Frequency Stability Of Microgrid Research Articles

Enhanced frequency control of a hybrid microgrid using RANFIS for partially shaded photovoltaic systems under uncertainties

Nowadays environmental concerns and fossil fuel limitations, as well as economic benefits and technical issues such as reliability lead conventional distribution networks to smart microgrids, where the renewable energy resources are merged with the grids. Nevertheless, the systems face new challenges due to the intermittent nature and uncertainties in the distributed generations, which cause frequency fluctuations in the microgrid. The photovoltaic cells are the main part of the contemporary microgrids. Although the photovoltaic (PV) systems depend on solar irradiance, and temperature and are affected by the partial shading phenomenon they could contribute to improving the microgrid frequency stability with a proper control scheme. In this paper, the frequency control strategy is designed for a hybrid stand-alone microgrid, which is robust against load disturbances, variations in weather conditions, and uncertainties in the microgrid parameters. The proposed intelligent control scheme relies on the Recurrent Adaptive Neuro Fuzzy Inference System (RANFIS). The Whale Optimization Algorithm (WOA) is employed to optimize the RANFIS controller structure and generate the parameters of membership functions. In this multi-objective optimization, the objectives are settling time (ST), overshoot (Osh), and Integral Square Error (ISE). The simulation results verify the high robustness and performance of the proposed RANFIS controller, compared to other controllers, during various operational circumstances, as well as the sporadic behavior of renewable energy resources (RES) such as fluctuations in solar radiation and certain uncertainties in the microgrid parameters.

Frequency stabilization in microgrid with PV system based on maximum power extraction: A sliding mode approach

The article addresses the critical issue of frequency regulation in microgrids (MG) integrated with solar photovoltaic (PV) systems, which rely on maximum power point tracking (MPPT) using sliding mode control (SMC). The frequency stability of MGs is a significant concern due to the inherent variability of renewable energy sources, making frequency regulation challenging. This research proposes a dual-objective control strategy. Firstly, it ensures the solar PV system maximizes power extraction via a buck-boost converter controlled by SMC. Simultaneously, it maintains frequency regulation in the MG under load disturbances using SMC. The SMC technique guarantees precise convergence to the maximum power operating point and minimizes frequency deviations in the MG. The proposed solution demonstrates effective maximum power extraction under varying irradiance levels and reliable frequency regulation despite system parameter uncertainties and nonlinearities such as generation rate constraints (GRC) and governor deadband (GDB). Additionally, the SMC-based design achieves faster convergence compared to traditional proportional-integral (PI) controllers optimized using intelligent techniques. Stability analysis, performed using Bode and Nyquist plots, further confirms the robustness of the proposed system. The model was developed and tested in the MATLAB Simulink environment, showcasing its efficacy and reliability.

Study on frequency stability control strategies for microgrid based on hybrid renewable energy

The dynamic nature of renewable energy sources, such as wind and photovoltaic power generation, significantly impacts the frequency stability of microgrid systems due to their pronounced intermittency, inherent randomness, and limited output support. Despite ongoing research, a comprehensive understanding of control measures to enhance microgrid frequency stability remains lacking. This paper addresses this gap by summarizing domestic and global advancements in control strategies for microgrid frequency stability. Specifically, it examines the operating states of microgrids and associated frequency stability issues and expounds various methods for maintaining frequency stability. The paper proposes innovative control measures to enhance frequency stability, including improvements in master-slave control, droop control, phase-locked loop, and virtual synchronous generator (VSG) techniques, particularly during transitions between islanded and grid-connected modes. The findings demonstrate the effectiveness of these enhanced control strategies in maintaining frequency stability, and the paper concludes by suggesting future research directions in this field.

An overview of the current Advanced Techniques for Frequency Regulation in grid-connected and off-grid Microgrids.

