Fast Frequency Response Research Articles

Dynamic interactions in large scale photovoltaic power plants with frequency and voltage support

The increasing penetration of Large-Scale Photovoltaic Power Plants in the power system is raising the concern of potential stability issues due to dynamic interactions of power electronics components. In particular, Power Plant Controllers are starting to provide a fast dynamic response for specific services, such as fast frequency response, which could trigger unexpected unstable interactions with the PV inverters or other grid components. Also, an eventual reduction of synchronous generation in the grid could lead to a power system with high penetration of power electronics, which presents unexplored stability problems. This paper presents an interaction and stability study of a Photovoltaic Power Plant connected to the grid. This study is based on a small-signal analysis employing eigenvalues and participation factors to identify potential unstable modes. A linear model of the Photovoltaic Power Plant is implemented to apply a small-signal analysis. This linear model is validated with the equivalent non-linear model based on time-domain simulations in Matlab Simulink.

Improvement of primary frequency modulation test method of renewable energy stations in North-west Power Grid

In recent years, with the rapid development of renewable energy power generation, the operation and structure of the power grid are becoming more and more complex, the difficulty of power balance and frequency regulation is increasing. North-west Power Grid took the lead in carrying out renewable energy frequency modulation function transformation and performance test technology research in 2016, and developed a primary frequency modulation function test method for renewable energy stations in the North-west transmission-end large power grid. In this paper, by calculating and analyzing the response data of some renewable energy stations when Yindong HVDC is blocked, combined with the fast frequency response performance test results of a renewable energy station, this paper analyzes the shortcomings of the current fast frequency response function test methods of the renewable energy stations of the North-west Power Grid, and put forward suggestions for improvement to provide technical support for the promotion of the primary frequency modulation function of renewable energy stations in the northwest transmission power grid.

Challenges and Mitigation Measures in Power Systems with High Share of Renewables—The Australian Experience

Australia is one of the leading countries in energy transition, and its largest power system is intended to securely operate with up to 75% of variable renewable generation by 2025. High-inertia synchronous condensers, battery energy storage systems, and grid-forming converters are some of the technologies supporting this transformation while facilitating the secure operation of the grid. Synchronous condensers have enabled 2500 MW of solar and wind generation in the state of South Australia, reaching minimum operational demands of ≈100 MW. Grid-scale battery energy storage systems have demonstrated not only market benefits by cutting costs to consumers but also essential grid services during contingencies. Fast frequency response, synthetic inertia, and high fault currents are some of the grid-supporting capabilities provided by new developments that strengthen the grid while facilitating the integration of new renewable energy hubs. This manuscript provides a comprehensive overview, based on the Australian experience, of how power systems are overcoming expected challenges while continuing to integrate secure, low cost, and clean energy.

Frequency Response From Aggregated V2G Chargers With Uncertain EV Connections

Fast frequency response (FR) is highly effective at securing frequency dynamics after a generator outage in low inertia systems. Electric vehicles (EVs) equipped with vehicle to grid (V2G) chargers could offer an abundant source of FR in future. However, the uncertainty associated with V2G aggregation, driven by the uncertain number of connected EVs at the time of an outage, has not been fully understood and prevents its participation in the existing service provision framework. To tackle this limitation, this paper, for the first time, incorporates such uncertainty into system frequency dynamics, from which probabilistic nadir and steady state frequency requirements are enforced via a derived moment-based distributionally-robust chance constraint. Field data from over 25,000 chargers is analysed to provide realistic parameters and connection forecasts to examine the value of FR from V2G chargers in annual operation of the GB 2030 system. The case study demonstrates that uncertainty of EV connections can be effectively managed through the proposed scheduling framework, which results in annual savings of <inline-formula><tex-math notation="LaTeX">$&amp;pound;$</tex-math></inline-formula>6,300 or 37.4&#x00A0;tCO<inline-formula><tex-math notation="LaTeX">$_{2}$</tex-math></inline-formula> per charger. The sensitivity of this value to renewable capacity and FR delays is explored, with V2G capacity shown to be a third as valuable as the same grid battery capacity.

