Frequency Regulation In Microgrids Research Articles

Fractional order slide mode droop control for simultaneous voltage and frequency regulation of AC microgrid

AbstractThis research proposes the application of fractional‐order sliding mode control (FOSMC) at the primary controller level to improve the stability of an islanded microgrid by adjusting its voltage and frequency. The control strategies used in the microgrid are performed in two levels (primary and secondary) in the islanded mode. Practically, most previous studies have worked to improve the primary controller. Droop control is one of the most commonly used methods at the primary level and is adopted in this study as well. The sliding mode control (SMC) strategy is normally used to control linear equations. Thus, the non‐linear microgrid equations were transformed into some linear ones using the input‐output feedback linearization technique. Further, a fractional sliding surface was acquainted. The sliding surface and FOSMC were designed to reject system uncertainties and organize the voltage and frequency. Design parameters were chosen using the Lyapunov stability theorem. The validation of the proposed method using Simulink‐MATLAB confirms its effectiveness in enhancing level power sharing, regulating frequency, and maintaining voltage stability across the system.

Real-Time Co-Simulation Implementation for Voltage and Frequency Regulation in Standalone AC Microgrid with Communication Network Performance Analysis across Traffic Variations

Effective communication networks are crucial for ensuring reliable and stable operation and control in smart microgrids (MGs). This paper proposes a comprehensive analysis of the interdependence between power and communication networks in the real-time control of a standalone AC microgrid to address this vital need. Thus, the role of communication network design is emphasized in facilitating an effective centralized secondary control to regulate the voltage and frequency of an MG. Consequently, voltage and frequency deviations from the droop-based primary control should be eliminated. This study employs a real-time co-simulation testbed setup that integrates OPAL-RT and network simulator (ns-3), supporting a rigorous evaluation of the interplay between the communication networks and control within the MG. Experiments have been conducted to demonstrate the effectiveness of the designed communication infrastructure in seamlessly enabling real-time data exchange among the primary and secondary control layers. Testing scenarios have been implemented, encompassing low-traffic patterns with minimal load variations and high traffic characterized by more frequent and severe load changes. The experimental results highlight the significant impact of traffic variations on communication network performance. Despite the increase in traffic, the effectiveness and reliability of the designed communication network have been validated, underscoring the vital role of communication in ensuring the resilient and stable operation of cyber–physical standalone AC microgrids.

Synergistic frequency regulation in microgrids: pioneering a controller for seamless integration of wave energy conversion systems

Synergistic frequency regulation in microgrids: pioneering a controller for seamless integration of wave energy conversion systems

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.

Brain Emotional Learning-Based Intelligent Controller for Frequency Regulation of Uncertain Islanded Microgrid Considering Renewable Energy Sources

Brain Emotional Learning-Based Intelligent Controller for Frequency Regulation of Uncertain Islanded Microgrid Considering Renewable Energy Sources

Coordinated Control of Proton Exchange Membrane Electrolyzers and Alkaline Electrolyzers for a Wind-to-Hydrogen Islanded Microgrid

In recent years, the development of hydrogen energy has been widely discussed, particularly in combination with renewable energy sources, enabling the production of “green” hydrogen. With the significant increase in wind power generation, a promising solution for obtaining green hydrogen is the development of wind-to-hydrogen (W2H) systems. However, the high proportion of wind power and electrolyzers in a large-scale W2H system will bring about the problem of renewable energy consumption and frequency stability reduction. This paper analyzes the operational characteristics and economic feasibility of mainstream electrolyzers, leading to the proposal of a coordinated hydrogen production scheme involving both a proton exchange membrane (PEM) electrolyzer and an alkaline (ALK) electrolyzer. Subsequently, a coordinated control based on Model Predictive Control (MPC) is proposed for system frequency regulation in a large-scale W2H islanded microgrid. Finally, simulation results demonstrate that the system under PEM/ALK electrolyzers coordinated control not only flexibly accommodates fluctuating wind power but also maintains frequency stability in the face of large disturbances. Compared with the traditional system with all ALK electrolyzers, the frequency deviation of this system is reduced by 25%, the regulation time is shortened by 80%, and the demand for an energy storage system (ESS) is reduced. The result validates the effectiveness of MPC and the benefits of the PEM/ALK electrolyzers coordinated hydrogen production scheme.

