Virtual Inertia Control Research Articles

Cascaded Integral Minus Tilt Integral Derivative With Filter for Frequency Stabilization of V2G/G2V Enabled Hybrid Microgrid

ABSTRACTRenewable generation plays an important part in today's power system. With the inclusion of the inverter interfaced renewable energy sources (RESs) into a microgrid, the total system inertia decreases and it leads to increased frequency deviation in presence of a disturbance. This paper proposes a cascaded Integral Minus Tilt Integral Derivative with Filter (I–TDN)‐Proportional‐Integral (PI), [(I‐TDN)‐PI] controller for frequency stabilization of a hybrid microgrid in presence of electric vehicles (EV). The microgrid model includes reheated thermal power plant with high degree of non‐linear system such as inverter based RESs like photovoltaic and wind generation systems. A diesel engine generator is incorporated for load frequency control during perturbation in the system frequency. Virtual inertia controller (VIC) with inverter based energy storage system (ESS) is commonly used to improve system inertia and frequency stability of the microgrid. In addition to the ESS, this paper proposes inclusion of the EVs in this VIC. The optimal gains of the proposed cascaded I‐TDN‐PI controller are determined using Mountain Gazelle Optimizer (MGO), a modern metaheuristic optimization algorithm. Sensitivity of the proposed controller is investigated in presence of system nonlinearities, load perturbations, time delay, system parameter variation and RES power fluctuations. The simulation results justify the robustness of the proposed control structure for frequency stabilization of the microgrid.

Load frequency and virtual inertia control for power system using fuzzy self-tuned PID controller with high penetration of renewable energy

AbstractReliance on renewable energy is increasing, and generating units are being added to the network. Since renewable power fluctuates greatly, the frequency deviation of the grid becomes a crucial problem with access to renewable power generation. The fluctuation of the renewable power output of the system puts forward a higher demand for load frequency control of the power grid to increase the penetration of renewable power in the system. PID controller has proven its effectiveness for the LFC due to its simple structure and clear concept. In this article, the virtual synchronous generator is introduced and a fuzzy self-tuned PID controller is proposed for inertia control. The proposed controller is implemented in light of the significant integration of renewable energy and virtual inertia. The efficacy of the suggested controller is evaluated against the traditional PID controller for the Egyptian Power System as a case study under various load disturbance scenarios. The control technique is employed for variable loads with photovoltaic and wind turbine generation systems. Three instances of load changes are studied and the controller design is performed based on grey wolf optimizer in each case. The overshot and integral time absolute error are considered as comparison measures. The new contribution is applied to the proposed controller for the grid and virtual inertia. In the case of many load variations imposed, the disturbances of residential and industrial loads varied from 0.05, 0.01, 0.15, and 0.02 pu. The maximum overshoot is 0.005 for the proposed controller and 0.0078 for the classic PID controller. The integral time absolute error is 0.06429 for the proposed controller and 0.11481 for the classic PID controller. The results demonstrate the efficacy of the proposed controller for inertia control with high penetration of renewable energy. The results show that the proposed fuzzy self-tuned PID controller has an overshot less than the classical PID controller by 25% and integral time absolute error by 45%. These results show that the use of the proposed fuzzy self-tune controller for the grid and inertia gave a better performance in terms of the overshot value and the integral time absolute error.

Transient energy transfer of wind-photovoltaic-storage grid-connected system under virtual synchronous coupling

In the new power system, the efficient capture of transient energy by a virtual synchronous generator (VSG) will be the key to improve the grid-connected stability of wind-photovoltaic-storage. This paper first analyzes the virtual synchronous coupling relationship between the VSG and the synchronous generator (SG), and constructs the dynamic model of grid-connected system. Secondly, based on the Hamiltonian theory, the transient energy transfer characteristics between the VSG and the SG under the virtual synchronous coupling are analyzed, and the conditions for the VSG to completely capture the transient energy is obtained, and a virtual inertia control strategy based on the efficient transfer of transient energy is proposed. Finally, a 9-node simulation system is built to verify that the proposed control strategy can significantly improve the performance of VSG in suppressing power oscillations and frequency changes.