The integration of renewable energy sources into the power system is an important step towards a sustainable energy transition. This transition could subsequently introduce substantial variability that critically impacts key operational parameters, such as frequency and voltage. This variability poses significant challenges, especially within microgrid configuration, both in grid-connected and isolated modes. Therefore, ensuring the stability of these parameters I paramount of their operational efficiency, reliability, and longevity. Despite these challenges, recent advancements in the field have led to the development of numerous advanced methodologies and control strategies designed to mitigate the impact of renewable sources on microgrid frequency stability. This paper provides a comprehensive overview of these state-of-the-art technologies and methodologies, including cutting-edge technologies such as adaptive load frequency control and Time-series prediction-based approaches. It offers insights into their application, effectiveness, and advantages in frequency control during microgrid operation, contributing to the ongoing discourse on integrating renewable energy sources with enhanced grid stability. Moreover, the discussion section provides insights and barriers impacting the implementation of these technologies in the current microgrid system and the power grid in general.

A New Fractional-Order Virtual Inertia Support Based on Battery Energy Storage for Enhancing Microgrid Frequency Stability

Microgrids have a low inertia constant due to the high penetration of renewable energy sources and the limited penetration of conventional generation with rotating mass. This makes microgrids more susceptible to frequency stability challenges. Virtual inertia control (VIC) is one of the most effective approaches to improving microgrid frequency stability. Therefore, this study proposes a new model to precisely mimic inertia power based on an energy storage system (ESS) that supports low-inertia power systems. The developed VIC model considers the effect of both the DC-DC converter and the DC-AC inverter on the power of the ESS used. This allows for more precise and accurate modeling of the VIC compared to conventional models. Moreover, this study proposes a fractional-order derivative control for the proposed VIC model to provide greater flexibility in dealing with different perturbations that occur in the system. Furthermore, the effectiveness of the proposed fractional-order VIC (FOVIC) is verified through an islanded microgrid that includes heterogeneous sources: a small thermal power plant, wind and solar power plants, and ESSs. The simulation results performed using MATLAB software indicate that the proposed VIC scheme provides fast stabilization times and slight deviations in system frequency compared to the conventional VIC schemes. The proposed VIC outperforms the conventional load frequency control by about 80% and the conventional VIC model by about 45% in tackling load/RESs fluctuations and system uncertainty. Additionally, the studied microgrid with the proposed FOVIC scheme is noticeably more stable and responds faster than that designed with integer-order derivative control. Thus, the proposed FOVIC scheme gives better performance for frequency stability of low-inertia power systems compared to conventional VIC schemes used in the literature.

Analysis of voltage and frequency stability of electric power system network with photovoltaic-based generation penetration

The operation of Distributed Generation (DG) with renewable energy sources integrated with distribution networks through microgrids poses challenges in terms of operation and control. If this is left unchecked, it can have a negative impact on system security and reliability in terms of voltage and frequency stability that will be disrupted because of frequent variations in power production and loading levels. This study investigates voltage and frequency stability in microgrids because of the penetration of DG with photovoltaic (PV) renewable energy sources in the power system using the Virtual Synchronous Generator (VSG) control technique. The VSG is a control alteration that enhances the capabilities of the power system so that voltage and frequency stability can be preserved and improved. The VSG control method with additional damping controllers that increase inertia with additional virtual inertia is used to simulate the speed of restoration of voltage and frequency stability of the power system due to the penetration of PV-based power plants. The simulation results show that at the time of penetration of PV-based power plants in the power system, there is a momentary instability in voltage and frequency, but it is immediately dampened by VSG control and can be quickly restored so that the stability of voltage and frequency is maintained.