Teaching learning optimization-based sliding mode control for frequency regulation in microgrid

Teaching learning optimization-based sliding mode control for frequency regulation in microgrid

Distributed robust control of frequency and active power-sharing ratio regulation in islanded AC microgrids

Distributed robust control of frequency and active power-sharing ratio regulation in islanded AC microgrids

Standardized Communication-Based Diverse Structure Model Predictive Controller With Demand Response for Frequency Regulation in Microgrids

Standardized Communication-Based Diverse Structure Model Predictive Controller With Demand Response for Frequency Regulation in Microgrids

Soft variable structure fractional sliding-mode control for frequency regulation in renewable shipboard microgrids

In light of the reliable operation of renewable shipboard microgrids, this paper implements a fractional-order theory for flexible modeling for an accurate study of shipboard microgrids. Then, it introduces a novel variable structure control strategy based on a fractional-order reduced chatter nonlinear sliding mode. This strategy incorporates a time delay estimation and an optimization routine for parameter adjustments, aiming to achieve nearly time-optimal control performance and faster frequency accommodation. The proposed method exploits the benefits of fractional order modeling, reduced chatter sliding mode, and variable structure approaches. While the adapted reduced chatter strategy may decrease convergence speed, the variable structure strategy compensates for this by accelerating settling speed. These features, along with continuous, soft, and limited control signals, make the proposed method suitable for the challenging conditions of low inertia, high dynamics, uncertainty, and a noisy environment in nonlinear renewable shipboard microgrids. The Lyapunov stability proof and simulation results demonstrate the proposed method's fast, high accuracy, and reliable performance. Furthermore, the validation process, which involves comparisons with conventional sliding-mode strategies, fractional-order proportional-integral-derivative controllers, and experimental test results using the Speedgoat real-time target machine in conjunction with Simulink real-time, serves to further establish the superiority of the proposed approach.

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.

Optimal Tuning of Virtual Inertia Control for Frequency Regulation of Microgrid

Optimal Tuning of Virtual Inertia Control for Frequency Regulation of Microgrid

Frequency regulation in microgrid using sliding mode control with event-triggering mechanism

Frequency regulation in microgrid using sliding mode control with event-triggering mechanism

Frequency Regulation of Microgrid with Renewable Sources Using Intelligent Adaptive Virtual Inertia Control Approach

Frequency control of small inertia microgrids (MGs) with amalgamation of renewable energies like wind and solar is a difficult job. Virtual inertia control (VIC) scheme is the concept of enhancing the MGs inertia employing storage elements. In the present study, an optimized fuzzy adaptive virtual inertia control strategy has been proposed for adaptive allocation of virtual inertia constant. To tune the suggested controllers, an improved golden jackal optimization (i-GJO) is projected in which priority is given to the better jackal’s during the search process, and also sine cosine adopted scaling factor is used to modify the jackal’s position throughout search process. The effectiveness of i-GJO method is evaluated by comparing the results with golden jackal optimization (GJO) and other similar recently proposed optimization algorithms. Then, proportional-integral-derivative controllers are tuned in VIC environment with fixed virtual inertia constant (KVT ) using proposed i-GJO technique, and the superiority of i-GJO over genetic algorithm, particle swarm optimization, and GJO is demonstrated. Finally, fuzzy based controller with constant KVT as well as fuzzy adaptive KVT has been designed using the proposed i-GJO technique. The sensitivity of the controller is also examined under irregular load changes and various rates of RES amalgamation.

Model-free frequency regulation in islanded microgrids: An event-triggered adaptive dynamic programming approach

This paper is concerned with frequency regulation in islanded microgrids via an event-triggered adaptive dynamic programming method. Comparatively to the existing works, we relax the typical limitations on the system, namely, exactly known models, constant load impedances, and single operation mode. The adopted frequency regulation scheme can reach frequency synchronization within the acceptable bounds in the presence of the model uncertainties, operation mode switching, and time-varying loads with no need for any prior information on the system parameters. By employing an event-triggered scheme, the secondary controller is updated only at the aperiodic triggering instants which contributes to less transmission cost. Besides, the use of measurements can help the adaptive weights to be adjusted online in the approximation process, which allows the proposed controller to adapt to the disturbances in real time. Finally, tests including the islanding process and load variation are performed in MATLAB/SimPowerSystem to show the effectiveness of the proposed method.

