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DESIGN AND OPERATION OF DC MICROGRID FOR INTEGRATION OF HYBRID RENEWABLE POWER SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR AWARD OF DEGREE OF MASTER OF TECHNOLOGY (POWER SYSTEM) SUBMITTED BY NATASHA M...

DESIGN AND OPERATION OF DC MICROGRID FOR INTEGRATION OF HYBRID RENEWABLE POWER SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR AWARD OF DEGREE OF MASTER OF TECHNOLOGY (POWER SYSTEM) SUBMITTED BY NATASHA MAHAJAN University Roll No.: 1908605 UNDER THE ESTEEMED GUIDANCE OF Dr. Vibhuti Head of Department July, 2024 I.K. GUJRAL PUNJAB TECHNICAL UNIVERSITY JALANDHAR (PUNJAB), INDIA SRI SAI COLLEGE OF ENGINEERING & TECHNOLOGY, BADHANI  CANDIDATE'S DECLARATION CERTIFICATE I hereby certify that the work which is being presented in this Thesis, entitled “Design And Operation of DC Microgrid for Integration of Hybrid Renewable Power” by NATASHA MAHAJAN in partial fulfillment requirement for the award of degree of M. Tech. (Power System) submitted in the Department of Electrical Engineering at Sri Sai College of Engineering & Technology Badhani, Pathankot under IK Gujral Punjab Technical University, Jalandhar is an authentic record of my own thesis work carried out under the supervision of Dr. VIBHUTI, Head of Department. The matter presented in this thesis has not been submitted by me in any other University/Institute for the award of M. Tech. Degree. NATASHA MAHAJAN Roll No.: 1908605 This is to certify that the above statement made by the candidate is correct to the best of my knowledge. Guide: Dr. Vibhuti Dr. Vibhuti Head of Department Head of Department Department of Electrical Engg. Department of Electrical Engg. Sri Sai College of Engg. & Tech. Sri Sai College of Engg. & Tech. Badhani, Pathankot Badhani, Pathankot The M.Tech. Viva-Voce Examination of Natasha Mahajan has been held on and is accepted. Signature of Guide Signature of External Examiner Signature of H.O.D i  ACKNOWLEDGEMENT While bringing out this thesis to its final form, I came across a number of people whose contributions in various ways helped my field of research and they deserve special thanks. It is a pleasure to convey my gratitude to all of them. First and foremost, I would like to express my deep sense of gratitude and indebtedness to my supervisor Dr. Vibhuti, Head of Department, Electrical Engineering Department at Sri Sai College of Engineering & Technology Badhani, Pathankot for her invaluable encouragement, suggestions and support from an early stage of this research and providing me extraordinary experiences throughout the work. Above all, her priceless and meticulous supervision at eachand every phase of work inspired me in innumerable ways. Her expertise and encouragement helped me to complete this research paper and write this thesis. I specially acknowledge her for her advice, supervision, and the vital contribution as and when required during this research. Her involvement with originality has triggered and nourished my intellectual maturity that will help me for a long time to come. I am proud to record that I had the opportunity to work with an exceptionally experienced Professor like her. I am grateful to Dr. VIPIN GUPTA, principal, for providing me with the opportunity to conduct my research at Sri Sai College of Engineering & Technology Badhani, Pathankot, and for all of the resources and support they provided. Finally, I am deeply indebted to my mother, Mrs. Sarita Gupta, my father, Mr. Rakesh Chander Gupta, my elder brother, Rahil Mahajan, and to my other family members for their moral support and continuous encouragement while carrying out this study. Without them, this journey would not have been possible. Lastly, I would like to thank all of the participants in my study for their time and willingness to share their experiences. This work would not have been possible without their contribution. NATASHA MAHAJAN ROLL NO: - 1908605 ii  ABSTRACT The increasing demand for clean and sustainable energy solutions, the concept of microgrids has gained significant attention in recent years. A microgrid is a localized power distribution system that can operate independently or in conjunction with the main grid, enabling the integration of renewable energy sources, energy storage, and advanced control techniques. Among various types of microgrids, Direct Current (DC) microgrids have emerged as a promising alternative to traditional Alternating Current (AC) grids, offering numerous advantages in terms of efficiency, reliability, and resilience. Unlike conventional AC grids, which rely on alternating current for power transmission and distribution, DC microgrids utilize direct current. This shift from AC to DC power distribution brings several benefits. This study presents a comprehensive analysis of the performance and benefits of DC microgrids as a sustainable and efficient solution for power distribution. The research begins by formulating the problem, identifying the challenges, and defining the objectives. The methodology involves designing and simulating the Photovoltaic (PV) system and wind farm to capture maximum power output. To analyze the performance of the microgrid during fault occurrences, different fault scenarios are simulated on the AC grid section. The behavior of the microgrid under these fault conditions is studied, and the response of the PV and wind sources, as well as the energy storage system, is evaluated. To achieve this, a simulation model was developed using MATLAB/Simulink to assess the performance of the DC microgrid system under different scenarios. The simulations demonstrate that the combined power generated by PV panels and wind turbines in the DC microgrid reaches approximately 10 kW, showcasing their capacity to provide a consistent and reliable power supply. The findings reveal that the DC microgrid effectively utilizes renewable energy sources to supply power to