Qobad Shafiee

Nowadays, the increasing global demand for energy rises the use of renewable energy sources. One of the main reasons for this trend is the environmental friendliness of these sources. The energy produced by renewable sources is influenced by factors such as sunlight intensity and wind speed. Therefore, the design of power electronic converters for renewable energy applications has become an important topic and has attracted the attention of many researchers. In DC microgrids, various components such as distributed generation sources, energy storage sources, and loads with different electrical characteristics are connected to the DC link. This connection is made through the power electronic converters. The presence of these converters creates two main challenges: 1) load-side converters act as constant power loads, which affect the small-signal stability of the system, 2) source-side converters do not add any inertia or damping to the system, and as a result, the inherent inertia of the entire system is low. The main objective of this thesis is to provide solutions for enhancing dynamic response of low-inertia DC microgrids using model-based predictive control in a systematic manner. This is achieved using the controllable power sources and the concept of virtual inertia using Model Predictive Control (MPC). In this thesis, novel method for improving the dynamic stability of DC microgrids based on the MPC and the concept of virtual inertia is presented. By using this method, virtual inertia coefficients are defined systematically, to improve and as a result, the dynamic response of the microgrid. Additionally, by simplifying the control structure and replacing the conventional PI current and voltage controllers with the MPC, a simpler control structure with optimal performance is proposed. The proposed solution is verified using a test system in the Simulink and SimPowerSystems environments of MATLAB software.

In the era of increasing renewable energy integration into power grids, ensuring grid stability and resilience has become a critical challenge, particularly in regions with weak grid infrastructure. Voltage stability, as key concern in modern power systems, is significantly impacted by the proliferation of renewable energy sources, which often exacerbate the vulnerabilities of these weak grids. The voltage control loop of a Virtual Synchronous Generator (VSG), commonly implemented using conventional reactive power-voltage droop control, is particularly prone to instability when subjected to disturbances or operating under weak grid conditions. Addressing these challenges is essential for the reliable operation of future power systems. This PhD thesis comprises three interconnected studies addressing crucial aspects of voltage stability and power quality in weak grids, focusing on mitigating the adverse effects of grid disturbances caused by distributed generation (DG), such as solar and wind power. The first study presents an innovative approach to enhance grid stability by optimizing passive LCL (inductor-capacitor-inductor) filters using evolutionary algorithms. Specifically, Multi-Objective Particle Swarm Optimization and Multi-Objective Genetic Algorithm techniques are employed to design filters that improve power quality and minimize harmonic distortion. This study highlights the importance of optimizing filter parameters to address weak grids. Through numerical simulations, the proposed method demonstrates significant improvements in total harmonic distortion (THD) and stability margin when connecting grid-connected converters to weak and very weak grids. The second study utilizes artificial intelligence (AI) to address the persistent issue of voltage instability in modern power systems. It introduces an AI-driven method that combines backpropagation-based artificial neural networks (ANNs) with surrogate optimization techniques. The new model optimizes the droop coefficient of voltage-reactive power control and fine-tunes proportional-integral controller parameters used in VSG strategy control, to enhance the performance of grid-connected converters in weak grids. Stability analyses and simulation results validate the effectiveness of this AI-driven approach in addressing voltage instability in the weak grid conditions. The study proposes an advanced control strategy to enhance voltage stability in weak grids, addressing the limitations of conventional reactive power-voltage droop control, especially in enhanced VSG. This research introduces a novel cascade droop control (CDC) technique that enhances voltage support and improves grid stability, even under challenging conditions. The proposed controller extends conventional droop control with layered control loops, offering improved performance without sacrificing simplicity or cost efficiency. The effectiveness of the CDC method is validated through extensive time- domain and frequency-domain analyses, confirming its ability to reduce voltage fluctuations and enhance grid stability. The three studies advance grid integration technologies by leveraging evolutionary algorithms, advanced control strategies, and AI-driven optimization to improve voltage stability and power quality in weak grids amid renewable energy integration.