Autonomous Dual Active Power-frequency Control in Power System with Small-scale Photovoltaic Power Generation

Active power control of the photovoltaic (PV) power generation system is a promising solution to regulate frequency fluctuation in a power system with high penetration of renewable energy. This paper proposes an autonomous active power control of a small-scale PV system for supporting the inertial response of synchronous generators and power-frequency control. In the proposed control approach, an effective grid frequency regulation scheme is realized using slow- and fast-frequency responses. A low-pass filter based frequency measurement is used for slow-frequency response, while direct frequency measurement is used for fast-frequency response. The designed dual droop characteristic-based control is shaped to achieve a smooth transition between slow- and fast-frequency responses. The performance of the proposed control approach is demonstrated for serious disturbance scenarios, i. e., considerable power-load imbalance and generation trip. In the power-load imbalance test scenario, the proposed control approach works properly within the normal frequency deviation region even when the frequency deviation exceeds that region occasionally. In the generation trip test, the frequency deviation is mitigated quickly, and the employed droop control is smoothly transferred from the slow- to fast-frequency responses.

Comparison and Influence of Flywheels Energy Storage System Control Schemes in the Frequency Regulation of Isolated Power Systems

Increased renewable energy penetration in isolated power systems has a clear impact on the quality of system frequency. The flywheel energy storage system (FESS) is a mature technology with a fast frequency response, high power density, high round-trip efficiency, low maintenance, no depth of discharge effects, and resilience to withstand continuous charge-discharge cycling without lifetime degradation. These FESS properties allows to effectively address the frequency quality problem. This study analyzes the contribution of a FESS to reducing frequency deviations in an isolated system that combines a diesel plant, wind farm, and pump-storage hydropower plant based on the El Hierro power system. This study approaches this analysis by comparing six different FESS governor control schemes (GCSs). Of these six GCSs, the nonlinear proportional variant (NLP <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\mathrm {V}}$ </tex-math></inline-formula> ) is a singular contribution based on the NLP scheme previously developed by the same researchers. Different governor’s parameter settings for the FESS GCSs were also compared, obtained from the proposed tuning methodology that considers the renewable energy generation distribution, frequency impact, and lifetime degradation of diesel, hydraulic groups, and flywheels. The GCSs were compared in terms of average frequency deviation, Zenith and Nadir frequency difference, wear and tear of diesel electromechanical elements and Pelton turbine nozzles, flywheels cycles per hour, and FESS average state of charge. The results show that including a FESS plant considerably improves frequency regulation. The tuning criteria and GCSs have a clear influence on the results, with NLP and NLP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</sub> GCSs offering relevant improvements in frequency deviations.

A Unified Power-Setpoint Tracking Algorithm for Utility-Scale PV Systems With Power Reserves and Fast Frequency Response Capabilities

This paper presents a fast power-setpoint tracking algorithm to enable utility-scale photovoltaic (PV) systems to provide high quality grid services such as power reserves and fast frequency response. The algorithm unites maximum power-point estimation (MPPE) with flexible power-point tracking (FPPT) control to improve the performance of both algorithms, achieving fast and accurate PV power-setpoint tracking even under rapid solar irradiance changes. The MPPE is developed using a real-time, nonlinear curve-fitting approach based on the Levenberg-Marquardt algorithm. A modified adaptive FPPT based on the Perturb and Observe technique is developed for the power-setpoint tracking. By using MPPE to decouple the impact of irradiance changes on the measured PV output power, we develop a fast convergence technique for tracking power-reference changes within three FPPT iterations. Furthermore, to limit the maximum output power ripple, a new design is introduced for the steady-state voltage step size of the adaptive FPPT. The proposed algorithm is implemented on a testbed consisting of a 500 kVA three-phase, single-stage, utility-scale PV system on the OPAL-RT eMEGASIM platform. Results show that the proposed method outperforms the state-of-the-art.