the load, while the AC grid provides backup power during fault situations. The energy storage system plays a crucial role in managing power fluctuations and stabilizing the grid. The integration of various power sources and control algorithms ensures a reliable and efficient power distribution system. In addition to power generation, the simulations also consider the response of the DC microgrid system to fault scenarios occurring in the AC grid. The results reveal that the DC microgrid exhibits seamless transitions and achieves a fast recovery time of 0.1 to 0.15 seconds. iii  TABLE OF CONTENTS Title Candidate’s Declaration Certificate i Acknowledgement ii Abstract iii Table of Contents iv-v List of Abbreviations vi List of Figures vii-ix List of Tables x Chapter 1: Introduction 1-10 1.1 Introduction 1-2 1.2 Dc Microgrid Systems 2-5 1.3 Constant Power Loads in Microgrids 5 1.4 Protection Strategy for Dc Microgrid 6-7 1.5 Dc Microgrid Control Strategies 7-10 Chapter 2: Literature Review 11-24 2.1 Literature Survey 11-24 Chapter 3: Problem Formulation and Objectives 25-27 3.1 Problem formulation 25-26 3.2 Problem Statement 27 3.3 Objectives 27 Chapter4: Methodology 28-32 4.1 Introduction 28 iv 4.2 Methodology 28-32 Chapter 5: Results and Discussions 33-53 5.1 Introduction 33 5.2 Analysis of Fault with Grid and PV Based DC-Microgrid 33-41 5.3 Analysis of Fault with Grid and Wind Farm Based DC-Microgrid 41-49 5.4 Analysis of DC-Microgrid with PV, Wind and AC Source 49-53 5.5 Summary 53 Chapter 6: Conclusions And Future Scope 54-55 6.1 Conclusions 54 6.2 Future Scope 55 References 56-65 List of Publications 66 v  LIST OF ABBREVIATIONS PV Photo voltaic MG Microgrid DGS Distributed generation system LV Low voltage MV Medium voltage ESS Energy storage system LVDC Low voltage distribution system CPL Constant power loads CVL Constant voltage loads LQR Linear-quadratic regulator PID Proportional integral derivative BESS Battery energy storage systems MPPT Maximum power point tracking AC Alternating Current DC Direct Current vi  LIST OF FIGURES Page No Figure 1.1 Typical configuration of a conventional DC microgrid. 3 Figure 1.2 DC micro-grids' protection issues and solutions. 6 Figure 1.3 Hierarchical control layers of a microgrid. 8 Figure 1.4 Hierarchical control architecture. 9 Figure 1.5 Three DC microgrid control methods. 10 Figure 4.1 DC-microgrid designed using MATLAB/Simulink. 29 Figure 4.2 Designed PV system in MATLAB/Simulink. 31 Figure 4.3 Wind farm model designed in MATLAB/Simulink. 32 Figure 4.4 Designed storage system for dc-microgrid. 32 Figure 5.1 Irradiance of the PV plant started at t=0 sec. 34 Figure 5.2 Power delivered to load by PV plant. 34 Figure 5.3 Output from ac-grid from t =0 to t=1 sec. 35 Figure 5.4 Irradiance of the PV plant started at t=1 sec. 35 Figure 5.5 Combined power delivered to load by ac-grid (from t=0 to 36 t=1 sec) and PV plant (from t=1 to t=5 sec). Figure 5.6 Output from ac-grid from t =0 to t=2 sec. 36 Figure 5.7 Irradiance of the PV plant started at t=2 sec. 37 Figure 5.8 Combined power delivered to load by ac-grid (from t=0 to 37 t=2 sec) and PV plant (from t=2 to t=5 sec). vii Figure 5.9 Output from ac-grid from t =0 to t=3 sec. 38 Figure 5.10 Irradiance of the PV plant started at t=3 sec. 38 Figure 5.11 Combined power delivered to load by ac-grid (from t=0 to 39 t=3 sec) and PV plant (from t=3 to t=5 sec). Figure 5.12 Output from ac-grid from t =0 to t=4 sec. 39 Figure 5.13 Irradiance of the PV plant started at t=4 sec. 40 Figure 5.14 Combined power delivered to load by ac-grid (from t=0 to 40 t=4 sec) and PV plant (from t=4 to t=5 sec). Figure 5.15 Wind speed profile from t=0 to t=5 sec. 42 Figure 5.16 Power delivered to load by wind farm (from t =0 to t=5 42 sec). Figure 5.17 Output from ac-grid from t =0 to t=1 sec. 43 Figure 5.18 Wind speed profile from t=1 to t=5 sec. 43 Figure 5.19 Combined power delivered to load by ac- grid (from t=0 to 44 t=1 sec) and wind farm (from t=1 to t=5 sec). Figure 5.20 Output from ac grid from t=0 to t=2 sec. 44 Figure 5.21 Wind speed profile from t=2 to t=5 sec. 45 Figure 5.22 Combined power delivered to load by ac-grid (from t=0 to 45 t=2 sec) and wind farm (from t=2 to t=5 sec). Figure 5.23 Output from ac-grid from t =0 to t= 3 sec. 46 Figure 5.24 Wind speed profile from t = 3 to t = 5 sec. 46 Figure 5.25 Combined power delivered to load by ac-grid (from t=0 to 47 viii  t=3 sec) and wind farm (from t=3 to t=5 sec). Figure 5.26 Output from ac-grid from t =0 to t= 4 sec. 47 Figure 5.27 Wind speed profile from t = 4 to t = 5 sec. 48 Figure 5.28 Combined power delivered to load by ac-grid (from t= 0 to 48 t=4 sec) and wind farm (from t=4 to t=5 sec). Figure 5.29 Three phase output from the grid. 50 Figure 5.30 Irradiance intensity input to PV panel. 50 Figure 5.31 Power output profile of PV plant. 51 Figure 5.32 Nominal excitation applied to wind farm. 51 Figure5.33 SOC of the batteries. 52 Figure 5.34 Bus voltage profile during complete simulation time. 52 Figure 5.35 Power delivered to load connected to the system. 