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.

Stability Improvement of Hybrid Renewable Energy Systems by Using Virtual Inertia Controller Based on Optimized FOPID with Harris Hawk Optimization

Stability Improvement of Hybrid Renewable Energy Systems by Using Virtual Inertia Controller Based on Optimized FOPID with Harris Hawk Optimization

Simulation of PSDF (Photovoltaic, Storage, Direct Current and Flexibility) Energy System for Rural Buildings

The PSDF (photovoltaic, storage, direct current, and flexibility) energy system represents an innovative approach aimed at achieving carbon neutrality. This study focused on rural buildings and utilized Modelica to develop a dynamic simulation model of the PSDF system. The research introduced a framework for direct current distribution microgrid systems with flexible regulatory mechanisms, employing a virtual inertia control strategy to provide stable adjustments for flexible operations and support integration with local grids. Case simulation results indicated that the system equipped with a water tank saved 3.15 kWh compared to the system without a water tank, resulting in an energy savings rate of 22.14%. Compared to traditional photovoltaic systems, the PSDF system significantly enhanced energy management flexibility and system reliability through the integration of thermal storage and battery management. This research made significant contributions to the fields of renewable energy and building energy systems by offering a scalable and practical solution suitable for rural contexts.

Towards non-virtual inertia control of renewable energy for frequency regulation: Modeling, analysis and new control scheme

Currently, when renewable generation participates in frequency regulation, the traditional control method is to emulate synchronous generators through virtual inertia control. However, virtual inertia has a time delay, so essentially, it is a fast power response. Meanwhile, virtual inertia control is likely to be affected by frequency fluctuation since it responds to the derivative of frequency. Hence, it’s worth exploring non-virtual inertia control for renewable energy when participating in frequency regulation. For this reason, a novel two-segment droop control scheme for renewable energy frequency regulation is proposed in this research. Firstly, the extended system frequency regulation (SFR) model, which contains virtual inertia with time delay, is built and analytically solved by order decrement based on the Routh approximation method. Afterwards, according to the analytical solution, time delay affects the frequency response of renewable energy. It can also be analytically proved that the non-virtual inertia control, e.g., sole droop control, could replace virtual inertia under the same frequency deviation. Still, more energy may be needed for frequency regulation. Furthermore, a novel two-segment droop control is presented, and to analytically prove its ability to replace virtual inertia, the impulse function balancing principle and the integration by parts algorithm were adopted to address the initial conditions of the differential equation. Based on the analytical expression, it can be analytically proved that a lower frequency deviation can be obtained under the same frequency regulation energy. Accordingly, a parameter-setting method for two-segment droop control was proposed. Finally, the effectiveness of the proposed method is verified by using a two-area system frequency response model, and the results reveal that it can be used to replace virtual inertia and has better performance.

Advanced frequency control schemes and technical analysis for large-scale PEM and Alkaline electrolyzer plants in renewable-based power systems

Integrating electrolyzers into power systems can significantly contribute to sustainable energy via the generation of green hydrogen while also enhancing frequency stability through effective regulation of the electrolyzers’ operating power. This study gives a comprehensive analysis of large-scale electrolyzer plants when providing frequency support to power systems. First, the authors present a model predictive control (MPC)-based secondary frequency controller, combined with a droop controller as the primary frequency controller and a virtual inertia controller. Additionally, the study introduces a universal system frequency response (U-SFR) modeling approach that enables high accuracy, low computation burden, and reduced initial parameters as a testbed. Finally, an in-depth analysis is conducted, focusing on different technical aspects of large-scale electrolyzer plants when providing frequency support services. Case studies integrating PEM and Alkaline electrolyzers into the modified IEEE 39-bus system with over 50% wind power penetration are conducted. It is found that the proposed U-SFR model achieves high accuracy with lower computational time compared to detailed physical models. Additionally, model predictive controllers improve frequency quality more effectively than PID and PID-FLC methods. PEM electrolyzers are found to be more efficient in providing grid frequency support than alkaline electrolyzers due to their technical characteristics. Finally, smaller hydrogen tanks may frequently breach storage constraints, negatively impacting the system’s frequency response capability.