Requirements for Interdependent Reserve Types Providing Primary Frequency Control

As renewable energy penetration increases and system inertia levels drop, primary frequency control is becoming a critical concern in relatively small interconnections such as the Electric Reliability Council of Texas (ERCOT). To address this problem ERCOT is implementing a number of market rule changes including the introduction of a new Fast Frequency Response (FFR) reserve type to the electricity market. This FFR reserve type aims to help the traditional Primary Frequency Response (PFR) reserve type in arresting frequency decline in the event of a large generator outage. This paper derives reserve requirements to ensure sufficient reserve to arrest frequency decline before reaching the critical frequency threshold while coupling PFR reserve, FFR reserve, and system inertia. The general reserve requirement places limits on the amount of PFR reserve that can be provided by each unit based on its ramping capabilities. Two such limits are derived from first principles and another is proposed that is capable of accommodating the equivalency ratio introduced in previous work. These PFR reserve limits also provide first principles insight into equivalency ratios, which have only been studied empirically in the past. High-level insights are provided on a large Texas test case.

High-Fidelity Model of Stand-Alone Diesel Electric Generator With Hybrid Turbine-Governor Configuration for Microgrid Studies

Diesel electric generators are an inherent part of remote hybrid microgrids found in remote regions of the world that provide primary frequency response (PFR) to restore system frequency during load or generation changes. However, with inverter-based resources (IBR) integration into microgrids, the IBR control provides a fast frequency response (FFR) to restore the system frequency. Hence, supplementing PFR with FFR requires a sophisticated control system and a high fidelity diesel electric generator model to design these control systems. In this work, a high-fidelity model of a diesel electric generator is developed. Its parameters are tuned using a surrogate optimization algorithm by emulating its response during a load change to a 400 kVA Caterpillar C-15 diesel generator, similar to those found in remote microgrids. The diesel electric generator model consists of a synchronous machine, DC4B excitation with V/Hz limiter, and a proposed modified IEEE GGOV1 engine-governor model (GGOV1D). The performance of the GGOV1D is compared with simple, Woodward DEGOV, and a standard IEEE GGOV1 engine-governor model. Results show that error in the diesel electric generator's response to load changes using the GGOV1D model is lower with an improved frequency response during the arresting and rebound period than the other engine-governor models.

Adaptive Synthetic Inertia Control Framework for Distributed Energy Resources in Low-Inertia Microgrid

Bulk integration of Distributed Energy Resources (DERs) into the power grids reduces the system&#x2019;s inherent inertial response.The reduced inertial response causes a high Rate-of-Change-of-Frequency (RoCoF) and poses formidable operational challenges for the grid frequency stability. Interconnections around the world comprehend the role and value of the Synthetic Inertia Control (SIC), which is considered as a subset of the Fast Frequency Response (FFR) and as one of the potential solutions to arrest high RoCoF in low-inertia power systems. This paper proposes an intelligent SIC model with an adaptive Fuzzy Logic Controller for a low-inertia microgrid. The proposed Fuzzy-SIC (FSIC) design optimizes the DER output to fulfill the FFR requirements of the system for various operating conditions. The particle swarm optimization algorithm is applied to tune the SIC unit parameters along with the secondary Proportional&#x2013;Integral&#x2013;Derivative control. The proposed approach is examined in a control area with distinct degrees of DERs and load. Case studies and numerical results demonstrate about 87% improvement in RoCoF and frequency nadir in comparison to the system without a synthetic inertia emulation. Furthermore, the robustness of the proposed approach is evaluated using various case studies and a time-domain analysis is conducted to demonstrate the impact of incremental SIC parameters on the system parameters.