53 ix  LIST OF TABLES Table 1.1 Few common example of DC micro-grid in practice 4 Table 5.1 Response of dc-microgrid with PV source and fault at 41 ac-grid section. Table 5.2 Response of dc-microgrid with wind farm source and 49 fault at ac-grid section. x  CHAPTER 1 INTRODUCTION 1.1 Introduction Due to its advantages over conventional Alternating Current (AC) systems for distributing power according to power density, Direct Current (DC) power distribution systems, and power distribution effectiveness, also known as DC micro- grids, are of great interest for a variety of power applications. Alternatively, short- circuit flaws in these systems pose serious risks. Due to the nonappearance of ordinary crossing zero of DC current, it is challenging to extinguish these arc faults with standard circuit breakers. Additionally, DC breakers are often more expensive and larger. Today, these systems' failure protection, to the magnitude that it even exists, is dependent on data networks, excess current timeout limitations in power converters, or dedicated circuit breakers that trip through overcurrent or distance relays. More reliable, completely distributed, communication-independent techniques are required. Interest in distributed generating systems using photovoltaic energy (solar and thermal), wind, biomass, mini-hydro, as well as use of fuel cells and micro turbines, has significantly increased in recent years. Due to the significant benefits they can offer, they are now accepted methods for reducing environmental pollution, addressing long-distance transmission issues, providing uninterruptible power, meeting high loads that occur suddenly and enhancing equipment performance. However, using Distributed Generation System (DGS) on a large scale has some drawbacks, a hefty price for single generation access, for instance and making it is more difficult to control. When DGS has a consequence on system energy and frequency from the grid point, such as the grid must shut down when it is separated since the other of the power system to craft a localised system powered by DGS. The advantages and potential of DGS are further undermined by the requirement for DGS to leave the system quickly in the event of accidental incidents. The idea of microgrid is introduced to resolve the conflict between the system and DGS [1–5]. A network of scattered energy resources, loads, and distribution network elements that may function in either grid linked or islanded approaches that are coordinated and managed inside undoubtedly defined geographic confines is known 1 as a micro-grid (MG). The key advantages of adopting a microgrid include expanding the supply of renewable energy, enhancing system independence/security, and boosting dependability [1-2, 6]. The distributed generation and controllable loads that could be linked to the average voltage grid or operated in a meticulous, synchronized manner on an island were all factors that were being taken into account when the MG concept was first anticipated in 2002 as a basis for the development of forthcoming low-voltage distribution systems. MG was founded on the concept of combining several micro sources and loads into a single distinct object, it might be considered one dispatchable consumer in the context of the overhead power system. In addition, it provides utilities, society, and end users with a number of benefits, including: 1. Enhanced energy effectiveness 2. Decreased total energy use 3. Decreased emissions of greenhouse gases and other pollutants 4. Enhanced dependability and quality of service 5. Cost-effective replacement of the electrical infrastructure. Microgrids clearly benefit end users, utilities, and society in terms of the economy and ecology, but implementing them presents significant technological difficulties, such as microgrid protection. Recently, hybrid MGs with both AC and DC MGs have been projected for a diversity of applications [11–16]. Research on DC MGs has recently increased to help with the integration of modern electronic loads and unconventional energy sources with dc output types, such as fuel cells, photovoltaic (PV) systems, and energy storages (such as lesser batteries and super-capacitors), while ac MGs have received the majority of the attention [16–17]. 1.2 DC Microgrid Systems Significant energy savings may be realised by connecting sources of DC electricity and DC loads directly, avoiding employing a DC power distribution system and converting DC-AC-DC energy, given the usage of the most energy-efficient electric 2 appliances, which operate internally on DC [7–12, 16–17]. This distribution strategy offers a more dependable and efficient energy transfer than traditional AC, it has been shown. The adoption of diverse DC power distribution systems is increasing as a result of these and other advantages including avoiding issues with harmonics, unhinges, synchronisation, and reactive power flows. As a result, DC-internal loads including electric vehicles, efficient DC motors, business data centres, fluorescent and Light Emitting Diode (LED) lighting systems, and all consumer gadgets will endure to grow quickly in both home and salable applications. A number of DC-DC converters are present in the typical DC micro-grid shown in Figure 1.1 in order to supply the necessary voltage level for all connected DC loads. The absence of reactive power and harmonics in this system, as one may anticipate, results in greater power quality and system efficiency [7, 12, 16–17]. Figure 1.1: Typical configuration of a conventional DC microgrid Any MG can be operated in either a grid-connected mode or an islanding (standalone) mode, and the details of each of these two MG operation modes are provided below: It's in "On- grid mode" when it's connected to the utility system, also referred to as "grid-connected mode." Depending on the location and overall capabilities of the installed DG units, the MG is frequently connected in this fashion to the major medium voltage (MV), such as 11-66 kV, or low voltage (LV), such as 3 110-690 V grids. It supplies the main utility with some electricity, either directly or indirectly, and uses that electricity to power the nearby loads. Additionally, the main functions of DG units in micro-grid systems are to provide local and power support as well as electricity generation. By directing the creation of regulated active and reactive powers in MGs utilizing interface power converters such DC/DC and DC/AC converters, the controller may direct the reference values of each DG unit. A few DG units, like those found in wind turbines and solar panel arrays, can also be controlled to generate their MPP. The utility is immediately severed from the MG. upon the onset of a failure and its associated switching events and provides it loads