Frequency Control Of Microgrid Research Articles

A modified model predictive control method for frequency regulation of microgrids under status feedback attacks and time-delay attacks

As a promising technology to integrate renewable energy and enable decentralized energy management, microgrid (MG) offers an appealing network architecture due to its potential economic, environmental, and technical benefits. However, with the increasing deployment of intelligent devices and the growing network interconnectivity, communication channels and controllers for MGs become more vulnerable to emerging cyber threats. Two types of attacks are considered in this paper, including the data integrity attacks on the system status feedback and time-delay attacks which may disrupt the control of the MGs and lead to adverse consequences. A modified model predictive control (MPC) scheme is proposed for the secondary frequency control of MGs based on the online status switching method and generalized cross correlation (GCC) estimation to detect the real system status and time delay injected to the control system. The Euclidean metric is used in the online status switching method to obtain the real system states. Meanwhile, the GCC based delay estimation is developed to detect and track the time delay posed by attacks in the real-time operation. Case studies under different scenarios of the attacks are conducted, and the simulation results verify the effectiveness of the proposed MPC scheme under the cyberattacks.

A comparative study between lithium-ion battery and Pb-acid battery-supercapacitor hybrid energy storage system for frequency control and Energy management of islanded microgrids

Among various storage technologies used for the energy storage systems, the supercapacitors, the Pb-acid-Batteries (PABs) and the lithium-Batteries (LBs) are widely used for microgrid applications. The supercapacitors with high-power density are suitable for fast power regulations; conversely, the PABs have high-energy density, which makes them suitable for long-term energy management. Since the PABs and the supercapacitor can complement each other deficiencies, their combination as a hybrid energy storage system is used. However, the LB has both high-energy and high-power densities. Therefore, an LB Energy Storage System (LBESS) can similarly function like a Pb-acid battery-supercapacitor-hybrid-ESS (PSHESS). This paper tends to determine which one is technically and economically more suitable for applications in islanded microgrids. For this purpose, a frequency control and energy management scheme is proposed. It maintains the balance between demand and supply, and also keeps the microgrid frequency within safe operational limits using the least needed sizes for the energy storage systems. Simulation results reveal the costs of LIBESS and PSHESS would be $140325.93 and $209408.37, respectively, which shows that the cost of the PSHESS is $69082.44 or almost 49.2 % more than the cost of the LIBESS. This indicates that the LBESS is more cost-effective than the PSHESS.

Frequency control of fully-renewable interconnected microgrid using fuzzy cascade controller with demand response program considering

The main purpose of this paper is to design a good fuzzy cascade controller for interconnected microgrids (μGs) with supporting a frequency perturbation-based demand response program. A fuzzy PD-(1+I) controller is optimally designed to perform the load frequency task in a fully-renewable interconnected μGs. In the proposed control strategy, exact adjusting of controller parameters and membership functions has a key role to achieve the robust performance. Thus, the fuzzy PD-(1+I) controller is automatically designed and updated using a nature-inspired mayfly optimization algorithm for finding a better controller and reducing system control cost. It combines the fuzzy theory and cascade control advantages to enhance load disturbance rejection effort in each μG and dump frequency fluctuations considering system parametric uncertainties and renewable energy sources (RESs) generation changes. The studied two-area islanded μG system by applying a fuzzy PD-(1+I) controller has been investigated in six different situations in comparison with the fuzzy PID and PD-(1+I) cascade controllers to demonstrate capability of load disturbance rejection, RESs generation changes and system parameters variation. The results in all cases show the decisive superiority of the fuzzy PD-(1+I) controller and its high adaptability than the other controllers.

Fractional order frequency proportional-integral-derivative control of microgrid consisting of renewable energy sources based on multi-objective grasshopper optimization algorithm