Load Frequency Control of Marine Microgrid System Integrated with Renewable Energy Sources

In seaports, low-carbon energy systems and energy efficiency have become increasingly important as a result of the evolution of environmental and climate change challenges. In order to ensure the continued success of seaports, technological advancements must be introduced to a number of systems, such as seaport vehicles, harbor cranes, and the power sources of berthed ships. Harbor areas might need a microgrid to handle these aspects. Typically, microgrids that substitute conventional generator units with renewable energy sources (RES) suffer from system inertia problems, which adversely affect microgrid frequency stability. A load frequency controller (LFC) based on a novel modified proportional integral derivative with filter (MPIDF) is presented in this paper for enhancing the performance of marine microgrid system (MMS). The serval optimization algorithm (SOA), a recent bio-inspired optimization algorithm, is used to optimize the MPIDF controller coefficients. This controller is tested on a marine microgrid containing a number of RES such as wind turbine generators, sea wave energy, and solar generation. The efficacy of the proposed MPIDF controller is verified with respect to other controllers such as PIDF and PI. Similarly, the proposed meta-heuristic algorithm is validated as compared to other algorithms including particle swarm optimization (PSO), ant colony optimization (ACO), and jellyfish swarm optimization (JSO). This study also evaluates the robustness of the proposed controller to different perturbations in step load, changes in system parameters, and other parameter variations.

Enhancement of Microgrid Frequency Stability Based on the Combined Power-to-Hydrogen-to-Power Technology under High Penetration Renewable Units

Recently, with the large-scale integration of renewable energy sources into microgrid (μGs) power electronics, distributed energy systems have gained popularity. However, low inertia reduces system frequency stability and anti-disturbance capabilities, exposing power quality to intermittency and uncertainty in photovoltaics or wind turbines. To ensure system stability, the virtual inertia control (VIC) is presented. This paper proposes two solutions to overcome the low inertia problem and the surplus in capacities resulting from renewable energy sources. The first solution employs superconducting magnetic energy storage (SMES), which can be deemed as an efficient solution for damping the frequency oscillations. Therefore, in this work, SMES that is managed by a simple proportional-integral-derivative controller (PID) controller is utilized to overcome the low inertia. In the second solution, the hydrogen storage system is employed to maintain the stability of the microgrid by storing surplus power generated by renewable energy sources (RESs). Power-to-Power is a method of storing excess renewable energy as chemical energy in the form of hydrogen. Hydrogen can be utilized locally or delivered to a consumption node. The proposed μG operation demonstrates that the integration of the photovoltaics (PVs), wind turbines (WTs), diesel engine generator (DEG), electrolyzer, micro gas turbine (μGT), and SMES is adequate to fulfill the load requirements under transient operating circumstances such as a low and high PV output power as well as to adapt to sudden changes in the load demand. The effectiveness of the proposed schemes is confirmed using real irradiance data (Benban City, Egypt) using a MATLAB/SIMULINK environment.

Performance enhancement of parallel‐operated inverter‐based virtual synchronous generators supplying active load

AbstractInverter‐based virtual synchronous generators (VSGs) by introducing the virtual inertia enhance the microgrid frequency stability. The subject of this paper is regarding the stability analysis and enhancement of the study system comprising parallel‐operated VSGs feeding an active load. The active load with tightly closed‐loop control behaves such as constant power load resulting in stability issue. In the article, impacts of the dc‐side voltage control bandwidth of the active load and power level of active load on the system stability are examined. Then, an approach based on feedback linearising technique implemented on VSGs is presented for stabilising the system at higher levels of active load power. By employing the presented approach, the VSGs show reduced output impedance at the low and middle‐frequency ranges, and this in turn stabilises the system even at the rated level of the active load power and at higher control bandwidths of the active load dc‐side voltage control loop. Next, the linearised state‐space equations of converters and related controllers are transferred from local dq‐reference frames to a common dq‐reference frame, and then stability of the whole study system is analytically examined. At the end, time‐domain simulations and hardware‐in‐the‐loop experiments are given to verify the analytical results.

Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids

For the time being, renewable energy source (RES) penetration has significantly increased in power networks, particularly in microgrids. The overall system inertia is dramatically decreased by replacing traditional synchronous machines with RES. This negatively affects the microgrid dynamics under uncertainties, lowering the microgrid frequency stability, specifically in the islanded mode of operation. Therefore, this work aims to enhance the islanded microgrid frequency resilience using the virtual inertia frequency control concept. Additionally, optimal model predictive control (MPC) is employed in the virtual inertial control model. The optimum design of the MPC is attained using an optimization algorithm, the African Vultures Optimization Algorithm (AVOA). To certify the efficacy of the proposed controller, the AVOA-based MPC is compared with a conventional proportional–integral (PI) controller that is optimally designed using various optimization techniques. The actual data of RES is utilized, and a random load power pattern is applied to achieve practical simulation outcomes. Additionally, the microgrid paradigm contains battery energy storage (BES) units for enhancing the islanded microgrid transient stability. The simulation findings show the effectiveness of AVOA-based MPC in improving the microgrid frequency resilience. Furthermore, the results secure the role of BES in improving transient responses in the time domain simulations. The simulation outcomes are obtained using MATLAB software.

Review on Virtual Inertia Control Topologies for Improving Frequency Stability of Microgrid

Renewable energy sources (RESs), such as solar and wind power, offer new technologies for meeting the world's energy requirements. The distributed generator (DG) based on RESs has no rotational mass and damping effects compared to the traditional power system with synchronous generators (SG). However, the increasing penetration level of DG based on RESs causes low inertia, a dampening effect on the dynamic performance of the grid, and stability. A solution to improve the frequency stability of such a system is to provide virtual inertia by using virtual synchronous generators (VSG), which can be created by using short-term energy storage and a power inverter, and a suitable control mechanism. The VSG control mimics the dynamics of the rotation SG and enhances the power system's stability. This paper presents an overview of various topologies on virtual inertia, VSG concepts, control techniques, and VSG applications. Finally, the VSG challenges and future research will be discussed.

Multi-Area Microgrid Load-Frequency Control Using Combined Fractional and Integer Order Master–Slave Controller Considering Electric Vehicle Aggregator Effects

Because of the lack of upstream grid support and low inertia, independent microgrids are very susceptible to load variations and uncertainty in the generation of renewable energy sources. Disruption of microgrid frequency stability causes severe damage to various system equipment and frequency-sensitive loads. By taking into account the effects of electric vehicles (EVs), this paper introduces an innovative control strategy with a master-slave configuration for frequency control of interconnected microgrids. In the proposed configuration, an integer-order controller serves as the master, while a merely fractional-order integrator acts as the slave controller. The master and slave controllers are concurrently optimized by the JAYA intelligent algorithm to achieve robust effectiveness. Additionally, nonlinearities in the system are implemented, such as diesel generator operating limits, signal controllers, and sending/receiving time delays. To assess the effectiveness of the proposed control strategy in a two-area microgrid, six basic scenarios are investigated: sudden load changes, perturbations at the inputs of renewable energy-based units, parametric uncertainties, time-delay effects as a nonlinear factor, complicated working conditions, and EVs impacts. Moreover, the controller’s performance on a simple closed-loop system has been carried out in order to confirm the viability of its practical implementation, and a comparison of experimental and simulation findings has also been provided. Studies demonstrate the proposed controller’s robustness as well as its fast-response capability. Besides, this controller features a simple structure that allows extra design flexibility.

Frequency Stability Constrained Microgrid Scheduling Considering Seamless Islanding

The frequency stability of microgrids is of paramount importance due to their low inertia and high share of renewable energy sources. In this paper, a frequency stability-constrained microgrid scheduling (FSC-MS) model is developed based on a time-dependent discretized frequency response model considering seamless unintentional islanding events. The optimal dispatch of controllable units, as well as optimal upward and downward primary reserves, are determined with a minimum operating cost while ensuring frequency stability criteria are maintained in their safe ranges following an unintentional islanding event, such as rate of change of frequency (RoCoF) and frequency nadir and overshoot. The limitation of generators with respect to primary frequency response is formulated in the form of primary reserve capacity and primary ramp rate limits. A cost-based model is presented to describe the available primary reserve of synchronous generators. The proposed FSC-MS model is formulated as a mixed-integer linear programming (MILP) problem using Benders decomposition. Simulation results on a medium voltage microgrid test system demonstrate the effectiveness of the proposed model to meet the frequency stability constraints while minimizing the total operating cost.