locally. In this instance, the MG is operating independently in a manner similar to physical islands when it is cut off from the main network. This mode is sometimes referred to as "Off-grid mode" or "islanding mode." If the electricity produced by the DGs of the MG is inadequate to supply all of its local demands during islanding, load shedding may be used [28–30]. Table 1.1 provides examples of common DC MG systems that are used for most data centre's or critical load applications, or are utilized as testing prototypes. TABLE 1.1 A Few Common Example of DC micro-grid in Practice A DC micro-grid can utilise a single cable (monopolar dc link), two cables (bipolar dc link), or even three cables (homopolar dc link) to transport electricity from the primary utility, distributed generation (DG) units, and energy storage systems (ESSs) through a shared DC distribution line. Low voltage distribution systems (LVDC network) often use the homopolar configuration, but High Voltage (HVDC) long- distance transmission networks frequently use the first two variations [2–3]. Any MG essential function in grid connected and islanded mode without endangering grid 4 dependability, voltage and frequency stability, or shield structures, reliable with the slight criteria for all associated devices, in order to evade any potential procedural issues such as power, and energy equilibrium, power quality, or safety issues. 1.3 Constant Power Loads in Microgrids Technology development has increased the use of power electronics devices, which has led to a sharp rise in constant power loads (CPLs), which has a greater electrical system integrity is affected., particularly micro-grid systems, a type of distributed energy system. The majority of micro-grid systems place their loads on the generating side. For the reason the supervision of load-associated protection is essential to a micro-grid system, we choose load side compensation. Additionally, It is point load correction to compensate for load side effects, meaning we can achieve it at the precise point we want. Controllable loads and critical loads are two different forms of micro-grid loads that may be categorized. Recharging stations for electric vehicles, heat pumps, and other manageable loads as well as data centre's and falling security measures under the type of crucial loads. For improved performance, critical loads that include steady voltage loads as well as steady power loads must get the appropriate attention. The good form of compensation for maintaining system integrity is to manage such sensitive loads viewed from the load side. In micro-grid applications, using load side compensation of Constant Power Load (CPLs) instability brought on by the coupling of CPLs and Constant Voltage Load (CVLs) is a useful approach. Additionally, by using this technique, we can manage the voltage collapse phenomenon of all CPLs by combining them into a single branch. In that situation, we just make up the difference where it is necessary. Additionally, the microgrid bus/feeder is made up of a number of intermittent sources with a constant voltage/generation mismatch. Therefore, providing reimbursement from the feeder side or using intermediate circuitry is relatively difficult and expensive. The suggested system must take these disturbances into account if we combine these compensatory methods on feeder side or intermediary circuitry. The further benefit of load side compensation arrangements over feeder side or intermediary circuitry type arrangements is that they may be made portable. 5 1.4 Protection Strategy for DC Microgrid In addition to earth fault prevention, integrated over-current and short-circuit protection also covers DC Micro Grid (MG) failures. In addition, moulded cases with DC circuit breakers, which are less expensive than fuses and over-current relays, can be utilised to offer the DC MG short-circuit shield shown in Figure 1.2. The breaker guards alongside power converter switching problems on the AC side. There are two different failure kinds in a DC system. There are dual sorts of faults: line-to- ground fault and line-to-line fault. The fault current route in a line-to-ground fault is either between a downward line and the ground or a downward line and a negative line. Between the positive line and the negative line, Line-to-line error is present. Additionally, since a DC circuit lacks a natural "current zero," There must be a way to zero out the current in the switch. To build an appropriate a DC system's grounding, two opposing objectives must be met: i.e., minimising the DC current; and increasing people security by minimising the voltage in the common mode Consequently, at the same voltage and current, the contacts are under more stress in a DC switch than an AC one. Other uses necessitate construction of unique DC breakers, except in rare instances where it is conceivable to utilise an overvalued DC-based AC circuit breaker circuits. Additionally, because to the low DC impedance in DC systems, DC faults levels are quite high. Figure 1.2: DC micro-grids' protection issues and solutions 6 According to Figure 1.2, increasing grid stability is the aim of grid compliance. One such criterion is the Low Voltage Ride Through (LVRT) capability, or the power plant's capacity to maintain grid connectivity by actively supplying reactive power up until fault clearance, during voltage decreases, and to a power system's stability. The coordination of the protective relays may be endangered by the use of reactive power during a grid failure. Alternatives for Micro-grid Protection Plans as shown in Figure. 1.2, given that a few ways to increase the security and safety capabilities of micro-grids [53-54]. Following is a brief explanation of each of the solutions listed in Figure. 2  Adaptive Protection: Existing overcurrent relays should offer the necessary sensitivity and selectivity due to the varying fault levels during off-grid and on-grid modes.  