Frequency Regulation In Microgrids Research Articles

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.

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.

Developing Control Strategy for PV-Based Distributed Generator for Enhancing Frequency Regulation of Microgrid

This paper presents a control strategy for a photovoltaic (PV)-based distributed generator (DG) to enhance the frequency regulation of a microgrid. A microgrid is a small-scale power system that integrates distributed energy sources and interconnected loads, which can operate independently or in parallel with the main grid. However, the high integration of DGs poses stability problems, particularly the frequency regulation under contingencies in the microgrid. For example, the shutdown of one generating unit or the reduction of system inertia owing to the high integration of converter-based DGs will increase the risk of instability of the microgrid and the main grid. Therefore, maintaining and increasing the frequency regulation capability is crucial in microgrid operation. This paper focuses on developing a controller for PV DG based on virtual inertia control combined with the conventional control method of a converter in order to regulate the microgrid frequency under contingency. The proposed control strategy for a PV-based DG is then verified through simulation of the 14-bus microgrid model using MATLAB/Simulink, showing regulation in frequency under island mode operation of the microgrid. In addition, comparisons between the original and proposed control strategy microgrid model are then carried out.

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.

Droop-Free Sliding-Mode Control for Active-Power Sharing and Frequency Regulation in Inverter-Based Islanded Microgrids

This paper introduces a simple decentralized sliding-mode (SM) approach to control active power sharing by regulating the local frequency in inverter-based islanded microgrids (MGs). Its sliding surface arises from the frequency correction term introduced in the droop-free technique; it relates local active power to neighboring MGs’ active power by considering available communications among voltage source inverters. Then, this schema allows one to avoid hierarchical control just as the droop-free method does, and the benefits associated are twofold. First, it reduces the steady-state frequency error while providing accurate active power distribution. Second, the system stays reliable, withstands uncertainties, and provides a fast transient response. A Lyapunov analysis confirms stability, and simulations on a realistic four-inverter MG platform substantiate the control scheme’s effectiveness. Its performance regards frequency regulation while achieving active power sharing, stability, and robustness against clock drifts and load steps.

A New Optimized FOPIDA-FOIDN Controller for the Frequency Regulation of Hybrid Multi-Area Interconnected Microgrids

This paper proposes a combined feedback and feed-forward control system to support the frequency regulation of multi-area interconnected hybrid microgrids considering renewable energy sources (RESs). The proposed control system is based on a fractional-order proportional-integral-derivative-accelerated (FOPIDA) controller in the feed-forward direction and a fractional-order integral-derivative with a low-pass filter compensator (FOIDN) controller in the feedback direction, referred to as a FOPIDA-FOIDN controller. Moreover, the parameters of the proposed FOPIDA-FOIDN controller (i.e., twelve parameters in each area) are optimally tuned using a proposed hybrid of two metaheuristic optimization algorithms, i.e., hybrid artificial gorilla troops optimizer (AGTO) and equilibrium optimizer (EO), and this hybrid is referred to as HGTOEO. The robustness and reliability of the proposed control system are validated by evaluating its performance in comparison to that of other counterparts’ controllers utilized in the literature, such as PID, FOPID, and tilt integral derivative (TID) controller, under the different operating conditions of the studied system. Furthermore, the proficiency of the proposed HGTOEO algorithm is checked against other powerful optimizers, such as the genetic algorithm, Jaya algorithm, improved Jaya algorithm, multi-verse optimizer, and cost-effective multi-verse optimizer, to optimally design the PID controller for the load frequency control of the studied two-area interconnected microgrid. The MATLAB simulation results demonstrate the viability and dependability of the proposed FOPIDA-FOIDN controller based on the HGTOEO algorithm under a variety of load perturbations and random production of RESs.

Microgrid Frequency Regulation and Optimal Sizing of Emergency Generator Considering VSG Coupled Electric Vehicles

Recently, the transition from conventional to renewable energy sources (RESs), from internal combustion engine vehicles to electric vehicles (EVs), and from the main grid to microgrids (MGs) are essential goals to both reduce greenhouse gas emissions and ensure the stability of power systems. However, the transitions cause new concerns in the grid including technical challenges and financial viability. This study examines the RES-based MG under realistic conditions considering the uncertainty in fleet size of EVs, emergency generator capacity, solar irradiation, and wind speed in island mode. The work aims to provide effective solutions including conventional methods alongside today’s trend namely doubly fed electrical generators (DFIG), vehicle-to-grid mechanism (V2G), maximum power point tracking controller (MPPT), voltage source inverter (VSI) with high switching frequency for technical challenges, and virtual synchronous generator (VSG) mechanism for financial viability. The paper provides a guide for resizing the emergency generators capacity depending on system instability. The observations verify that the control mechanisms reinforce the system to remain stable by decreasing the range of frequency fluctuation from 3.1 to <0.05 Hz, the peak point of frequency from 51.8 to 50.05 Hz, and the emergency generator capacity from 0.7605 to 0.3420 MVAr at MATLAB and Simulink.

Twin Delayed Deep Deterministic Policy Gradient (TD3) Based Virtual Inertia Control for Inverter-Interfacing DGs in Microgrids

Environmental and energy security concerns lead to the continuous displacement of traditional fossil fuel-based power generation to power electronics interfaced distributed generations (DGs). Increasing penetration of renewable energy sources and the substitution of synchronous generators with power electronic converters have resulted in reduced power system inertia and damping. This causes large frequency deviations and a higher rate of change of frequency. The fast and flexible nature of the energy storage system with a designed controller can achieve frequency stability in low inertia microgrids (MGs). The conventional proportional-integral-based virtual inertia controller is unable to eliminate frequency instability in low inertia MG. To enhance frequency stability, this article proposes a virtual inertia emulation strategy using a twin delayed deep deterministic policy gradient (TD3) algorithm for fast frequency regulation of MGs with inverter-based DGs. A comparative analysis of the TD3 scheme and the conventional method is made. The results show that the TD3-based virtual inertia control provides better tracking with a 56.6% reduction in frequency deviation and faster transient recovery than the conventional virtual inertia control against a broad range of operational scenarios. Performance metrics and simulation results are shown to demonstrate the feasibility of the proposed control scheme.

Neuromorphic deep learning frequency regulation in stand-alone microgrids

Frequency instability has been a growing problem in recent years due to the rising penetration of distributed generating systems in the format of Microgrids (MGs), which are powered by renewable energy sources (RESs) with an unpredictable nature. The provision of an effective load frequency control (LFC) to an MG model under such conditions contributes significantly to the restoration regarding the unconfigured power system’s stability. An MG structure is employed, which combines renewable energy sources like solar and wind, as well as biologically renewable sustainable energy sources like wastewater, agricultural and domestic wastes, and contains appropriate battery systems and is suited to achieve both energy and waste control in this study. In addition, redox flow battery (RFB), an innovative battery storage system with a fast dynamic response in this MG structure, has been considered as one of the energy storage devices. A nonlinear integral backstepping (NIB) controller is adopted to stabilize the frequency deviation of the integrated MG system with RFB under various level of load disturbances and randomness of RESs. In particular, a spike neural network (SNN) based on neuromorphic platform is proposed to adjust the coefficients of NIB controller. Furthermore, real time analyses are performed with OPAL-RT to validate the feasibility of the proposed strategy from a systematical viewpoint. As a result of this study, the proposed controller for load disturbance, RES power changes, and contingency circumstances in bio renewable MG is determined to be flexible enough to satisfy the efficient frequency regulation for these grids.