Highly sensitive and fast response strain sensor based on evanescently coupled micro/nanofibers

Flexible strain sensors play an important role in electronic skins, wearable medical devices, and advanced robots. Herein, a highly sensitive and fast response optical strain sensor with two evanescently coupled optical micro/nanofibers (MNFs) embedded in a polydimethylsiloxane (PDMS) film is proposed. The strain sensor exhibits a gauge factor as high as 64.5 for strain ≤ 0.5% and a strain resolution of 0.0012% which corresponds to elongation of 120 nm on a 1 cm long device. As a proof-of-concept, highly sensitive fingertip pulse measurement is realized. The properties of fast temporal frequency response up to 30 kHz and a pressure sensitivity of 102 kPa⁻¹ enable the sensor for sound detection. Such versatile sensor could be of great use in physiological signal monitoring, voice recognition and micro-displacement detection.

Hybrid-Mode PFM Control for LLC Resonant Converter

This article presents a new hybrid-mode pulse-frequency-modulation control method for an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> resonant converter. In the proposed control method, the primary-side resonant current sensing signal of the current-mode control variable is combined with a ramp signal of the voltage-mode control variable to determine an operating frequency. Then, the proposed control method mainly modulates the ramp signal in accordance with the output load condition. Therefore, the control-to-output voltage transfer function has both the current <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</b> mode control and voltage-mode control characteristics that provide fast frequency response and stable output voltage regulation in a light-load condition. In addition, since the ramp signal is also used for slope compensation of the resonant current sensing signal, an external slope compensation circuit is not required. A small-signal ac modeling and loop analysis of the proposed method verify the advantages. The proposed control method is implemented into a field programmable gate array (FPGA) board with an analog front-end board. An experiment is carried out on a 288-W <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LLC</i> resonant converter. The result shows that the proposed control method provides fast dynamic performance and stable operation under a light-load condition without an additional slope compensation circuit.

Cloud-Edge Interoperability for Demand Response-Enabled Fast Frequency Response Service Provision

The massive penetration of Renewables into the energy mix and the existence of IoT-enabled Distributed Energy Resources (DERs) in the emerging smart grid, while a blessing towards de-carbonization, increase considerably the operations and planning functions of the grid. Cloud processing of IoT/DER data facilitates the deployment of various Demand-Response (DR) and other DER asset scenarios, the organization of distribution grids into Local Energy Markets (LEM) and the efficient computation of load forecasting and power flow. Cloud computing enables a plethora of service provisions to the grid including frequency response. The decentralized nature of DERs at the edge of the distribution grid requires nodal approaches for the computation of power grid congestion constraints and power flow solutions. We present here a cloud-edge continuum approach, anchored on the new generation of communications infrastructure, which expedites the computation time of the load and DER forecasting and optimal power flow calculations. The proposed approach allows the LEM operator to respond to Fast Frequency Response service procurement signals issued by the balancing authority requiring even sub-second latency for service settlement. The proposed cloud-edge architecture has been tested on the IEEE European Low Voltage Benchmark model and provides scalability and elasticity for various DR/DER configurations.

Power Control Strategy for Solar Photovoltaic Systems for Fast Frequency Response Ancillary Service

Power Control Strategy for Solar Photovoltaic Systems for Fast Frequency Response Ancillary Service

Cooperation of large-scale wind farm and battery storage in frequency control: An optimal Fuzzy-logic based controller

Grid integration of renewables and battery energy storage systems and its consequent synchronous machines retirement may drive power systems into low-inertia conditions with high risk of frequency instability which is associated with lack of sufficient inertia and primary frequency response previously supplied by synchronous machines. Therefore, there is a need to figure out alternative solutions to compensate the lack of system frequency dynamic supports in future renewable-dominated power systems. In this context, this paper aims to highlight wind farm capabilities, particularly doubly-fed induction generator (DFIG) and permanent magnet synchronous generator (PMSG), in system primary frequency control, similar to conventional synchronous units, while also investigates the synergy between the wind unit cooperation with large-scale battery storages. First, a novel dynamic model is presented which takes into account large-scale wind farms, as well as utility-scale batteries, equipped with frequency-sensitive active power reference scheme so as to control the system frequency violations following contingencies. The proposed frequency control model also includes power-electronics interface model, its associated control loops, and a novel Fuzzy-logic based controller. The proposed Fuzzy-logic based controller along with a wash-out filter allows combined wind-battery system to estimate the system active power mismatch, emerged from a contingency/trip, to determine the consequent frequency variations, and therefore to deliver fast frequency response in a robust and reliable way to arrest the mentioned frequency distortions. The proposed Fuzzy-based controller is then designed via optimizing its model parameters, including the membership function parameters, thereby improving its efficiency in frequency control provision as well as active power control. The optimization process is performed via a widely used artificial bee colony (ABC) algorithm while a multi-objective function is considered. The proposed frequency control model is then evaluated in the 14-generation low-inertia Australian test system with 30% wind penetration. This work tries to provide a deep insight on how to utilize wind farms for frequency support and how to wind-battery frequency response may positively interact with nearby converter-based resources, i.e., photovoltaic units. The proposed Fuzzy-based coordination approach for large-scale wind-battery units can be a potential solution to deal with frequency stability problems in future power systems with low-inertia conditions including multiple nearby converter-based resources.