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

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

Deep Entropy-Learning based virtual inertia control for VRFB regulation considering Phase-Locked loop dynamics

The virtual inertia control (VIC) technique is often adopted as a prominent mechanism to address the inertia deficiency of modern integrated power systems with high penetration of sustainable energy units. In such control mechanisms, a phase-locked loop (PLL) is required to estimate the grid frequency. However, utilization of such frequency measurement platforms is accompanied by large frequency fluctuations due to its inherent dynamics. In particular, this paper proposes an adaptive integral recursive backstepping (I-RBSC) based on virtual inertia for the regulation of vanadium redox flow battery (VRFB) in stand-alone Micro-Grids (SMGs). Unlike previous works that neglected the effect of frequency measurement devices, this work investigates the effect of PLL dynamics in virtual inertia control. The I-RBSC controller is designed by an entropy-driven actor-critic neural networks (NNs) to adaptively adjust the tunable coefficients during its interaction with the SMG. By training the ability of deep NNs, the entropy is maximized to regulate the system output. The VRFB unit can be discharged up to 90% which can quickly respond to the randomness of loads and sustainable energy units. The transient outcomes of SMG reveal the feasibility of I-RBSC (designed by entropy learning) to address the challenges of low inertia and PLL dynamics. The real-data of wind turbine and solar radiation are utilized to simulate the SMG in a more realistic framework from a systematic point of view. The comprehensive analysis under typical scenarios confirms the supremacy of the suggested VIC controller over prevalent state-of-the-art virtual inertia controllers including conventional VIC, fuzzy logic, backstepping, and model-predictive control (MPC).

Virtual inertia control of distribution grids under automobile charging and discharging load uncertainty

Abstract Automobiles with unstable charging and discharging loads usually have unstable power, frequency, and other parameters of the distribution network. Therefore, a virtual inertia control strategy is proposed to enhance the distribution network’s stability and improve the grid’s voltage quality. This method can enhance the inertia control capability of the grid by incorporating the sag coefficient and SOC control, which in turn achieves the purpose of improving the grid’s reliability. The results show that changing the sag coefficient can enhance the voltage stability to reduce the impact of the battery while incorporating the SOC inertia coefficient control, the distribution grid operation will be more stable, and the power quality will be higher. The new method enhances the stability of voltage load to a certain extent and lays the foundation for the subsequent virtual inertia control technology.

Comparison between FLL and PLL in frequency estimation to supply distributed virtual inertia

To connect renewable energy sources (e.g. solar or wind) on the grid, an inverter or electronic converter is used. However, a traditional inverter has no inertia in the face of frequency changes. Unlike the inertia of the rotor of a synchronous generator. Frequency variations are a product of the imbalance between the energy generated and the grid loads. If the frequency is too far from its nominal value or if the rate of change of frequency (RoCoF) is high, it can affect the synchronism of the generators that feed the grid. Therefore, power cuts are made in sectors on the grid, thus preventing instability from spreading to other sectors on the grid, which translates into large economic losses. Solutions such as inverters with virtual inertia (or emulated inertia) are a good alternative due to their structural simplicity and low cost, compared to other solutions such as synchronous condensers, for example. For the virtual inertial control strategy, the grid frequency needs to be measured. This article compares the use of a phase-locked loop (PLL) or a frequency-locked loop (FLL) for frequency estimation and its effect on inertia emulation. The proposed control designs are validated through simulations.

Optimized coordinated control method with virtual inertia based on fractional impedance model for charging stations

