Frequency Control Of Microgrid Research Articles

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.

Designing optimized PID controller using improved bacterial foraging optimization algorithm for robust frequency control of islanded microgrid

Designing optimized PID controller using improved bacterial foraging optimization algorithm for robust frequency control of islanded microgrid

Secondary Frequency Control of Microgrids: An Online Reinforcement Learning Approach

In this article, we present a reinforcement learning-based scheme for secondary frequency control of lossy inverter-based microgrids. Compared with the existing methods in the literature, we relax the common restrictions on the system, i.e., being lossless, and the transmission lines and loads to have known constant impedances. The proposed secondary frequency control scheme does not require <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> information about system parameters and can achieve frequency synchronization within an ultimate bound in the presence of dominantly resistive and/or inductive line and load impedances, model parameter uncertainties, and time varying loads and disturbances. First, using Lyapunov theory, a feedback control is formulated based on the unknown dynamics of the microgrid. Next, a performance function is defined based on cumulative costs toward achieving convergence to the nominal frequency. The performance function is approximated by a critic neural network in real-time. An actor network is then simultaneously learning a parameterized approximation of the nonlinear dynamics and optimizing the approximated performance function obtained from the critic network. Furthermore, using the Lyapunov approach, the uniformly ultimate boundedness of the closed-loop frequency error dynamics and the networks' weight estimation errors are shown.

Frequency control of hybrid microgrid comprising solid oxide fuel cell using hunger games search

Frequency control of hybrid microgrid comprising solid oxide fuel cell using hunger games search

Distributed event-triggered secondary frequency control of islanded AC microgrids under cyber attacks with input time delay

This article proposes a distributed event-triggered secondary frequency control considering cyber attacks and disturbances subject to input delay for islanded AC microgrids (MGs). The reliance on communication networks exposes MGs to cyber attacks. Therefore, detection and prevention of cyber attacks is one of the most important issues for islanded MGs. The purpose of this article is the analysis of the impacts of cyber attacks, such as false data injection (FDI) and denial-of-service (DoS) on communication links and local controllers (LCs), in the presence of time delay in communication links. Our method conserves communication resources by reducing the number of transmissions of sampled data. Also, each distributed generation (DG) can quickly detect and isolate corrupted links and controllers. Moreover, we have analyzed the stability of our proposed strategy by the Lyapunov theory. The superior features of our proposed method, including cyber security, number of transmissions of sampled data, and communication time delay, have been investigated in MATLAB/SimPowersystems Toolbox.

Learning-based Fractional Order PID Controller for Load Frequency Control of Distributed Energy Resources Including PV and Wind Turbine Generator

Due to the ever-increasing penetration of renewable resources, Frequency control of microgrids has recently been received special consideration from researchers. The continual supply of load consumption is the major issue of standalone microgrids due to the high penetration of renewable resources. Furthermore, microgrids suffer from low inertia against load changes due to their small size and unpredictable load interruption. In addition to the above-mentioned issues, the uncertain and intermittent behaviors of renewable resources cause problems to keep the balance between load and generation sides. Hence, it is very important to consider novel control methods for keeping balance and consequently control of frequency deviation. In this research, a novel learning-based fractional-order controller is proposed to control the frequency of microgrids including micro-turbines, photovoltaic panels, and wind turbines in order to increase system stability and reduce frequency fluctuation time. The efficiency of this controller has been compared with conventional methods in the simulation and result section.

Intelligent voltage and frequency control of islanded micro-grids based on power fluctuations and communication system uncertainty

Control of critical micro-grid factors such as voltage/frequency is complex and challenging in power distribution networks that include micro-grids. Therefore, providing an efficient and optimal control framework to maintain stability and control the critical factors of the network significantly affects the development of micro-grids goals. The present study proposed the intelligent voltage/frequency control scheme in primary and secondary micro-grids. Micro-grid voltage/frequency restoration was planned based on the PSO-Fuzzy control algorithm in the primary control. In addition to optimizing the members of the fuzzy controller, the PSO optimization algorithm was also used to calculate the voltage/ frequency deviation based on the voltage error factors and the violation of the deviation from the frequency reference. The PSO-Fuzzy structure was provided to optimize hybrid energy storage units' charge and discharge thresholds. Moreover, an intelligent artificial neural network algorithm was presented based on Lyapunov stability equations and a communication system platform to compensate for the voltage/frequency deviation in the secondary control. The proposed algorithm had optimal and efficient performance in different scenarios, such as the effect of load dynamic and its type, power fluctuations, and communication system delays.