A Packet Loss-Dependent Event-Triggered Cyber-Physical Cooperative Control Strategy for Islanded Microgrid.

In this article, a cyber-physical cooperative control strategy is proposed for islanded microgrid (MG), which divides the MG into cyber and physical layers. And the main designs in these two layers are two event-triggered mechanisms, where one mechanism is used to improve the voltage and frequency stability of MG considering the packet loss problem, the other is used to reduce the communication burden in the control process. More specifically, the control process of the first mechanism can be understood as we use these event-triggered mechanisms to complete the secondary control in the physical layer based on the information in the cyber layer. In this mechanism, the packet loss situation in one communication channel is divided into three categories: 1) to handle the case where the loss rate is small, an adaptive virtual leader-following consensus controller (AVLFCC) is proposed in the cyber layer; 2) to handle the case where the loss rate is large and the forecasted data can be used, a hybrid forecast supplement method (HFSM) is proposed in the physical layer; and 3) to handle the case where the loss rate is large and the forecasted data cannot be used, a path reconstruction method combined with a novel sliding-mode control (SMC) is proposed in the cyber layer. In the second mechanism, an event-triggered protocol is designed for the consensus controller to reduce the communication burden based on the designs in 1)-3). Finally, based on these designs in the two mechanisms, a novel secondary controller is designed. And the experimental results have confirmed the validity of the contributed strategy.

Coordinated Power Sharing in Islanding Microgrids for Parallel Distributed Generations

Optimal power sharing between parallel inverters and the demand load in microgrids is challenging and particularly critical for power grids in islanding operation. This paper introduces a novel control approach for managing parallel distributed power sources in the presence of variable load in islanding regime. The proposed scheme is based on the modified sliding mode control (MSMC) which is combined with the optimal Riccati control method to achieve convergence at the slip level with higher accuracy. The mathematical principles of the network equations are derived and its stability is obtained using the Lyapunov function. The MSMC simulation results are discussed in relation to the conventional droop method, while the laboratory evaluation was carried out to characterize its dynamic and static response. The results show that the proposed scheme control is able to manage the distributed power generation for static and dynamic load scenarios, and as such, guarantying microgrid frequency stability.

Microgrid Frequency Stability Enhancement Through Controlling Electric Vehicles Batteries Based on Fuzzy Logic Controller

The large-scale renewable energy contribution tends to expand vastly; this is due to the numerous benefits of the renewable energy, but renewable resources are intermittent and changeable in nature, which would affect the microgrid frequency stability. In this paper, a renewable and green microgrid is proposed aiming to emission power generation; the microgrid consists of biogas plant, biodiesel plant, photovoltaic system, wind turbines, battery energy storage system, load, and electric vehicles. The main contribution of this paper is providing the frequency stability enhancement of the proposed microgrid through controlling the electric vehicles batteries using fuzzy logic controller based on three main factors, the state of charge of the electric vehicles batteries, the microgrid frequency deviation signal, and the departure time of the vehicle that is set in advance by the owner. This work is discussing three scenarios, in the first one, the batteries of the electric vehicles are going to be charged directly once they get plugged into the charging point, in the second one, the electric vehicles batteries are going to be charged based on fuzzy charging control technique, in the third scenario, the vehicle to grid concept is applied, so the charging and discharging of the electric vehicles batteries are going to be controlled through fuzzy logic controller.