The primary objective of this research is to mitigate the negative impacts of active power fluctuations in weak power grids using grid-connected converters (GCCs). Weak grids need more infrastructure and stability measures to accommodate the integration of renewable energy sources, such as high levels of solar photovoltaic power. One of the key challenges encountered in such grids is the absence of inertia from converter-based resources, which can lead to grid instability. This thesis proposes a solution to this challenge by employing power electronics grid-forming converters to synthesize additional inertia and damping properties, effectively emulating the behavior of synchronous generators through the use of virtual synchronous generator (VSG)-based converter control strategies. By incorporating these control strategies, the proposed method aims to overcome the limitations of weak. Integrating high levels of solar photovoltaic power into weak grids can lead to local mode oscillations and grid instability. To tackle this issue, the proposed method focuses on suppressing these oscillations by emulating a virtual damper winding (VDE) within the VSG-based GCC. By incorporating virtual inertia and damping properties, mitigating active power fluctuations and enabling the smooth integration of solar photovoltaic power. A genetic algorithm (GA) optimization tool is introduced to optimize the VSG-based GCC’s performance. This tool allows for the optimization of virtual damping and inertia parameters, enabling the VSG-based converter to effectively adapt to the changing conditions of weak grids. Through comprehensive time-domain and frequency-domain analyses, the proposed method is evaluated, and simulation results validate the effectiveness of the optimization technique and implementation procedure. The validity of the proposed method is further confirmed through simulations conducted in the MATLAB/Simulink environment, which encompass various operating scenarios encountered in weak grids. The thesis provides a comprehensive discussion of the approach, optimization tool, and simulation results, emphasizing the efficacy of the proposed method in addressing the challenges associated with weak grids.

Today, due to the great need for electrical energy and the daily and even hourly increase, the demand for this energy is increasing. On the other hand, the application of laws to reduce greenhouse gases and even the need for more efficiency has caused researchers to use new and smart approaches to produce and consume this energy. One of these approaches is the use of solar energy. In this way, we can produce electrical energy with the help of solar panels, but the problem and challenge, in addition to uncertainty, is that the output voltage of these panels is direct voltage and must be converted to alternating voltage for use. Now, an intermediary must be placed between the electric panels and the consumer or the electric network. With advances in semiconductor elements, this medium was made and used. To produce more energy in this way, these panels and the necessary structure must be connected to each other. By connecting these resources, a small network called a microgrid is produced. These microgrids have received much attention from researchers, people and governments. This is while in order to generate the necessary power through interface converters, we need controllers that can activate the semiconductor elements and direct the generated power through the panels to the loads. In this thesis, using a model-based predictive controller in a microgrid consisting of two distributed generation units that are in parallel and at a distance from each other, we produce a stable and quality voltage to supply non-linear loads connected to the network. In this controller, we need a cost function per unit in order to produce voltage with quality according to global standards. In the algorithm of this controller, all the required restrictions, which affect the output, are given, and this causes the output of the unit to change according to the designer's opinion or the network's needs. In the continuation of the work process, we compared the results of the predictive controller with the traditional controller (Droop). To prove the efficiency of this controller in the considered microgrid, which includes two units with the same controller and specifications, it is implemented in the simulation environment of MATLAB software and you will see the desired response that includes stable voltage and the minimum amount of total harmonic distortion.

Photovoltaic (PV) panels as a renewable energy source have become increasingly vital in addressing global energy challenges and reducing environmental impacts. To optimize the efficiency and performance of photovoltaic systems, accurate modeling and prediction of outputs such as current, voltage and power of the panel or modeling of open circuit voltage, short circuit current, voltage and current at the maximum power point in different environmental conditions is necessary. Is. This thesis presents a research and laboratory study in the field of modeling solar panels using machine learning algorithms, with the aim of increasing the understanding of the behavior of the photovoltaic system with a black box approach. This research begins with a critical evaluation of conventional modeling approaches and reveals their limitations in capturing nonlinear relationships and adapting to dynamic environmental conditions. To overcome these challenges, machine learning appears as a powerful alternative that is able to learn complex patterns from extensive data sets and provide accurate predictions. This thesis examines the simplest different machine learning techniques, including polynomial regression, exponential regression, and neural networks, which are used with two sets of real-world data and one set of synthetic data. They include temperature, radiation and applied load. The effectiveness of these algorithms is evaluated through testing and detailed analysis, focusing on accuracy, the ability to generalize to test data, and validation with real laboratory data. In addition, the quality of the data, especially the excitability, are examined to increase the convergence and strength of the models.