Due to the EV (Electric Vehicles) charging stations are characterized by weak damping and low inertia, the EV with a high degree of uncertainty can easily have an impact on the stability of the charging station system. Therefore, this paper proposes an optimization control method to improve the system inertia effect based on the fractional order impedance model of the charging station. This paper presents a study on establishing a fractional impedance model for charging stations, using the deviation between theoretical impedance spectra and actual measurements as a criterion. The goal is to enhance system inertia and optimize the parameters of the fractional-order controller to improve the supporting capacity of the charging station system and enhance its dynamic response. Initially, considering the fractional characteristics of the EV load, a fractional impedance model of the charging station is established. The analysis demonstrates that the fractional-order capacitor provides inertia to the system, enhancing its inertia support capability. In addition, a virtual inertia control strategy based on fractional-order PID (FOPID) is designed. Finally, an improved particle swarm optimization algorithm is utilized to optimize the control parameters. Through experimental verification under different operating conditions, it has been demonstrated that the fractional-order control strategy can achieve a dynamic response time of approximately 0.025s and limit the voltage deviation within 5%. Furthermore, the rotational inertia can rapidly increase to the maximum value satisfying the objective function within 0.05s. The results indicate that this control method effectively suppresses the DC voltage and power oscillations in the distribution grid.

Capacitor virtual inertia control and equivalent inertia analysis for a grid-forming wind generation system

A grid-forming wind generation system exhibits exceptional grid frequency support abilities. The DC capacitor of the grid-forming wind generation system, which is characterized by rapid response and high sensitivity to minor disturbances, can provide short-term inertia support for the power system. This paper proposes the capacitor virtual inertia control for the grid-forming wind generation system, coupling the DC capacitor voltage with the power system frequency, which enables the DC capacitor to participate in the system frequency response process and reduces the rate of change of the system frequency during the disturbance. To analyze the inertia of the wind power generation system, this paper establishes an equivalent Philips–Heffron model for the grid-forming wind generation system and uses the equivalent inertia constant to quantify the inertia of the wind power generation system. The effectiveness of the proposed control strategy and the reasonableness of the inertia assessment method are verified through simulations in the single-turbine system and the IEEE four-machine two-area system.

Mechanism Analysis of the Effect of the Equivalent Proportional Coefficient of Inertia Control for a Doubly Fed Wind Generator on Frequency Stability in Extreme Environments

With the large-scale access of a doubly fed wind generator (DFWG) with inertia adjustment capability to the polar microgrid, the frequency stability characteristics of the polar microgrid become more complicated. To enhance DWFG frequency stability and ensure the safe and reliable operation of polar microgrids, a DFWG connected to a two-region interconnected polar microgrid is used as the research background for this paper. Firstly, the equivalent model of two regional inertia centers is derived, and the effect of DFWG virtual inertia on the rotor motion equation of the regional inertia center is analyzed when a DFWG is directly connected to the polar microgrid. Then, from the point of view of the transient energy of the system, the influence of the equivalent proportional coefficient of virtual inertia control of the DFWG in two regions on the transient energy during the acceleration and deceleration of the system is studied when the swing direction of the system power angle is different, and the influence mechanism of the swing direction on the frequency stability is further investigated. Finally, the maximum frequency offset is proposed to evaluate the frequency stability of the system, and the two-region system simulation model is built into the PSASP 7.4.1 simulation software to verify the correctness of the proposed theory.

Advanced Primary Frequency Regulation Optimization in Wind Storage Systems with DC Integration Using Double Deep Q-Networks

With the gradual increase in wind power installation capacity, the proportion of traditional synchronous generators driven by fossil fuel is gradually declining. Due to the fact that wind turbines are connected to the grid through power electronic converters, which decouple rotor speeds from the system frequency and reduce system inertia levels, inadequate inertia levels can pose a threat to frequency stability when disturbances occur. To address this issue, this paper proposes a frequency regulation optimization strategy for the direct current (DC) transmission of a wind storage system. This strategy incorporates virtual inertia control and virtual droop control to adjust wind power output based on frequency deviation and rate of change. Fuzzy logic control is employed for energy storage, adaptively adjusting active power based on frequency deviation and the rate of change. Additionally, under the context of multi-DC transmission in renewable energy systems, an optimization strategy for proportion and integration (PI) parameters of the frequency limit controller (FLC) is proposed. Considering frequency deviation and DC regulation power simultaneously, the double deep Q-network (DDQN) algorithm is adopted in the simulation model to attain the optimal parameters of FLC. Simulation results conducted using MATLAB/Simulink 2022a indicate that this strategy increases the lowest frequency by 0.28 Hz and decreases the response time by 1.04 s compared with the non-optimized strategy.