Uncertainty quantification for aerodynamic pressure probes, using adaptive quasi-Monte Carlo

In the present study, an adaptive randomized Quasi Monte Carlo methodology is presented, combining Stein’s two-stage adaptive scheme and Low Discrepancy Sobol sequences. The method is used for the propagation and calculation of uncertainties related to aerodynamic pneumatic probes and high frequency fast response aerodynamic probes (FRAP) in the subsonic flow regime, . The use of the proposed methodology allows the fast and accurate, in a probabilistic sense, calculation of uncertainties, ensuring that the total number of Monte Carlo (MC) trials is kept low based on the desired numerical accuracy. Thus, the method is well-suited for aerodynamic pressure probes, where multiple points need to be evaluated in their calibration space. Complete and detailed measurement models are presented for both a pneumatic probe and FRAP. The models are segregated in sub-problems that allow the evaluation and inspection of intermediate steps of MC in a transparent manner, also enabling the calculation of the relative contributions of the elemental uncertainties on the measured quantities. The adaptive scheme is implemented with a block-to-block evaluation, which accelerates the calculation of statistical parameters. Various, commonly-used sampling techniques for MC simulation and different adaptive MC schemes are compared, using both theoretical toy distributions and actual examples from aerodynamic probes’ measurement models. The robustness of Stein’s two-stage scheme is demonstrated even in cases when significant deviation from normality is observed in the underlying distribution of the output of the MC. With regards to FRAP, two issues related to piezo-resistive sensors are addressed, namely temperature dependent pressure hysteresis and temporal sensor drift, and their uncertainties are accounted for in the measurement model. These effects are the most dominant factors, affecting all flow quantities’ uncertainties, with significance that varies mainly with M and operating temperature. This work highlights the need to construct accurate and detailed measurement models for aerodynamic probes, that otherwise will result in significant underestimation (routinely in excess of 50) of the final uncertainties.

Power reserve control of solar photovoltaic system for improved frequency response of a stand-alone power system

ABSTRACT The growing share of photovoltaic (PV) installations in power systems, with the consequent reduction in system inertia, has necessitated considering PV systems to participate in grid ancillary services such as fast frequency response (FFR). Power reserve control (PRC) of PV systems, to create the required reserve power, needs the PV systems to be operated at a point below the maximum-power point. This paper presents a novel power-command tracking algorithm for PV systems to realize PRC operation. Based on the single-diode model (SDM) and single measurement sample, the proposed PRC algorithm provides a straightforward estimation of the maximum-power point (MPP) quantities without requiring an irradiance sensor. A self-adaptive voltage-tracking method (inner control) is proposed which directly translates a reference power command into an equivalent voltage command for the interfacing DC-DC converter even under changing irradiance levels. Additionally, the strategy unifies the PRC mode and MPP mode into a single control algorithm, allowing an optimal transition between the two modes of operation. The proposed PRC scheme is implemented on a solar-diesel hybrid power system to provide frequency regulation. An appropriate power reference for the inner controller is generated via an optimally-tuned inertial and damping controller (ID-controller) with constraints on the power command. Various aspects of modeling and control are addressed, and simulation experiments are conducted to illustrate the effectiveness of the suggested approach. The results show that, with the proposed PRC, frequency deviation and rate-of-change of frequency (RoCoF) are reduced by 86% and 59%, respectively compared to MPP-mode operation.