The inevitable influence of renewable energy sources in the production of energy needed by cities and industries and the fact that renewable energy production is the cheapest option for energy supply in the long term, has prompted researchers to develop methods of exploiting various types of energy and Renewable energies, including solar energy, fuel cell, wind energy, etc., should be the target of their research. In the meantime, the variable nature of these energies, in different conditions and times, has caused electronic power converters and their control methods to be highly considered in order to optimize the extraction and exploitation of renewable energies. Considering that the production power of some renewable energy sources is of DC type and also a large part of consumers are fed by DC power, DC micro grids have been of great interest in the past years. Electronic power converters, as an important part of micro grids, are responsible for the transmission and control of power quality. Since the use of these converters increases the initial cost of micro grids, therefore, the use of DC-DC converters in the conditions where the production power and feeding of consumer equipment are both of DC type is economical. In this research, the impedance source DC-DC converter has been introduced due to its advantages over other types of converters, including its use as a buck and boost converter, and then, after modeling the state space of the standard structure of this converter, the ADRC control method has been used to eliminate disturbances to the system and finally provide stable and quality power to the consumer. The simulation results show that the ADRC controller can guarantee the stability and reliability of the impedance source converter in the presence of system disturbances and uncertainties.

ریزشبکه ساختار جدیدی است که با حضور منابع تولیدپراکنده، منجربه بهروزرسانی شبکه برق میشود. قابلیت کار در حالت جزیرهای یکی از مهمترین مزیتهای اساتفاده از ریزشابکهها اسات، زیرا امکان تداوم تامین توان را در زمان بروز اغتشاش در شبکه اصلی فراهم میکند. تسهیم توان یا بهاشترا گذاری توان در ریزشاابکههادر حالت جزیرهای همواره یک نیاز اساااساای محسااوب میشااود، در واقع تسااهیم توان در بین واحدهای تولید پراکنده یکی از مهمترین چالشهای موجود در ریزشبکه است، چرا که عدم تسهیم مناسب توان در میان آنها منجربه تسهیم بار نابرابر میشود که ممکن است در حالت اتصال به شبکه به مصرفکننده و همچنین شبکه آسیب برساند و اغلب منجربه ناپایداری میشود. ت سهیم توان منا سب باعث بهبود عملکرد ریز شبکه و افزایش کنترلپذیری آن در زمان خطا میشود. در ریزشبکههایی که از چندین منبع تولید پراکنده تشکیل شده است، روش کنترل افتی تکنیکی است که برای ت سهیم توان بهصورت گ سترده مورد ا ستفاده قرار میگیرد. کنترل افتی بهفرکانس و ولتاژ اجازه میدهد تا در مقادیر متفاوتی از مقدار مرجع خود ثابت شاااوند و توان اکتیو و راکتیو را در بین منابع تولید پراکنده به اشترا بگذارند، اما در حالی که توان اکتیو بهطور متناسب با مقدار نامی در بین منابع تولید پراکنده تسهیم میشود، ت سهیم توان راکتیو بهدلیل تفاوت در امپدانس خط و امپدانس خروجی اینورترها، به خطا منجر می شود. جهت تسهیم دقیق توان در ریزشبکه ضمن استفاده از روش کنترل افتی، ضروری است به نحوی تفاوت در امپدانس خط و امپدانس خروجی اینورترها کنترل و جبران شود. رویکرد کنترلی پی شنهادی این پژوهش ا ستفاده از حلقههای دینامیک مجازی به عنوان ترمهای ا صالحگر جهت ت سهیم منا سب توان ا ست. ا ستفاده از حلقههای دینامیک مجازی یک روش مناساب جهت بهبود عملکرد روش کنترل افتی معمولی در تساهیم توان اسااات. در این تحقیق ابتدا با اساااتفاده از حلقه امپدانس مجازی تفاوت در امپدانس خط و امپدانس خروجی اینورترها جبران میشود که موجب بهبود تسهیم توان اکتیو و راکتیو میشود، سپس با اعمال حلقه کنترل م جازی به عنوان جایگزین حل قه ام پدانس م جازی ت فاوت در ام پدانس خط و ام پدانس خروجی اینورترها جبران میشاااود و تساااهیم توان اکتیو و راکتیو بهبود مییابد. حلقه کنترل مجازی شاااامل یک جبرانساز پسفاز است که با ایجاد فاز منفی موجب بهبود تسهیم توان میشود.