In recent years, fractional order proportional-integral-derivative (FOPID) controllers have been applied in different areas in the academy due to their superior performance over conventional proportional-integral-derivative (PID) controllers. When the literature is reviewed, it has been observed that lack of studies that use swarm-based and multi-objective optimization algorithms together with FOPID controllers in frequency control of micro-grid. The load frequency control (LFC) problem is considered as two objectives in order to eliminate the complications that occur when only the frequency deviation is minimized. In our study, a method called MOGOA-FOPID in which both the frequency deviation and the control signal are minimized together for the frequency control in the microgrid is proposed. By using the multi-objective grasshopper optimization algorithm (MOGOA), both the frequency deviation and the control signal are minimized together, and thus, it is aimed to limit the battery capacity, reduce the flywheel jerk and avoid high diesel fuel consumption as well as an effective frequency control. In order to obtain a more realistic system, not only the photovoltaic (PV) solar and wind power but also the load demand is taken in a stochastic structure. Then, the results of the proposed MOGOA-FOPID are compared with the results of multi-objective genetic algorithm (MOGA)-based PID/FOPID and MOGOA-PID and its superiority is demonstrated. Finally, robustness tests of the system are performed under the perturbed parameters and outperform of MOGOA-FOPID over other methods is seen.

A Disturbance Observer Based Fuzzy Feedforward Proportional Integral Load Frequency Control of Microgrids

In this paper, the load frequency control problem of microgrids in islanded operation mode is tackled using Fuzzy Feedforward PI (FFPI) controller. To this end, a feedforward loop is considered in the control structure of the microgrid in addition to the classical feedback controller wherein a proportional integrator controller is used. The disturbance signal, which can be load variations or renewable energy resources uncertainties, is estimated using a disturbance observer. The understudy microgrid includes wind turbine and solar cells as renewable sources, and a diesel generator and loads. A fuzzy controller is also used for pitch angle control of the wind turbine, which may smooth out the generated power and improve the frequency control of microgrid. To show the capability of the proposed strategy, two different scenarios are considered and the obtained simulation results easily approve the efficiency of the proposed structure for load frequency control of microgrid in islanded operation mode.

Investigations of Decoupled Trigonometric Saturated and Fuzzy Logic Techniques for the Automatic Frequency Control of Islanded Microgrid

This paper involves the investigation of new techniques for the automatic load frequency control of islanded Microgrids. Microgrids are being established as a part of smart grid environment. In modern power systems, smart grid represents the solution for many of traditional power system problems such as frequency fluctuations. Frequency fluctuations have negative consequences in terms of electrical equipment life, production cost and production losses relative to costumers and electricity producers. So, the frequency of power system must be kept in acceptable range. In order to operate a power system with fixed frequency, it is necessary to always maintain a balance between the generation and the consumption of active power. The frequency droop control methods are widely used to control active power and frequency of the parallel synchronous generators in the traditional power grid. At present, this method has also been applied to the control of parallel inverters to share the load demand in proportion to their ratings. In order to improve the frequency control of traditional droop control technique applied in islanded microgrid, It is proposed to investigate the Decoupled Trigonometric Saturated (DTS) and fuzzy droop control techniques on islanded microgrids which uses meshed parallel inverter systems. To verify the performance of the proposed ALFC based on Decupled trigonometric saturated controller, fuzzy PI controller the MATLAB/SIMULINK environment is used.

Investigations of Decoupled Trigonometric Saturated and Fuzzy Logic Techniques for the Automatic Frequency Control of Islanded Microgrid

This paper involves the investigation of new techniques for the automatic load frequency control of islanded Microgrids. Microgrids are being established as a part of smart grid environment. In modern power systems, smart grid represents the solution for many of traditional power system problems such as frequency fluctuations. Frequency fluctuations have negative consequences in terms of electrical equipment life, production cost and production losses relative to costumers and electricity producers. So, the frequency of power system must be kept in acceptable range. In order to operate a power system with fixed frequency, it is necessary to always maintain a balance between the generation and the consumption of active power. The frequency droop control methods are widely used to control active power and frequency of the parallel synchronous generators in the traditional power grid. At present, this method has also been applied to the control of parallel inverters to share the load demand in proportion to their ratings. In order to improve the frequency control of traditional droop control technique applied in islanded microgrid, It is proposed to investigate the Decoupled Trigonometric Saturated (DTS) and fuzzy droop control techniques on islanded microgrids which uses meshed parallel inverter systems. To verify the performance of the proposed ALFC based on Decupled trigonometric saturated controller, fuzzy PI controller the MATLAB/SIMULINK environment is used.