Photoinduced Multistable Resonance Frequency Switching of Phase Change Microstring at Room Temperature

AbstractVanadium dioxide (VO2), a promising phase change material, exhibits insulator to metal transition at 68 °C, manifests a drastic change in multiple physical properties, such as electrical resistance, mechanical modulus, lattice parameters, etc. From technological perspective, the transition temperature can be reduced by precise strain engineering. Here a noncontact, all‐optical, and highly energy efficient platform is demonstrated to study macroscopic dynamics related to the localized structural rearrangements at room temperature. A thin layer (≈25 nm) of polycrystalline VO2 deposited on a platinum coated silicon nitride microstring resonator shows a fast controlled mechanical resonance frequency response upon variations in optical power and wavelength. It is shown multiple stable frequencies of the resonator, designated as different equilibrium states, can be activated at different optical powers (≈200 µW) and wavelength, i.e., 450, 520, and 635 nm. The observed multiple resonance states of the microstring are explained because of the generation of stress due to the interplay between thermal expansion and the temperature‐induced phase change of VO2. It is believed this change in frequency states under the controlled external optical excitation can have potential applications in ultrafast optical switching, intelligent temperature sensors, and neuromorphic devices operated at room temperature.

Zeolitic imidazolate frameworks derived Co-Zn-nanoporous carbon-sulfide material for supercapacitors

To synthesize porous carbon-based electrodes for supercapacitors, a bimetallic strategy is used from zeolitic imidazolate frameworks (ZIFs), i.e., ZIF-67 and ZIF-8 are used for derived carbon material. The synthesized electrode comprises two metals, nitrogen and nanoporous carbon with sulfur, which have precisely controlled specific surface area, porosity, and graphitization degree. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and galvanostatic charge-discharge (GCD) methods are used to explore the electrochemical behavior of the prepared materials using three-electrode configurations in an electrolyte solution (2 M KOH). By combining the consequences of sulfur and bimetal, the prepared specimens performed exceptionally well. The modified final ZIF-derived bimetallic sulfide exhibited an enhanced specific capacitance value of 815 F/g at a scan rate of 2 mV/s. According to the findings, the modified composite has very little resistance to charge transfer, a fast frequency response time, and an improved specific capacitance value. The composite's coulombic efficiency remains at 83.9% after 5000 cycles. The final composite's outstanding performance is due to its nitrogen-doped nanoporous carbon nature/structure and bimetallic derived sulfide composition.

A Combined RMS Simulation Model for DFIG-Based and FSC-Based Wind Turbines and Its Initialization

Reconstructable dynamic simulation models of modern variable-speed wind turbines (WTs), which are integrable into any simulation software, are crucial to the scientists investigating the contribution of WTs to counteracting the current power system stability issues. The structural similarity between a doubly fed induction-generator-based (DFIG-based) WT model and a full-scale-convertor-based (FSC-based) WT model using induction generator offers the possibility of integrating them into a combined modular model with little effort and the same used parameter set. This article presents a combined root mean square (RMS) WT model, which contains a DFIG-based WT and a FSC-based WT using induction generator. The model is designed based on fundamental machine and converter equations and can be applied for classical network stability analyses. Furthermore, analogous well-performing initialization procedures for both DFIG-based and FSC-based WT models are also introduced. As an example, to demonstrate the performance of the WT model in frequency stability studies, the model is extended with a droop-based fast frequency response (FFR) controller and is implemented in a MATLAB-based RMS simulation tool. The results of the case studies confirmed a solid functionality of initialization procedures. Furthermore, they illustrate feasible and comparable general behavior of both WT models as well as their plausible responses in the event of a frequency drop in a 220 kV test system.