با توجه به رو به اتمام بودن سوخت های فسیلی و آلودگی های زیست محیطی ایجاد شده در اثر مصرف بی رویه ی این سوخت ها، انرژی های تجدیدپذیر به عنوان جایگزینی پاک و کم هزینه مطرح شده اند. یکی از روش های قابل اطمینان و پرکاربردی که در سال های اخیر برای تزریق منابع انرژی تجدیدپذیر به شبکه های برق، معرفی شده است، تولیدات پراکنده ی دارای اینورتر است. تولیدات پراکنده به غیر از تامین توان در زمان وصلی شبکه اصلی، ملزم به تامین بارهای متصل به خود در حالات قطعی و خطاهای شبکه نیز هستند. بنابراین اینورترهای به کار رفته در تولیدات پراکنده، می بایست توانایی عملکرد در هر دو مد متصل به شبکه و مستقل از شبکه (جزیره ای) را دارا باشند، و به صورت ملایم و یکپارچه میان این مدها گذار کنند. گذار بین این مدها، ممکن است سبب ایجاد اعوجاجات و نوساناتی در سیگنال های ولتاژ و جریان شود. بنابراین، اعمال کنترل کننده مناسب به اینورترهای مورد استفاده در تولیدات پراکنده، جهت به حداقل رساندن این نوسانات و تضمین گذاری ملایم و نرم، از نکات لازم و حائز اهمیت برای عملکرد مناسب و بهینه تولیدات پراکنده است، چرا که اهداف تولیدات پراکنده توسط اینورترها محقق می گردد. روش کنترلی استفاده شده در این پژوهش، کنترل مدل-پیش بین است که از یک تابع هدف واحد، برای دستیابی به اهداف کنترلی در هر چهار مد کاری اینورتر بهره می گیرد. ضمنا"، از یک الگوریتم تشخیص مد کاری و همگام سازی، برای شناسایی مد کاری اینورتر و تنظیم فاز ولتاژ بار بر اساس فاز ولتاژ شبکه، پیش از اتصال به شبکه استفاده می کند. همچنین یک استراتژی خودتنظیم، به تنظیم خودکار وزن های تابع هدف در هر بازه سوئیچینگ می پردازد. نوآوری این پایان نامه، استفاده از اینورتر منبع ولتاژ سه فاز همراه با بار سه فاز می باشد. با توجه به نتایج عددی حاصل، می توان گفت که کنترل کننده ذکر شده با دستیابی به THD اندک و فراجهش جزئی ولتاژ لینک DC، به ویژه در مدهای گذار، توانسته عملکرد مناسب و قابل قبولی را در بهبود پاسخ اینورتر و تضمین گذار ملایم و یکپارچه ایفا کند.

The control community has embraced the use of linear and contemporary controllers in microgrids in recent decades. Two types of controllers with adjustable parameters are integral-proportional (PI) controllers and model predictive controllers (MPC). Regulatory approaches must therefore be applied to these parameters. The application of appropriate methods to achieve seamless transitions between the operating modes of a microgrid, i.e., stand-alone (SA) and grid-connected (GC) operations, is an important aspect of microgrids. Also among the difficult tasks is the extraction of the model of a microgrid with multiple distributed generation (DG) units. This subject serves as the primary basis for this thesis. In addition to these concerns, the use of a unified approach without the need to change the controllers in the microgrid's operating modes, as well as the transition period, is one of the most important implementation and economic concerns. In this thesis, one of the offline data-driven controllers is used to tune the PI and MPC using an iterative feedback tuning approach and the same controller. This thesis focuses on the parameters of these controllers in place of power compensators in order to achieve a seamless transition between the operating modes of a two-unit microgrid. In MATLAB/Simulink, three different scenarios were used to compare the two proposed methods on the studied system