Performance Assessment of Novel Solar Thermal-Based Dual Hybrid Microgrid System Using CBOA Optimized Cascaded PI-TID Controller

The article assesses the frequency control of a dual area hybrid microgrid (DHM) that comprises solar thermal systems alongside biodiesel-powered generators, energy storage components, and DC link. The chaotic butterfly optimization (CBOA) technique is used to attain the tuned gain constraints of the cascaded PI-TID controller. The novelty of the system lies in the integration of a combined solar gas turbine and solar chimney for load frequency control studies. Also, the application of CBOA to tune the controllers of cascaded PI-TID controllers is a novel approach. The superiority of CBOA tuned PI-TID controller is obtained after performing a comparative analysis of PID, TID, and PI-TID for controller selection and PSO, SCA, BOA, and CBOA for selecting the superior algorithm. The outcome of each component of the system is analyzed and subjected to the consideration of different real-time scenarios. Sensitivity evaluation is carried out by altering the source and load settings to establish the domination of the CBOA optimized PI-TID controller.

An approach to arranging primary and secondary control of the operating parameters in microgrids featuring inverter-connected generator sets

Various low-power generator sets (GS) are mainly integrated into microgrids by means of inverters coupled with energy storage systems (ESS). ESSs are connected either to the DC busbars of GSs or to the AC busbars of the microgrid, in this case they are equipped with individual inverters. Use of ESS helps balance power in cases of load surge / loadshedding when the microgrid is islanded. This paper overviews approaches to arranging primary and secondary control of the operating parameters of microgrids. It discusses the technical challenges of, and possible solutions for, implementing primary and secondary control in low- and medium-voltage distribution grids featuring inverter-connected GSs. Calculations of electromechanical transients show that inverter-connected GSs have advantages over conventional GSs when used microgrids that are weakly connected to the power system (the external grid) or islanded. In a microgrid featuring inverter-connected GSs, active and reactive power need to be controlled separately as in power systems featuring conventional GSs; implementation of such controls must be adjusted for the parametric and topological characteristics of low- and medium-voltage distribution grids. To address the issues of linked control, this paper proposes a comprehensive approach that adjusts microgrid design for the specifics of inverter-connected GSs, improves inductance, and incorporates algorithmic solutions. It details upon the virtual impedance algorithm, which extends the common principle of droop speed control. Its implementation helps load the GSs and the ESS with adjustments for their installed capacity; it can also simulate the mechanical constant of GS inertia. Primary control has a low margin that mainly comes from the ESS; thus, backups available to secondary control must be used to compensate for the deviations in operating parameters; this is a key challenge of secondary frequency and voltage control in microgrids. When primary and secondary voltage and frequency controls have been duly implemented in a microgrid, its GSs, the ESS, and electricity delivery to the loads within the microgrid can all operate reliably in a variety of operating situations.

Robust Frequency Control in Interconnected Microgrids: An H$_2$/H$_{\infty }$ Control Approach

The advancement of renewable energy resources and their implementation in the power sector poses a serious challenge of maintaining the frequency. In this article, a specified structure-based H <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_2$</tex-math></inline-formula> /H <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_\infty$</tex-math></inline-formula> controller is proposed to stabilise the frequency of the interconnected microgrids system. The norms of the controller are optimized using the teaching-learning-based optimization. A dynamic frequency model of two area microgrids interconnected through a tie-line has been employed to inspect the frequency control of microgrids. Generation using numerous renewable resources and storage sources are considered in suitable combination. The dynamics of dc-link along with measurement unit are also considered in each of the microgrids. In addition, the microgrids are designed with demand response program to damp out the oscillations. A comparative analysis of controllers designed using various existing algorithms namely particle swarm optimization, genetic algorithm, and simulated annealing has been presented. The system response attained is compared to that of other forms of controllers in the literature. Varying input conditions are assumed for wind and solar generation units and their respective frequency responses are studied utilizing two of the best performing algorithms.

Flywheel energy storage system based microgrid controller design and PHIL testing

Microgrids consisting of renewable energy based distributed generators have become popular as a way of energizing off-grid systems. Due to their low-inertia, these distributed generators require a robust frequency control system to maintain it. This problem is amplified by the fact that there is no centralized grid that anchor the system voltage and frequency. For this reason, such off-grid microgrid employs storage systems and diesel generators to provide some flexibility. Flywheel energy storage systems (FESSs) have very quick reaction time and can provide frequency support in case of deviations. To this end, this paper develops and presents a microgrid frequency control system with FESS. The system performance tests are performed with real-equipment where FESS is connected to digital real time simulator. Several frequency events are triggered and the frequency profile is observed to compare microgrid’s performance with and without the developed frequency control. Results show that flywheel energy storage system provides a much smoother frequency profile with less deviations.