Virtual Inertia Control for Power Electronics-Integrated Power Systems: Challenges and Prospects

In modern power systems, conventional energy production units are being replaced by clean and environmentally friendly renewable energy resources (RESs). Integrating RESs into power systems presents numerous challenges, notably the need for enhanced grid stability and reliability. RES-dominated power systems fail to meet sufficient demand due to insufficient inertia responses. To address this issue, various virtual inertia emulation techniques are proposed to bolster power system stability amidst the increased integration of renewable energy sources into the grid. This review article explores state-of-the-art virtual inertia support strategies tailored to accommodate the increased penetration of RESs. Beginning with an overview of this study, it explores the existing virtual inertia techniques and investigates the various methodologies, including control algorithms, parameters, configurations, key contributions, sources, controllers, and simulation platforms. The promising virtual inertia control strategies are categorised based on the techniques used in their control algorithms and their applications. Furthermore, this review explains evolving research trends and identifies promising avenues for future investigations. Emphasis is placed on addressing key challenges such as dynamic response characteristics, scalability, and interoperability with conventional grid assets. The initial database search reveals 1529 publications. Finally, 106 articles were selected for this study, adding 6 articles manually for the review analysis. By synthesising current knowledge and outlining prospective research directions, this review aims to facilitate the current state of research paths concerning virtual inertia control techniques, along with the categorisation and analysis of these approaches, and showcases a comprehensive understanding of the research domain, which is essential for the sustainable integration of renewable energy into modern power systems via power electronic interface.

Optimization of battery/ultra‐capacitor hybrid energy storage system for frequency response support in low‐inertia microgrid

AbstractModern power system networks are under statutory obligations to integrate renewable energy sources (RES). The primary reason is to meet ever‐increasing energy demand and also to curtail environmental pollution by greenhouse gases. However, the higher penetration of RES has the tendency of reducing inertia of overall power system network. Consequently, frequency stability is affected and deviates beyond allowable permissible limits leading to power blackouts, load shedding, and even total system failure. To address the issues associated with reduced inertia, an optimal control of hybrid energy storage system (HESS) has been proposed. HESS is basically a combination of battery and ultracapacitor, where ultracapacitor addresses rapidly varying power component by mimicking inertia while the battery compensates long‐term power variations. Thus, the HESS is effectively controlled to compensate the loss of inertia by regulating its energy flow. For the purpose of improved efficiency and better power management of the HESS, an improvised particle swarm optimization (MPSO)‐based virtual inertia control design has been proposed. The proposed MPSO is utilized to tune the gains of bidirectional dc–dc converter in such a way that improves frequency nadir with faster response to transient disturbances. This proposed method is simulated in MATLAB and its merits are validated in real time using hardware in loop. On analysing of the results, it can be observed that frequency nadir is improved by 48.96% with significant reduction in rate of change of frequency in comparison to conventional particle swarm optimization.

Learning-Based Virtual Inertia Control of an Islanded Microgrid With High Participation of Renewable Energy Resources

Learning-Based Virtual Inertia Control of an Islanded Microgrid With High Participation of Renewable Energy Resources

An Adaptive Virtual Inertial Control Strategy for DC Distribution Networks

The DC distribution network is a low-inertia system, which is very sensitive to load disturbance, system failure, and other factors. By adding virtual capacitance to the converter connected to the power supply, the virtual inertia of the DC power grid can be improved. Firstly, this paper proposes a strategy for adjusting virtual capacitance based on the voltage change rate to achieve adaptive control of virtual inertia, which enables the converter to quickly absorb or release energy during power fluctuations. Secondly, the adaptivity of the strategy is improved and the main control parameters in the proposed control method are qualitatively analyzed. Finally, the four-terminal photovoltaic storage DC distribution network system is constructed. Through Simulink, the adaptive virtual inertia control is incorporated on the battery side to simulate and validate the effectiveness of the strategy and the rationality of parameter analysis. The results show that this method can provide flexible and adjustable inertia support for DC grids and improve the voltage stability of DC grids.