Inverter-based Distributed Generations (DGs) have emerged as an efficient solution for the exploitation of renewable energies. In addition to regular power generation in the grid presence, DG systems must be able to supply local loads during main grid outages. Hence, their inverters should be capable of operating in both grid-connected and islanded modes. These systems operate as current sources for the AC grid in grid-connected mode, and as voltage sources for the load to control its voltage and frequency in islanded mode. The transition between operating modes may distort the voltage or current waveforms because of a frequency, phase, or amplitude mismatch between the inverter output voltage and the grid voltage. Therefore, for a smooth transition without abrupt changes and distortions, a comprehensive control method is required to be applied to inverters. The control strategy proposed in this research, entitled “Hybrid Fuzzy-Predictive Control,” provides the adjustment of the predictive control cost function coefficients intelligently by using fuzzy logic, and has the harmonic distortion rejection capability caused by nonlinear loads. This controller leads to improved inverter behavior in transitions, as well as enhanced dynamic response in steady states. This improvement has been measured using various control criteria in the simulations. In addition to mitigating Total Harmonic Distortion (THD), enhancing steady-state error, and reducing the overshoot/undershoot of the inverter time response, the suggested control method increases the efficiency, and is also robust under the parameteric uncertainties. The innovation of this thesis is combining fuzzy and predictive control methods, and applying the hybrid controller to voltage source inverters used in distributed generations

Increasing the penetration level of distributed generation units as well as power electronic devices increases the complexity and variability of the dynamic behaviour of the micro grids. Micro grids have many challenges, such as being random in their production. As a results, the energy production from distributed generation sources will be constantly fluctuating. Therefore studying the micro grid transient modelling and its signal stability are importance. One of the major disadvantages of most studies on micro grid modelling is their excessive attention to the steady state period and the lack of attention to micro grid performance during the transient period. Also, in most of papers, the behaviour of different micro grid loads has not been studied. One of the mechanisms of power systems stability studies is the application of state space modelling. These stability studies including the development of state space models of various components of the power system and then linearizing them around an equilibrium point. In this paper, a comprehensive method for modelling of islanded inverter-based micro grids with dynamic and static loads is presented. The basic concepts of the proposed method are dq0 transformation and dq0-based models. In order to find a complete and accurate model of islanded inverter-based micro grid, the sub-modules of generation, network and load must be modelled in local dq reference and then transferred to a common reference. The simulation results show the effectiveness of the proposed modelling approach for transient stability studies

Restrictions on fossil fuels and environmental issues have led to the expansion of the use of distributed generation resources. Distributed control is a common method for optimal operation and increasing efficiency and reducing control complexity. Techno-logical advances and communication networks, as well as the availability of high-precision computing resources, enable remote control, operation, and monitoring, make microgrids a physical cyber system. These systems are vulnerable to cyber threats, malware, and viruses. Therefore, security should be considered as a challenge when designing controllers of microgrids. In this research, the threats and vulnerabilities of distributed secondary control in AC microgrids are studied. To improve resilience against cyber attacks in the communica-tion layer, a method based on graph theory and consensus algorithm is proposed. To maintain the stability of the system against attacks, and to increase the self-healing of the system, a robust controller based on Quantitative Feedback Theory is proposed. The results of this study can be used to improve the resilience of distributed systems against cyber attacks.

In recent years, cyber- attacks on communication links became an interesting research topic in various fields. In general, the aim of these attacks is to disrupt the system by corrupt exchange information, sever communication link, etc. Cyber-attacks could occur on different components in cyber-physical-systems e.g., measurement sensors, control and communication links. Distributed control is an attractive alternative to centralized control, however, this control architecture is vulnerable to cyber-attacks due to exchange information between different units. Since cyber-attacks could cause damages in control systems, the resilient control method against them is necessary. In this thesis, firstly the impact of cyber-attacks on current communication links of different secondary control strategies in DC microgrids are studied. Then, resilient control methods against cyber attacks of theses systems are considered. In the first method, an PI controller with an adjustable gain is employed to eliminate the impact of FDI attack on the communication links. A fuzzy based resilient secondary controller is then proposed to cope with all the well-known cyber attacks in DC microgrids. In this method, the communication weights of the Consensus protocol of the distributed secondary controls of units are adjusted through a fuzzy controller. A DC microgrid test system is employed to verify the proposed methods using numerical simulations.