Imbalance‐based primary frequency control for converter‐fed microgrid

Frequency droop control is a simple and effective frequency control method. However, it is not appropriate as a primary frequency control for microgrids with energy storage systems and voltage source converters (VSCs) owing to their slow response speed. In addition, it is difficult to determine the grid balance only with frequency deviation. In this paper, a new converter-fed microgrid primary frequency control method based on the estimated active power imbalance for fast response and less variability in the transmission system is proposed. The active power imbalance is estimated via frequency deviation, frequency drop speed and the modified swing equation. The estimated imbalance indicates the status of the power imbalance more quickly and accurately than the frequency deviation. The proposed method does not require communication devices, responds quickly to frequency drops, and prevents unnecessary operation of the grid-connected VSC because it uses the estimated imbalance instead of the frequency or angle for droop control. Simulation results show that the proposed method is significantly faster than frequency droop control methods, improves the rate of change of frequency and frequency nadir and reduces variability in the transmission system.

Load frequency control of a microgrid employing a 2D Sine Logistic map based chaotic sine cosine algorithm

This paper proposes a maiden application of a two dimensional Sine Logistic map based chaotic sine cosine algorithm (2D-SLCSCA) optimized classical PID controller for load frequency control (LFC) of an islanded microgrid (MG). In comparison to random variables and 1D chaotic sequences, the 2D chaotic sequences are more ergodic and possess a wider chaotic range, thereby enhancing the global convergence speed and search capability of an algorithm. Initially, the proposed 2D-SLCSCA is tested on eight classical benchmark test functions and its performance is compared with 1D Logistic map based chaotic SCA (1D-LCSCA), 1D Sine map based chaotic SCA (1D-SCSCA), and the SCA incorporating random variables. Test results reveal that the proposed algorithm exhibits better convergence characteristics, statistics, and execution time. Finally, the proposed 2D-SLCSCA is implemented for the LFC analysis of the islanded MG. To establish the competence of the proposed algorithm in this regard, its performance is compared with 2D Hénon map based chaotic SCA, 2D Lozi map based chaotic SCA, improved salp swarm algorithm (ISSA), SCA, grey wolf optimizer (GWO), and particle swarm optimization (PSO) algorithm considering diverse load disturbance patterns in the MG. Simulation results affirm that the proposed control scheme augments the frequency response of the MG exhibiting a maximum percentage improvement of 78.89%, 78.86%, and 96.51% in peak overshoot (OSpeak), peak undershoot (USpeak) and objective function (OFITSE) value, respectively as compared to the other algorithms. Furthermore, sensitivity of the proposed 2D-SLCSCA is validated considering ± 30% variation in the MG parameters.

Coordination of hybrid energy storage system, photovoltaic systems, smart lighting loads, and thermostatically controlled loads for microgrid frequency control

Coordination of hybrid energy storage system, photovoltaic systems, smart lighting loads, and thermostatically controlled loads for microgrid frequency control

Feedforward Fractional Order PID Load Frequency Control of Microgrid Using Harmony Search Algorithm

Feedforward Fractional Order PID Load Frequency Control of Microgrid Using Harmony Search Algorithm

Central Damping Controller for Microgrid Voltage and Frequency Dynamic Stability Using Adaptive Artificial Neural Network

This paper presents an online non-model-based scheme to voltage and frequency control of microgrids in the presence of inverter-based distributed energy resources (DERs). For developing proposed controller, considering adaptive control concept, a central controller is designed through aggregation distribution procedure which optimized using artificial adaptive neural network (AANN). In this case, based on the system dynamic variables, the DERs dynamical models are provided which following Lyapunov-based theory, the corresponding central controller is designed. In this way, the proposed Lyapunov theory is responsible to limit AANN weighted boundaries which following an optimization procedure, it is resulted in controller accuracy. By developing central controller, the intelligent AANN is provided which considering a set of offline training procedure, online values of dynamic variables are estimated through real-time working mode. By this way, it is not required to receive any initial information related to DER variables which based on the developing non-model-based dynamical model, the central damping controller (CDC) is extended. The effectiveness of proposed CDC scheme is verified on a typical microgrid test system consisting of several DERs which considering different fault event scenarios, CDC damping performances are evaluated. Simulation results prove the voltage and frequency damping performances of proposed controller in the presence of low-inertia suppliers.