An IGAP-RBFNN-based secondary control strategy for islanded microgrid-cyber physical system considering data uploading interruption problem

At present, the traditional islanded microgrid is changing to a cyber-physical system. And the data in its cyber layer is often used to solve practical problems in the physical layer through sensors and communicators. But the use of communication data also brings a lot of problems. Among them, the upload interruption problem (i.e., communicator or sensor failure) will make a heavy impact on the system. To improve the voltage and frequency stability of microgrid through secondary control considering data uploading interruption, an improved growing and pruning-radial basis function neural network-based secondary control strategy is designed in this study. The main designs can be summarized as below: (1) When the communicator cannot receive data, a prediction compensation part is designed directly in the corresponding communicator, i.e., the predicted data is used to complete the follow-up works; (2) When the sensor cannot send data, a nonlinear cyber-physical vulnerability assessment part and a neighbor transmission part are designed. In this way, a neighbor sensor is selected to send the interrupted data for the follow-up control process; (3) Based on these designs above, a novel secondary control is designed for microgrid. Finally, the simulation results show the effectiveness of the proposed strategy.

Self-Adaptive Secondary Frequency Regulation Strategy of Micro-Grid With Multiple Virtual Synchronous Generators

With the penetration rate of distributed generator and distributed energy storage growing, the frequency stability of microgrid (MG) is severely affected. In this paper, a self-adaptive secondary frequency regulation (FR) strategy based on virtual synchronous generator (VSG) for a microgrid containing wind turbine, photovoltaic array, and electric vehicle (EV) cluster is proposed. First, modified VSG control is applied to renewable energy units and EV cluster, where nonerror frequency regulation is realized by introducing proportional-integral control into power-frequency controller of VSGs. Secondly, the FR reserve capacity of wind turbine, photovoltaic array, and EV are predicted in real time through their respective characteristics. Then, a self-adaptive adjustment strategy for secondary FR parameters of VSGs is designed to control the FR power of VSGs according to real-time predicted FR capacity. Finally, the coordinated FR strategy of VSGs and conventional unit is proposed considering the situation of insufficient FR capacity of VSGs. Through the analysis of simulation results, the reasonability and validity of proposed self-adaptive FR strategy for multiple VSGs have been verified.

Optimal Frequency Restoration of Inverter-Interfaced Microgrids via Distributed Energy Management

Abstract Despite the potential role of microgrids is well recognized in supporting the integration of renewable energy sources into the future power system, the impacts of intermittence renewable generation on the microgrid frequency stability is still being explored, and the related challenges remain to be addressed. In this paper, we focus on an islanded inverter-interfaced microgrid and present a consensus-based gradient algorithm for optimal frequency restoration via distributed energy management, preserving the standard hierarchical control architecture but merging the interdependent layers. The network-preserving model is applied to prevent loss of network topology and transient characteristics. Furthermore, not only distributed generators but also demand-side customers are considered to be actively participating in the proposed architecture. Convergence analysis implies that the closed-loop system is asymptotically stable, and its equilibrium will converge to the optimal solution of the associated energy management problem, which is consistent with the observation from the simulation study, including intermittent generation and load perturbation, carried out on a 6-bus test microgrid system. Therefore, the effectiveness of the proposed algorithm is verified.

Faster Islanding Detection of Microgrid Based on Multiscale Mathematical Morphology

Faster and reliable islanding detection of microgrid is necessary to protect the equipment and maintenance personnel. Voltage and frequency are two important parameters needs to be controlled in microgrid; Voltage and frequency stability of microgrid depends merely on main grid during grid connected mode and depends on individual controllers during islanding mode. This research proposes a time domain technique based on multi-scale mathematical morphology (MMM) for islanding detection. The proposed technique uses multiscale dilation-erosion difference filter (MDEDF) with peak value of the signal. The performance of the proposed technique is validated in IEEE-13bus system with different cases such as mismatch in real power, reactive power, load switching, motor switching; L-G fault .The results validate the accuracy and efficacy of the proposed technique and also compared with recently published work.