Provisional Microgrid Frequency Regulation by Brain Emotional Learning Based Intelligent Controller and Implementation Through FPGA

With the advancement of technology and human movement towards evolution, intelligent control methods are becoming more important. One of the areas of progress is related to the development of new frameworks for electricity generation and distribution systems, and the microgrid structure with economic capabilities is one of the frameworks. Accordingly, this paper presents a new practical method for controlling the frequency of microgrids and is able to cover the following issues at the same time. 1- It considers the nonlinear model of provisional microgrid which has a hybrid structure (AC and DC) in addition to renewable energy sources. 2- Introduces a method for microgrid frequency control under different operational conditions that performs based on the brain emotional learning. 3- Ensures the operation and applicability of the control method for the provisional microgrid through implementation of FPGA for the first time 4- Confirms the robustness of the proposed method under extreme load changes. So, in the simulation scenarios, the effects of wind turbine and solar energy are considered and under the influence of various changes in load and system uncertainties, the robustness and efficiency of the proposed method are well demonstrated.

Hybrid cyber-attack compensation of sustainable microgrid using active disturbance rejection control strategy

A modified active disturbance rejection control (ADRC) strategy for the frequency regulation of sustainable microgrid against hybrid cyber-attacks is proposed in this paper. The proposed technique mitigates the effect of attacks which in turn regulates the frequency of microgrid. The sustainable microgrid consists of solar and wind as renewable energy sources, energy storage systems (ESSs) like battery ESS and flywheel ESS, and controllable sources of energy like fuel cell and diesel generator. The cyber-attacks such as false data injection, denial-of-service and time delay attack are considered for designing the proposed ADRC technique. The robustness of the microgrid system with the proposed controller is investigated by varying generation and load, stochastic nature of attacks, parametric uncertainties and generation rate constraint and governor dead band nonlinearities. Further, the stability analysis of the microgrid with proposed ADRC is investigated under the aforementioned cyber-attacks using the small gain theorem.

A Potent Fractional-Order Controller for Interconnected Multi-Source Microgrids

Frequency deviations and the capability to cope with demand are two of the main problems in isolated or interconnected microgrids, especially with the increase in the penetration level of renewable energy sources. Those two problems call for new improved controllers and methods able to suppress frequency deviations while keeping a balance between supply and demand. This study focuses on the implementation of a filtered fractional-order PDF controller in series with a one plus fractional-order PI controller (FOPDF-(1+FOPI)) for the frequency regulation of three-area multi-source interconnected microgrids. The proposed controller is optimized via the coot optimization algorithm. The proposed microgrids incorporate various sustainable units, renewable energy sources and a hybrid energy storage system in each area. The microgrids consist solely of sustainable and renewable sources and aim to provide possible microgrid configurations for 100% sustainable microgrids, which could be farms or small communities. The proposed controller is compared with the PIDF, integer-order PDF-(1+PI), and FOTDF-(1+TI) controllers in various scenarios. The first scenario involved evaluating the proposed controller in an isolated microgrid, where it achieved the best ITAE value, outperforming the second best by 29.5%. The second scenario considered three-area interconnected microgrids without RES penetration. The results revealed that the FOPDF-(1+FOPI) controller reduced the settling time in area one by 79.13% and 52.26% compared to that of the PIDF and FOTDF-(1+TI) controllers. Next, RES penetration was introduced into each microgrid in the form of steps or varied changes. Subsequently, performance evaluation was conducted in the presence of a communication time delay and noise in the control channels. Finally, a robustness assessment was conducted for the proposed controller in the interconnected microgrids with respect to parameter uncertainties. The simulations showed a maximum deviation in the settling time and maximum overshoot in area 1 of 66.6% and 38.74%, respectively

An Optimized PI Damping Control for Frequency Regulation in Low-Inertia Microgrid

An Optimized PI Damping Control for Frequency Regulation in Low-Inertia Microgrid

Fuzzy model predictive control for frequency regulation of temporary microgrids during load restoration

AbstractTemporary microgrids containing a high proportion of distributed renewable generations can offer great benefits during the recovery stage after large‐scale power system blackout, by picking up critical load and speeding up the entire grid recovery process. To solve the frequency security problem of temporary microgrids faced in the load restoration process, this paper proposes an adaptive fuzzy model predictive control (adaptive fuzzy‐MPC) strategy to obtain effective frequency regulation to suit the special characteristics of this process. First, the load restoration plan within a short time frame is regarded as the feedforward information and assists in the establishment of the MPC model. Then, considering the uncertainty of renewable distributed generations, the regulation resources are cooperated by an adaptive fuzzy controller which provides the weights of different regulation resources adopted in MPC. Specifically, the base weights of the energy storage system and renewable distributed generations are obtained from fuzzy rules, and then the weight for each regulation resource is modified by the designed adjustment rules. Simulation results illustrate that the proposed strategy can efficiently improve frequency performance while making various frequency regulation resources with different regulation capacities cooperate properly, which can further accelerate the load restoration progress and enhance system resilience.