Current Limiting: To prevent equipment damage and safety concerns, current limiting is necessary.  Virtual Impedance: In addition to aiding in the regulation of power flow, virtual impedance has the ability to smooth out harmonics, create an intended dynamic, and allow for ride-through of errors.  Fault Current Limiter: During a fault condition, the DG shall remain connected to the grid in accordance with the LVRT criteria.  To satisfy the needs for the smart grid, a promising islanding detection approach is needed.  Standardisation: The implementation calls for highly dependable, affordable, and quick communication standards as well as utility codes. 1.5 DC Microgrid Control Strategies The use of advanced control techniques is essential for micro-grids. There are various control techniques available to achieve this purpose. A linear control is the most often used control method. Its popularity has grown as a result of its reliability and simplicity. In contrast, linear control, as the name implies, takes into account an operational point-centered linear model. This suggests that the operational point is the 7 sole region where the simplified model is applicable. There are several methods regarding linear control in micro-grids. For instance include either transfer coefficients or state space modelling, in which the allocation of poles using the State feedback, the linear quadratic regulator, and comparative integral derivative are also viable solutions. The system's entire model serves as the foundation for nonlinear control method, on the other hand. It follows that the nonlinear operation dynamics are taken into account. The more true-to-life grid modelling and the fact that not a model constrained to run in a circle around the operational point are advantages of nonlinear control method. Even so, a disadvantage a nonlinear control approach is the complicated evaluation and challenging control legislation implementation. Hierarchical control at several layers is developed to make sure the microgrid is properly controlled. A assured amount of unconventionality among various control levels is provided by these control layers. Additionally, there are numerous control layers the benefit of being more trustworthy because they continue to function even in the event that the centralised control layer fails. Figure 1.3 depicts the three layers used in hierarchical micro-grid control. Figure1.3: Hierarchical control layers of a microgrid 8 For current, voltage, and power sharing, conventional hierarchical control systems are suggested. Figure 1.4 depicts the categorized control architecture, which includes the primary, secondary, and tertiary control levels. The system's reaction time is determined by the bandwidth. It is a gauge of how long it takes to react to a command change in input. The graph demonstrates that primary control has the quickest response time compared to tertiary control, which takes the longest to react to a change in system variables. Figure 1.4: Hierarchical control architecture The bottom rung of the control hierarch, or primary control, is sometimes mentioned to as indigenous control or internal control and includes the fastest reaction. A few seconds are the time frame in which this control layer functions. When a disturbance affects The primary control layer is in care of managing the current and voltage in the microgrid in mandate to adjust the operating points of the grid while the secondary controller computes the new set of optimal operation values. The power quality is under secondary control. This suggests the ideal power flow to maintain system power balance. Each power source in the network has its power; there are three different techniques to implement the secondary control layer generation controlled by this control layer, as illustrated in Figure 1.5, from a communication-based approach. 9  Figure 1.5: Three DC microgrid control methods No necessity for communication in decentralised control. This control method solely defines its control actions using measurable local information. As a result, all Distributed Generation Unit (DGUs) are independent of one another and communication, enabling parallel operation. All sensor data, such as micro-grid statuses, is transferred in centralised control from the DGUs to a central controller Micro grid Central Controller (MGCC). All of the incoming data is processed by this central controller, which then transmits control actions back. Since the central controller has real-time information about every power source, the microgrid can perform as well as it possibly can. The controls depend on the communication network's dependability, which is a disadvantage. There is no need for a centralised controller in dispersed control. To perform at their best, DGUs only share their states with their immediate neighbours. The principal advantage of this method is that a DGU solely depends on communication with its neighbours. Therefore, provided that the communication network is active, the system can endure to function properly even if some communication links fail. This suggests that single point of failure (SPOF) cannot affect distributed control. In the hierarchy control scheme, tertiary control is the uppermost layer, and it responds slowly. The energy market is covered in this layer, which organises the energy dispatch schedule from an economic perspective while taking into consideration negotiations between customers and providers. Social issues and human-machine interaction are also covered at this level. 