Traditional centralized power generation has recently lost its attraction due to increasing concerns about environmental pollution and the fossil energy crisis. Distributed generation (DG) may be a promising alternative as it can facilitate the interconnection of renewable energy sources (RESs), such as photovoltaics, wind turbines and hydropower. To increase the reliability, flexibility, power quality and intelligence of DG system, several DG units, together with loads and energy storage systems (ESSs), are integrated into a single controllable entity, known as microgrid. Renewable energy sources are usually connected to a point of common couplling through electronic power based interfaces such as inverters. One of the main problems of these electronic power converters is the creation of voltage harmonics along with nonlinear loads. Therefore, coordinated control of parallel inverters and voltage quality play an essential role in the strong performance of microgrids. In this thesis, the load and/or grid connected to an inverter is modeled as the combination of voltage sources and current sources at harmonic frequencies. As a result, the system can be analyzed at each individual frequency, which avoids the difficulty in defining the reactive power for a system with different frequencies because it is now defined at each individual frequency. Moreover, a droop control strategy is developed for systems delivering power to a constant current source, instead of a constant voltage source. This is then applied to develop a harmonic virtual synchronous generator controller so that the right amount of harmonic voltage is added to the inverter reference voltage to compensate the harmonic voltage dropped on the output impedance due to the harmonic current. This forces the output voltage at the individual harmonic frequency to be close to zero and improves the total harmonic distortion (THD) of the output voltage considerably. To evaluate the effectiveness of its performance, it is compared with a droop controller. MATLAB software is used in SimPowerSystems to evaluate the performance of controllers.

Nowadays, microgrids (MGs) have been introduced as new structures of electrical power systems. These structures include a number of distributed generation units (DGUs), loads, and energy storage systems, which can be operated in either interconnected mode, grid-connected mode, or islanded mode. To appropriate control of these systems hierarchical controls have been proposed, where primary control has to keep the voltage and frequency stability of units, and the secondary control (SC) is focused on power quality issues and voltage and frequency restoration considering appropriate power sharing among units. Communication infrastructure (CI) in microgrids (MGs) allows the application of different control architectures for the secondary control (SC) layer. The use of new SC architectures involving CI is motivated by the need to increase MG resilience and handle the intermittent nature of distributed generation units. The structure of SC is classified into three main categories, including centralized SC (CSC) with a CI, distributed SC (DISC) generally with a low-data-rate CI, and decentralized SC (DESC) with communication-free infrastructure. To meet the MGs’ operational constraints and optimal performance, control and communication must be utilized simultaneously in different control layers. In this thesis, first, we review and classify all types of SC policies from CI-based methods to communication-free policies, including CSC, averaging-based DISC, consensus-based DISC methods, containment pinning consensus, event-triggered DISC, washoutfilter-based DESC, and state-estimationbased DESC. Each structure is scrutinized from the viewpoint of the relevant literature. Challenges such as clock drifts, cyber-security threats, and the advantage of event-triggered approaches are presented. Fully decentralized approaches based on state-estimation and observation methods are also addressed. Although these approaches eliminate the need of any CI for the voltage and frequency restoration, during black start process or other functionalities related to the tertiary layer, a CI is required. Then, a decentralized optimal secondary controller for frequency regulation and accurate active power sharing in autonomous microgrids is presented. This optimal controller does not require any communication network. Unlike most of the existing works, a systematic approach of secondary controller design is introduced based on a quadratic cost function in the form of a linear quadratic regulator (LQR) problem. The design procedure only depends on the cut-off frequency of the power calculation filter. Decentralized behavior, simplicity, optimality based on a quadratic cost function, and straight forward design procedure are the main advantages of this approach. Finally, a decentralized SC based on the active power estimation (APE) is presented, as well. This achievement is realized by employing the unique feature of frequency as a global variable in autonomous AC MGs. The APE is merely based on the droop coefficient of P −ω characteristics. The decentralized SC, utilizing a consensus protocol, restores the MG frequency to the nominal value while maintaining accurate power-sharing of the droop mechanism. The consensus protocol is estimation-based and does not require communication infrastructure. In addition to the proposition of stability analysis method, experimental results with four distributed generation units (DGUs) also verify the effectiveness of the proposed SC structures.