A fuzzy adaptive fractional order-PID controller for frequency control of an islanded microgrid under stochastic wind/solar uncertainties

Frequency control is the key factor in a renewable energy-based microgrid system. The inherent dynamics and low inertia of most power generating units of microgrids lead to frequency oscillations in the system. This manuscript well addresses on a robust fuzzy adaptive Fractional Order-PID (fuzzy FO-PID) controller and this is used in an AC microgrid model for achieving frequency control under various disturbances. Since a microgrid is devised with a lot of low inertia and large dynamics-based power-generating units, conventional controllers are found to be inferior while controlling the frequency of a microgrid. In the light of this, this work employs a robust fuzzy adaptive Fractional Order-PID controller to achieve improved frequency performance in the microgrid. The proposed fuzzy FO-PID controller acts as a secondary frequency control loop to amend necessary control actions over vibrant frequency under different uncertainties like load dynamics, wind fluctuation and solar intensity variation. The proposed controller is governed by a novel teaching–learning-based optimization (TLBO) technique to obtain optimal parameters under various disturbances. An assignment on a comparative study has been synthesised to justify the supremacy of the proposed TLBO algorithm in regard to the frequency control of a microgrid system.

Robust and Resilient Distributed Optimal Frequency Control for Microgrids Against Cyber Attacks

The optimal frequency control of autonomous microgrids (MGs), i.e., to achieve fast frequency recovery and dynamic power adjustment of the distributed generators in proportion to predefined participation factors, can be achieved in a fully distributed way based on the subgradient consensus protocol. However, such a distributively controlled MG is susceptible to different types of cyber attacks infiltrated from different locations. In this article, a robust and resilient distributed optimal frequency control scheme is proposed to address the threat of cyber attacks. It is facilitated by introducing an auxiliary networked system interconnecting with the original cooperative control system. On condition that the cyber attacks are within certain ranges, the robust design can maintain the functionalities by significantly attenuating the impact. Otherwise, the cyber attacks can be easily detected, and resilient reactions can be taken to mitigate their influences via isolation. Simulation results in a modified IEEE 34-bus MG validate the effectiveness of the proposed approach.

Game theoretic vulnerability management for secondary frequency control of islanded microgrids against false data injection attacks

Game theoretic vulnerability management for secondary frequency control of islanded microgrids against false data injection attacks

Imperialist competitive algorithm optimized cascade controller for load frequency control of multi-microgrid system

ABSTRACT Control of multi-energy source-based microgrid is a complex task due to the presence of unpredictable renewable energy sources (RES). This paper proposes a cascade structure of proportional derivative with (1+ PI) controller (C-PDF(1+ PI)) for load frequency control of an AC multi Micro-grid (MG). The MG contains a thermal power unit, Diesel Engine Generator (DEG), Micro Turbine (MT), Fuel Cell (FC), and uncontrolled solar and wind sources. Diverse storage device units like Battery Energy Storage System (BESS), Fly Wheel Energy Storage System (FESS), and Electric Vehicles (EV) are also included in the studied MG system. The proposed C-PDF(1+ PI) controller consists of a first stage Proportional Derivative controller with filter (PDF) and one plus proportional-integral (PI) controller in the second stage. The Imperialist Competitive Algorithm (ICA) is applied to optimize the controller parameters. To confer superiority of the C-PDF(1+ PI) controller, its responses are related with PI, PID, and PIDF controllers. It is observed that the ITAE improvement in percentage with the proposed approach is 70.64%, 53.23%, and 47.10% compared to PI, PID, and PIDF controller while considering the simultaneous variations in load, solar, and wind powers. To justify the efficacy of the ICA technique, it is compared with other well-established techniques like the Genetic algorithm (GA) and the Cuckoo Search algorithm (CSA). It is observed that for the identical system and C-PDF(1+ PI) controller, the ITAE value improvement in percentage by ICA compared to GA and CSA are 31.94% and 15.93%, respectively, while considering all the three uncertainty like changes in load condition, change in solar power irradiation and changes in wind power conditions. Finally, it is conferred that the proposed ICA optimized C-PDF(1+ PI) controller significantly improves microgrid dynamic performance under various operational conditions.