10  CHAPTER 2 LITERATURE REVIEW 2.1 Literature Review In microgrids, dc is often preferred to ac for three reasons: First off, distribution level transformer-free power systems are now feasible owing to the swift advancement of power electronics technology. Second, dc systems require fewer power conversion steps when several ac and dc loads are associated to the same bus. Third, due to the skin effect, dc current can travel through the entire cable while ac current only passes through the outer surface of a cable. Dc systems may therefore offer times more power than ac systems for power lines of the same size. The current DC microgrid modelling, control, and theoretical stability analysis techniques are thoroughly examined in this chapter. Wu et al (2022) proposed solution for reducing the contravention compression of a solid-state circuit breaker while eradicating DC faults and enhancing fault current restraint is the current restrictive solid-state circuit breaker topology. This construction has compensations over conventional ones, especially in the limitation of fault current and the cutting off of fault line speed. It works particularly well for DC microgrids that are fast expanding and have a large amount of fault current. The blocking process of this topology is theoretically examined in this study, along with predictions of energy consumption and a design strategy for important factors. Using Sabre software, a simulation model is made to verify the proposal's viability. The findings show that the suggested structure performs admirably in terms of fault isolation speed and can reduce the rising proportion of fault current by 53.9%. The newly developed DC solid-state circuit breaker topology in this study has a primary branch made up of a capacitor-blocking module and a current-limiting component. This structure can prioritise the current-limiting branch and carry out the proper fault cutoff operation based on the results of the fault detection when the grid current is abnormal. The presence of the current-limiting inductor slows the increase of the fault current, lowers the overcurrent amplitude, minimises fault energy feed-in, speeds up fault clearance, and promotes dependable grid operation. 11  Hategekimana et al (2022) study reveals that the proposed fault detection and isolation methods swiftly detect faults in the network and efficiently isolate the faulty line segment, enabling the grid to be restored to its normal operation promptly. Two algorithms, implemented in MATLAB/SIMULINK, are developed to analyze fault occurrence and its isolation. The results indicate that these methods hold promise for microgrid protection, effectively addressing fault detection and grid restoration issues, especially in rural villages. The simulation outcomes demonstrate that the proposed fault detection and isolation methods precisely identify and quickly isolate the faulty section of the LVDC microgrid, leading to grid restoration and continuous electricity supply to the unaffected areas. The line fault searching approach is suggested among the ones put out because of how quickly the grid is restored, improving grid performance as a whole. Additionally, by using relays located at both ends of the grid line to interact with the DAB converter, the design and modelling of this technology help to shorten the time it takes to discover faults. The suggested grid protection approach is appropriate for a variety of LVDC microgrid systems, particularly in rural communities, and successfully addresses issues with fault detection and isolation. Reddy et al (2022) proposed protection scheme is of great importance due to the current limit converters and bidirectional power flow in ring-configured systems. It efficiently finds issues like faults and unexpected load switching. The protection approach makes use of oscillation frequency and estimated inductance by investigating fault current characteristics and capacitor-discharge. This method effectively distinguishes between internal and external faults and, in the instance of internal problems, provides the location of the defect. The simulation experiments demonstrate that, despite diverse abnormal circumstances, the projected fault site is unchanged, enhancing relay dependability, particularly for high fault resistances. In this study, a novel protective strategy is suggested to address these problems. Starting with the difference in successive current sample data, it evaluates the current difference index. This non-zero index makes it possible to distinguish between developing faults and sudden switching loads by estimating the fault frequency using the inherent properties of fault current. Local voltage and current samples taken during the fault are then utilised to estimate inductance, which provides information on the polarity and size of the fault and its location, respectively. The suggested 12 approach is tested in MATLAB/Simulink under a variety of conditions, such as low and high resistance faults, varied locations, bidirectional power flow, variable load conditions, and other configurations. The outcomes show that the approach is accurate in determining fault locations in each of these scenarios. This proposed technique surpasses others, increasing relay dependability, according to a comparison study using existing protective measures. Pandey et al (2022) introduces an innovative fault detection and identification method for low-voltage direct current (DC) microgrids with meshed configuration. The technique is based on a graph convolutional network (GCN), which uses measurement data from the network topology and explicit spatial information to effectively find flaws even in the presence of noise and faulty data. The adjacency matrix of the GCN is built using the network topology's inherent graph representation, with node properties including bus voltage and line current samples following faults. Using PSCAD/EMTDC to simulate the DC microgrid model, fault scenarios are developed while taking into account a variety of environmental and physical factors. Convolutional neural networks (CNN), support vector machines (SVM), and fully connected networks (FCN) are compared with other machine learning methods. The outcomes show that the suggested