In dc MGs, the distributed sources, energy storage systems and loads with different electrical characteristics are typically interconnected to the main bus through power electronic converters. The existence of interfaced converters creates two major problems: 1) the load-side converters and their associated loads, usually considered as constant power loads (CPLs), introduce destabilizing effects into the system, 2) the source-side converters do not possess any inertia or damping properties but reducing the overall inertia of the system. In this thesis, modeling and stability analysis of low inertia dc MG loaded by CPLs have attracted attention and their operating performance are improved by using the concept of controlled power source and virtual inertia in ac MGs dynamic response. The controlled power source consists of three fundamental components: energy storage system, bidirectional interfaced converter, and proper control mechanism. Thus, each component is considered as a useful solution to improve the dynamic response of the system. For energy storage unit, a supercapacitor is proposed due to the high power density and fast dynamic response. The proposed control scheme is composed of a virtual inertia and a virtual damping. It is implemented in the inner current control loop. The proposed virtual inertia is implemented in series with the derivative feedback of output voltage that decreases the rate of change of voltage immediately after disturbance. Furthermore, the proposed virtual damping decreases negative impact of CPLs on stability by improving damping ratio. The proposed control scheme is not dependent on structure of the intrfaced converter and its performance has been tested on buck and boost converters. In order to study the stability of dc MG with CPLs, a comprehensive smallsignal model of sources, interfaced converters, control system and loads are derived by using state space averaging. The effect of proposed control parameters on stability are investigated and an acceptable range of inertia response parameters is determined by using the system’s root locus analysis. The required modeling and simulations are done in Simulink and SimPowerSystems environments of MATLAB software.

In recent years, DC microgrids have received special attention due to their easier control, increasing renewable energy sources with DC output and increasing DC loads. Renewable energy sources are often either no inertia or low inertia; however, DC microgrids in the island state (lack of main grid support) and high penetration of renewable energy sources have very low inertia, which in turn drives and fluctuates. To address this problem, the concept of virtual inertia has recently been introduced. In this study, a virtual controller was used to improve the dynamics of a DC microgrid. A virtual inertial controller is introduced as a virtual controller based on the concept of a virtual synchronous machine. The virtual controller is implemented with a built-in controller and a secondary controller in a buck converter. To optimize the robust performance of the microgrid against perturbations and uncertainties, a new approach based on 𝐻∞ robust control is proposed. In the proposed solution, a small 𝐻∞ robust controller is designed instead of a virtual controller with the help of a small signal network model. Then, the virtual controller parameters are determined based on a proposed algorithm. In the following, the simulated DC microgrid is simulated in Simulink / MATLAB software. Then, to evaluate the performance and performance of the proposed solution, the network underwent various tests. The simulation results not only show the robust and optimal performance of the network in the presence of uncertainties, but also determine the efficiency and flexibility of the virtual controller to improve the inertia and dynamics of the network.

Nowadays, Electrical Microgrids are known as a group of most important players of smart grids, which in the AC, DC, and hybrid types are studied, experimentally implemented, and operated in real cases. These active distribution grids that are formed from a set of distributed generation units and electrical consumers, can be operated in the main grid-connected and isolated/islanded modes. So far, these two operation modes have been taken into account in different aspects, i.e. stability, control, protection, planning and operation. In recent years, the interconnected microgrids as a new operation mode is taken into account. It can be resulted in improvement of generation and consumption felxibility, reliability resiliency, penetration increase of renewable energy sources and load shedding decrease. Although, the mentioned adventages are claimed in the valid references and can intuitively be proved, they should be studied in detail and their challenges should be eliminated. Connecting several relatively extensive systems causes a large scale system, which the modeling method and the analysis of the impact of each component on the system stability and control is an important challenge to be researched. Therefore, In this thesis, modeling, stability analysis, and improvement of interconnected AC microgrids is payed attention. Two types of the interface devices of AC microgrids are considered including circuit breakers and back-to-back converters. Both groups of interconnected AC microgrids through these interface devices are modeled and their small-signal stability is analyzed. Moreover, the reduced-order linear models are proposed using perturbation and aggregation methods in otder to analyze the stability of dominant low-frequency modes and study frequency response. The acceptable ranges for the most important parameters of the microgrids and interfaces to stabilize the system interconnected microgrids are calculated using eigenvalue analysis, participation matrix and sensitivity analysis. Furthermore, the transient stability of the studied system is assessed, which results in limiting the DC link voltage in the case of back-to-back converters. Finally, a generalized droop controller embedded with logical functions is proposed to improve the performance of the interconnected microgrids in the emergency condition. The required modeling and simulations are done in Editor, Simulink and SimPowerSystems environments of MATLAB software, as well as real time in OPAL-RT digital simulator.