Distributed Finite-Time Event-Triggered Frequency and Voltage Control of AC Microgrids

This paper proposes a finite-time event-triggered secondary frequency and voltage control for islanded AC microgrids (MGs) in a distributed fashion. The proposed control strategy can effectively perform frequency restoration and voltage regulations, while sharing the active and reactive power among the distributed generators (DGs) based on their power ratings. The finite-time control enables a system to reach consensus in a finite period of time enhanced from the asymptotic convergence. The event-triggered communication is utilized to reduce the communication burden among the DG controllers by transmitting data among DGs if an event-triggering condition is satisfied. The performance of the proposed finite-time event-triggered frequency control is verified utilizing a hardware-in-the-loop experimental testbed which simulates an AC MG in Opal-RT.

Design of Improved Nonlinear Active Disturbance Rejection Controller for Hybrid Microgrid With Communication Delay

In this paper, an improved nonlinear active disturbance rejection control (INLADRC) approach is proposed for load frequency control of hybrid microgrid with communication delay. The INLADRC technique includes a nonlinear extended state observer (NESO) to estimate the system states and a nonlinear controller for the cancellation of the generalized disturbance acting on system. The effect of communication delay in the hybrid microgrid system is alleviated via the incorporation of an auxiliary structure that also restores the synchronization between the inputs of NESO. The efficacy of the proposed approach is validated via a comprehensive analysis, wherein step variations as well as random perturbations are considered in solar power, wind power and load demand. Further, the performance of proposed technique is also corroborated via consideration of real time solar and wind data. Moreover, the robustness of INLADRC technique is investigated in presence of parametric uncertainty, model-plant mismatch, delay time mismatch as well as varying communication delay. An extensive comparative analysis is a testimony to the effectiveness of INLADRC approach.

Islanded micro-grid frequency control based on the optimal-intelligent lyapunov algorithm considering power dynamic and communication uncertainties

Frequency control is considered as one of the vital factor in electrical networks. The idea of ​​micro-grids based on renewable resources and energy storage units is one of the attractive solutions to the current network challenges. In this research, a novel method based on the uncertainties of power generation and using the energy storage characteristics in micro-grid frequency control is presented. Objectives of this study include 1- Management and control of energy storage unit, especially batteries in order to create a frequency support mechanism in the micro-grid. 2- Management and protecting the battery against the changes in charge and discharge currents, reducing transient fluctuations affecting the battery and also preventing interruptions suddenly the battery power. Accordingly, the frequency control method based on modeling uncertainties as well as the use of stability equations of the Lyapunov function and the optimal distribution of active power between power sources and storage units are described. The proposed method is then validated, analyzed and exploited in the primary and secondary. In the following, the optimal factors related to storage protection using PSO algorithm are presented. The stability of the proposed method, analysis of eigenvalue ​​and also the results are analyzed by MATLAB / Simulink software.

Electric Vehicles Aggregation for Frequency Control of Microgrid under Various Operation Conditions Using an Optimal Coordinated Strategy

This paper presents a novel optimal coordinated strategy for frequency regulation (FR) through electric vehicles (EVs) under variable power system operation states (PSOSs). The methodology ensures a secure and economical operation of the power system through the coordination of the frequency regulation, the power of the electric vehicles and generators with multiple optimization objectives. In the normal state of operation of the power system, the battery degradation cost is taken into account and accordingly the minimum FR cost is utilized as an objective. On the other hand, for abnormal operation, the optimization objective considers the minimum frequency restoration duration. Different scenarios have been investigated to validate the proposed method. The simulation results confirm the usefulness and superior performance of the proposed optimized coordinated control strategy.

An improved moth swarm algorithm based fractional order type-2 fuzzy PID controller for frequency regulation of microgrid system