GCN-based method performs better than the competition in fault detection and classification, demonstrating superior resilience in the Nodes and edges of the graph are defined, and network topology is incorporated to provide temporal and spatial information to the fault data samples, enhancing classification accuracy. The method is extensively evaluated through fault simulations involving variations in temperature, irradiance, fault resistance, and fault distance. The experimental results showcase the method's high accuracy in distinguishing various types of disturbances, including faults. However, one limitation of the suggested process is its dependency on the grid topology, as the adjacency matrix needs to be reconfigured when the topology changes. To address this, future work may explore dynamic graph approaches to handle frequent system-changing conditions and enhance the method's flexibility. Ibrahim et al (2022) addresses the challenges involved in protecting DC microgrids and explains fault detection techniques and design standards for effective 13 protective systems. The consequences of various protection solutions for DC microgrids, such as those for line-to-ground and line-to-line faults, are discussed. The research also offers DC fault current interrupting devices as viable remedies to improve DC microgrid protection. However, safeguarding DC microgrids from different defects is a difficult task. This is because DC power networks are special in that they have plenty of big DC capacitors, low resistance DC connections, no natural zero-crossing locations, and lots of transient current and voltage. The protection challenges with DC microgrids are further complicated by converters with restricted fault current, short lines, and practical grounding techniques. A substantial amount of distributed generation has been integrated into utility networks as a result of the growing use of renewable energy sources. This pattern has resulted in challenges in quality, safety, and reliability are reviving interest in DC power systems. Due to their reliance on power electronic components, DC microgrids provide an alluring solution to these problems. They provide a practical method for integrating distributed energy systems with power grids and exhibit outstanding performance in both grid-connected and islanded modes. Prince et al (2022) gives a comparative examination of the different protection issues that DC microgrids with integrated converters, storage, and distributed energy sources face. The development of an appropriate protection mechanism is necessary due to the special characteristics of failures in DC microgrids. In order to explore various topologies, protection and fault concerns, and other pertinent issues in DC distribution systems, the study adopts a methodical approach. Grounding and the absence of zero-crossing current, two crucial concerns in DC microgrids, are thoroughly examined. Despite the operational benefits of DC microgrids, a fundamental question surrounds their protective infrastructure. The difficulties with grounding systems in DC microgrids are thoroughly investigated, as well as the features of several grounding topologies. An adaptive protection strategy is most useful in this situation because conventional protection strategies are frequently ineffective for DC microgrids. Additionally, the protection devices for DC microgrids should be designed in accordance with the characteristics of the fault current. It is clear that additional academic research is needed to fully understand the safety of DC systems due to the absence of norms and recommendations. By taking the dynamic behaviour of renewable energy sources into account, models' accuracy 14 can be improved. For DC microgrids, a fault detection technique should be created that is not dependent on the grid's fault impedance. The type of DC faults the system experiences should determine the selection of an appropriate protection mechanism. Zolfaghari et al (2022) emphasizes the prevalence of BILPCs as the primary method for interconnecting HMGs. Among the control strategies for BILPCs, the droop-control- established approaches have been widely utilized. Looking ahead, future research endeavors may focus on enhancing the heftiness and tractability of the existing control approaches or exploring novel approaches based on switched control ideas. Additionally, unconventional approaches, such as small-scale Flexible AC Transmission Systems (FACTS), could be considered as viable options for interconnecting HMGs. These research directions hold potential for advancing the efficiency and effectiveness of HMG interconnection techniques. The integration of AC and DC microgrids forms the hybrid AC/DC microgrid (HMG), a crucial element in the forthcoming implementation of smart grids. Within HMGs, the interconnection of AC and DC microgrids and the control of bidirectional link power converters (BILPCs) have received significant research attention over the past decade. This study provides a thorough analysis of various connectivity strategies and control issues related to AC and DC microgrids in HMGs. Batmani et al (2022) presents a fault-tolerant control system using the nonlinear state-dependent Riccati equation (SDRE) approach. The suggested system is made up of three emergency controllers, a master controller, an observer-based fault detection and isolation system, and an observer-based fault isolation system. As a suboptimal nonlinear regulator, the master controller attempts to bring the DC microgrid (MG) back to the intended equilibrium point during normal operation. The goal of the SDRE observer is to offer a uniform platform for DC MG fault isolation and detection. The suggested system may isolate the malfunctioning distributed generation (DG) unit in the event of an unanticipated problem, and the emergency controllers are immediately triggered to stabilise the MG. Results from simulations show that the suggested approach is effective in attaining control goals and providing online safety. 