زیرساخت های شبکه هوشمند الکتریکی (SG ) به عنوان یک شبکه ارتباطی و توزیع شده در یک منطقه جغرافیایی وسیع به راحتی قابل دسترس هستند. این امر سبب به وجود آمدن آسیب پذیری های امنیتی جدیدی به واسطه وجود تکنولوژی های توزیع شده در شبکه هوشمند می شود. به نحوی که رویکردهای معمولی مانند آنتی ویروس ها و فایروال ها قادر به فراهم سازی امنیت کامل نیستند. بنابراین جهت دستیابی به یک شبکه هوشمند کارآمد، این شبکه ها نیازمند سیستم های امنیتی جدیدی هستند که ضمن رفع نمودن نواقص امنیتی موجود قادر به فراهم نمودن امنیتی پایدار در مقابل حملات احتمالی باشند. امروزه سیستم های تشخیص نفوذ به عنوان یکی از مکانیزم های اصلی در فراهم کردن امنیت شبکه ها مطرح هستند. این سیستم ها می توانند فعالیت های شبکه را بصورت پیوسته تحت نظارت و سنجش قرار داده و فعالیت های غیرعادی که مربوط به حملات می باشند را در اسرع وقت شناسایی کنند. در این پایان نامه یک نمونه سیستم تشخیص نفوذ مبتنی بر مشخصات رفتاری شبکه ارائه می گردد. جهت طراحی این سیستم ابتدا لیستی از مشخصات و قواعد رفتاری شبکه هوشمند در قالب مشخصات رفتاری ریزشبکه ها تهیه می شود سپس براساس این مشخصات وضعیت های امن شبکه توسط بردار حالت مدلسازی شده و با استفاده از تکنیک آماری آزمون فرض آشکارسازی نفوذ انجام می گیرد. سیستم های تشخیص نفوذ عموماً با دو پارامتر مهم نرخ اعلان اشتباه و نرخ عدم تشخیص نفوذ مواجه هستند. این پایان نامه براساس این دو پارامتر به بهینه سازی مسئله تشخیص نفوذ پرداخته و فضای آماری آزمون فرض را براساس مناسب ترین مقدار حد آستانه بدست آمده ناحیه بندی می کند. نتایج عددی کارآمدی مدل پیشنهادی را به عنوان گامی مهم در جهت طراحی یک سیستم تشخیص نفوذ کامل و ارتقاء امنیت شبکه نشان می دهد.

Concerns about environmental pollution, climate change and declining fossil fuels have increased the need for renewable energy around the world. One of the best uses of renewable resources is the concept of microgrid. A microgrid is a small scale of the power grid that includes renewable energy sources, energy storage sources, and loads that are interconnected. The advancement of power electronic interfaces such as AC / DC and DC / AC in recent decades, and their flexibility in transmitting electrical energy, has led to a desire to design and use more microgrid systems. Power electronic converters and electric motor actuators, which are the main components of DC microgrids, will behave like a constant power load when needed to be tuned precisely. This type of load has a negative impedance characteristic at the input terminal that affects the stability of the system and the quality of the control system. This effect is more pronounced in the case of island microgrids and may even cause system instability; Therefore, the existence of this type of load in DC microgrid is considered as a challenge. In this dissertation, we first model and analyze the stability of a DC microgrid, including a distributed generation unit (DG) that provides the power required for a fixed power load. Then, due to the high penetration of this type of load in DC microgrid and the issue of instability in them, an optimal nonlinear controller, using the state dependent Riccati equation method (SDRE), is presented for the DC bus voltage tracking problem, and compared with other methods. Then, to study the power transmission in these types of systems, the study system is developed and a droop-based model predictive controller (DMPC) is designed to compare its performance efficiency and compared with normal droop control. Simpower/Matlab software is used to evaluate performance and designed controllers. The simulation results for the studied system are given at the end of each chapter.