droop coefficients. Moreover, the offshore stations will estimate the onshore DC voltage as the control signal for fast frequency support. After that, the OWFs will recover their rotor speed with an asymptotic control scheme to reduce the second frequency drop. Case studies are carried out on 3-terminal and 5-terminal test systems, and the Opal-RT real-time simulation platform, respectively. Different control schemes are compared, and the parameter uncertainty and noise disturbance are considered to illustrate the performance and effectiveness of the proposed ADDC scheme.

Manta ray foraging optimization algorithm‐based load frequency control for hybrid modern power systems

Abstract: The regulation of the frequency and line power flow in interconnected power networks is considered to be a key aspect of load frequency control (LFC). This article broaches a modern power network composed of three interconnected control areas including traditional generation units taking into account non-linearities, also renewable energy sources (RESs) and energy storage (ES) units are involved in the power grid paradigm. Two forms of RESs are included in the analysis, which are photovoltaic (PV) and wind power plants. In addition, the study framework involves three types of ES units, which are batteries of plug-in electric vehicles (PEVs), flywheel energy storage system (FESS) and capacitive energy storage system (CESS). In this analysis, LFC is accomplished by the use of proportional-integral-derivative (PID) controllers in the system control loops. A recent optimization algorithm called Manta Ray Foraging optimization (MRFO) is employed to obtain the optimal gain configuration of the controllers. Real site measurements are imported to the RESs involved in the study aiming to examine the proposed control scheme under realistic conditions. Compared with other rival algorithms, the effectiveness of the MRFO-based PID controller is validated. Simulation results confirm the efficacy of the proposed control scheme. The findings also ensure the role of ES units in optimizing the time-domain responses. The main contributions of this paper are applying a new metaheuristic optimization algorithm to solve the LFC problem and introducing a new criteria for judging the system performance in compliance with the harmonic spectrum of the responses in the frequency domain. The results of the simulation are retrieved through a MATLAB model.