BMI-Based Load Frequency Control in Microgrids Under False Data Injection Attacks

In this article, the power fluctuation problem caused by adding renewable energy sources to microgrids (MGs) is addressed. These power fluctuations which can cause several adverse effects, including system instability, load shedding, and eventually blackouts are attenuated by designing a load frequency controller (LFC) to provide a constant and uniform frequency in different operation cases of MGs. This article designs a dynamic output feedback controller (DOFC) for LFC in MGs while considering the contraction observer for attack mitigation. We suggest a new formulation of the sufficient conditions for the DOFC design problem in the form of bilinear matrix inequalities (BMIs) and try to minimize the frequency deviation subject to load, solar, and wind energy changes. The proposed formulation effectively changes the problem to a new BMI model which can easily be divided into two problems, one is a convex optimization problem and the remained part is a quadratic matrix inequality problem which is linearized around the feasible solution of the linear matrix inequality part by a Taylor-like expansion. This leads to a more exact and less conservative solution as compared to the previous methods suggested in the literature. To illustrate the merits of the developed approach, numerical simulations on a sample ac–MG are carried out. Comparing norms of the frequency variations in the closed-loop system with multiple prominent methods in previous works, including <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{H}}_\infty }, \ {\boldsymbol{\mu }}$</tex-math></inline-formula> , fuzzy type-1, and intelligent-PI, shows that our proposed method reduces the two and infinity norms of frequency fluctuations by 84% and 80%, respectively compared to the traditional <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{H}}_\infty }$</tex-math></inline-formula> method which is the best among the analyzed approaches. This further verifies the efficacy of the designed DOFC in our article.

Rejectable deep differential dynamic programming for real-time integrated generation dispatch and control of micro-grids

With the application of renewable energy and distributed power generation in micro-grids, conventional artificial intelligent control strategies have shown deficiencies for the frequency control and economic dispatch of micro-grids. Conventional deep learning controllers could provide outputs although when the predicted probability is not high, which will lead to micro-grid system divergence. This paper proposes a rejectable deep differential dynamic programming for the real-time integrated generation dispatch and control of micro-grids. The rejectable deep differential dynamic programming can provide an action from an analytic control algorithm when the predicted probability is not high enough. The deep differential dynamic programming contains four deep neural networks, i.e., “deep differential prediction network”, “deep differential evaluation network 1”, “deep differential evaluation network 2” and “deep differential execution network”. To verify the feasibility and effectiveness of the proposed rejectable deep differential dynamic programming, a total of 25 combined conventional optimization and control algorithms are compared under a micro-grid based on Hainan Power Grid. The numeric simulation results show that the proposed approach can obtain high control performance for the real-time integrated generation dispatch and control framework, which can replace the conventional combined “economic dispatch + automatic generation control + droop control” framework of micro-grids.

Asynchronous Periodic Distributed Event-Triggered Voltage and Frequency Control of Microgrids

In this paper, we introduce a distributed secondary voltage and frequency control scheme for an islanded ac microgrid under event-triggered communication. An integral type event-triggered mechanism is proposed by which each distributed generator (DG) periodically checks its triggering condition and determines whether to update its control inputs and broadcast its states to neighboring DGs. In contrast to existing event-triggered strategies on secondary control of microgrids, the proposed event-triggered mechanism is able to handle the consensus problem in case of asynchronous communication. Under the proposed sampled-data based event-triggered mechanism, DGs do not need to be synchronized to a common clock and each individual DG checks its triggering condition periodically, relying on its own clock. Furthermore, the proposed method efficiently reduces communication rate. We provide sufficient conditions under which microgrid's frequency and a critical bus voltage asymptotically converge to the nominal frequency and voltage, respectively. Finally, effectiveness of our proposed method is verified by testing different scenarios on an islanded ac microgrid benchmark in the MATLAB/Simulink environment as well as a hardware-in-the-loop (HIL) platform, where the physical system is modeled in the Opal-RT and the cyber system is realized in Raspberry Pis.

Inertia-Enhanced Distributed Voltage and Frequency Control of Low-Inertia Microgrids

This paper proposes a novel inertia-enhanced distributed control method to complement the inertia of microgrids. The rate of change of frequency (RoCoF) and the rate of change of voltage (RoCoV) are employed in this paper to quantify the frequency inertia and voltage inertia, respectively. Then, a fully distributed algorithm with constrained changing rates is proposed. By bounding the changing rates of frequency and voltage during the consensus control, the algorithm can address the consensus problem while enhancing the inertia of microgrids. Compared with most inertia control methods, the proposed method can utilize the reserve power of scattered DGs to supply inertia. Besides, it performs better under disturbances and delays than conventional distributed control methods. The effectiveness of the proposed method is validated by several cases in MATLAB/Simulation and a hardware experiment.