ABSTRACT This research work introduces an improvised moth swarm algorithm (i-MSA) to resolve the load frequency control issue of microgrid (MG) systems. A microgrid system is a cluster of distributed generation (DG) power sources like photovoltaic (PV), wind power systems along with electric storage devices such as electrochemical batteries, flywheel systems, and electric vehicles. The unpredictable responses of DG sources influence a large frequency deviation, which creates frequency regulation problems taken as the problem objective for this research work. In the preliminary stage, the effectiveness of the i-MSA has been established by performing a comparative analysis considering single/multidimensional benchmark test functions. To validate the superiority of the i-MSA method, the technical viability has been measured by comparing the outcomes of the proposed approach with those of some newly recommended optimization methods. Furthermore, an advanced hybrid fractional order type-2 fuzzy PID (FO-T2F-PID) controller is projected for frequency control of the MG system. The uncertainties due to DG source penetration in the MG system and the impact of storage devices including the EV system to regulate the frequency have been studied using the proposed approach. The effect of operational parameter variations has been studied through a sensitivity test. From the data analysis, it is observed that the i-MSA-scaled FO-T2F-PID approach presents advancement in the fitness function of 29.11%, 33.53%, 47.16%, and 55.37% as compared to h-DE-PS: 2DOF/PID, I-JAYA: fuzzy PD/PI-PD, hybrid DFPS: TID, and Kriging: FOPID approaches, respectively. Similarly, the improvement in the settling interval for the proposed approach is observed to be 33.83%, 35.82%, 38.12%, and 42.18% as related to h-DE-PS: 2DOF/PID, I-JAYA: fuzzy PD/PI-PD, hybrid DFPS: TID, and Kriging: FOPID approaches, respectively. To indorse the practicability of the i-MSA-based FO-T2F-PID method, real-time simulation testing has been carried out in the MATLAB-interfaced OPAL-RT experimental setup. Finally, the optimum results obtained from the proposed approaches are confirmed by relating the same to some recently published frequency regulation outcomes in a benchmark power system model. It is observed that the i-MSA-based FO-T2F-PID method delivers advancement in microgrid frequency control compared to recent research outcomes.

Frequency Control and Energy Management of Microgrid with Distributed Energy Storage

The purpose of the Energy Management System (EMS) is to ensure a high degree of efficiency, stability, and dependability. And the electrical system should have the ability to adjust to the majority of changes such as renewable energy integration. In some situations, the power generated by distributed power sources is greater than the local demand. This has an effect on the microgrid's stability and frequency. Smart energy management in a microgrid is proposed in this research., consisting of a wind power generator, photovoltaic and storage energy system for frequency regulation, and system balance. The above paper's main contribution is a system for managing energy. based on a clever strategy using MATLAB/Simulink. The results of the simulation and analyses demonstrate that the suggested microgrid energy management system is efficient at balancing energy.

Adaptive Frequency Control of Microgrid Based on Fractional Order Control and a Data-Driven Control With Stability Analysis

In this paper, a new adaptive fractional frequency control method for microgrids(MG) and low inertia networks is presented. The newly proposed grid frequency control is based on the droop and inertia controller for doubly-fed induction generator (DFIG) wind turbine (WT) using a data-driven algorithm. Also, in this paper, to ensure the grid frequency stability, the stability region boundary has been calculated using the parameter space method for above and below synchronous speeds. In the first step in the proposed method, a data-driven control (DDC) is used to update the frequency control coefficients. In the second step, in order to deployment more frequency data and to use both frequency error concavity and slope, the utilization of fractional gradient descent (FGD) and fractional inertia control is proposed. In the third step to maintain frequency stability, the updated frequency controller coefficients are compared with the stability region boundary. If the updated frequency controller coefficients are in the authorized band, they are applied. To test the proposed idea is a simulated real grid in Ontario, Canada. The simulation results indicate the proper operation of the control system in transient and steady-state and under different conditions.

Distributed Model Predictive Frequency Control of Inverter-Based Networked Microgrids

This paper proposes a distributed frequency control method for an off-grid inverter-based networked microgrid system (NMS) with loads, renewable generators and energy storage devices (ESDs). The frequency regulation problem is formulated as a model predictive control (MPC) problem that aims to maintain the supply-demand power balance within each microgrid and scheduled net power interchange among connected microgrids at minimal regulation costs. The charging/discharging efficiencies as well as energy capacities of ESDs, and constraints on bus voltages are also considered. The proposed MPC problem is solved by a distributed projection-based algorithm via information sharing between adjacent buses. The effectiveness of the proposed method is validated by simulations implemented in Matlab/Simulink.

A Cooperative Rate-Based Model Predictive Framework for Flexibility Management of DERs

Collective self-consumption is driving the transformation of distribution networks towards independently controllable community microgrids. The objective of this work is to utilize limited heterogeneous flexibilities in the system to perform grid-support functions to evade additional investment on dedicated storage facilities. We propose a cooperative receding horizon control that allows optimal use of the collective resources over the prediction horizon. The conventional linear state-space model employed in the predictive control is replaced by a novel rate-based model that propagates state derivatives rather than the states across the prediction horizon, thus eliminating offset errors. The proposed cooperative predictive control strategy with rate-based model has been applied to the microgrid frequency control problem. The proposed control strategy has been illustrated on a power hardware-in-the loop platform by modeling a microgrid system with grid-supporting <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">der</small> s. The simulations reveal the effectiveness of the proposed strategy by comparing the control solution with a dedicated storage facility and its replacement distributed flexible resources.