15  Li and Chen et al (2022) introduces a novel DC microgrid cluster (SCMC) having differential power processing features that is series-connected. The proposed cluster comprises of n microgrids that may transmit power amongst one another thanks to n bidirectional DC/DC converters. An additional converter is also included to balance out current changes brought on by voltage variances. By using a series architecture, the converter's one port voltage can be decreased to the voltage difference between a microgrid and a bus, allowing the converters to process a portion of the power and transmit the rest directly. This feature leads to improved power density, reduced converter voltage stress, and enhanced overall efficiency. A thorough examination of the system performance measures is done, along with a comparison to more traditional methods that highlights the proposed SCMC's undeniable advantages. Moreover, a case study of a three-microgrid cluster is used to implement the design concerns and control methodologies. Experimental simulations are used to further substantiate the theoretical analysis. The DC microgrid cluster with differential power processing properties is series-connected offers a promising solution for power transfer and distribution among microgrids, achieving significant improvements in power density, cost reduction, and voltage stress reduction for converters. Rao and Jena (2022) presented simulations on a two-bus tapped DC microgrid are used to validate the proposed architecture while taking into account various failure situations, including high-resistance faults, variable fault locations, and various distributed generation operation modes. Additionally, a lab-implemented DC microgrid hardware bed is used to evaluate the proposed method under various fault scenarios. Due to its efficiency and simplicity as compared to AC microgrids, DC microgrids are becoming more and more popular. Protection strategies for tapped line-based DC microgrids are still in the early phases of development, although a variety of protection solutions are available for ring main and radial DC microgrid topologies. The loads and distributed energy resources (DERs) in tapped line-based medium-voltage direct current (MVDC) microgrids are connected at various places along the line. Existing unit protection techniques, however, fail to detect system problems when there is no communication link from the tapped line to any bus in the microgrid. This article suggests a novel unit protection technique for tapped line MVDC systems based on the idea of superimposed resistance to overcome this 16 problem. The suggested method is resilient to load changes and variations in power generation at the tapping station since it uses prefault current data to determine the tapping state. The findings show that the suggested unit protection approach for tapped line-based MVDC microgrids is reliable and effective, providing a viable way to improve the fault detection capabilities in such systems. Prince et al (2022) proposes an efficient fault identification method for safeguarding DC microgrids based on the actual and fictitious powers derived using Fast Fourier Transform (FFT). When dispersed generators are integrated into DC microgrids, weak fault currents in a variety of directions can result. This coordination issue and difficulty for conventional over-current relays. To overcome this, strategies for quick short-circuit fault detection and fault isolation protection are built using the complicated power concept (real and imaginary). To provide fault isolation, solid- state DC circuit breakers are used in conjunction with the real and imaginary power that is proposed to be derived from the total FFT power signal (based on bus voltage and line current). In the DC microgrid, relay trip threshold values for real and fictitious power are established for a variety of pole-pole (P-P) and pole-ground (P-G) failure scenarios. Using MATLAB/Simulink software, the suggested protection method is tested on straightforward and modified IEEE 9-bus DC microgrids in On/Off-Grid modes. The results of the simulations show how well the suggested approach can identify faults in the simulated DC microgrids. A useful fault identification method based on actual and fictitious FFT powers is also presented in another paper for the protection of DC microgrids. The suggested approach uses complex FFT power, real FFT power (RFFT), and imaginary FFT power (IFFT) to identify and categorise errors at various DC microgrid locations. It is suggested to use a relay trip threshold to recognise P-P and P-G faults with accuracy in various fault scenarios. Chen et al (2022) introduces a fresh approach to dealing with protection issues in DC microgrids and networks, which frequently use DC-DC power converters with lots of semiconductor-based power electronics to link renewable energy sources and flexible loads. However, the majority of semiconductor devices are only capable of withstanding a small number of faults, and traditional power electronic protection solutions have problems with timing, self-destructing, and 17 judgement. The study suggests using a superconducting fault current limiter (SFCL) to protect power electronic devices and expand its applicability to microgrids in order to get around these restrictions. The SFCL serves as a passive current limiter that is self-triggering, recoverable, and passive, thus no additional hardware or software is required. The viability of applying this superconductor-based protection method to produce self-acting fail-safe protection for DC-DC converters is shown through experimental investigations and computer simulations. Additionally, system-level simulations investigate how well the SFCL can handle millisecond-level faults and transients in a photovoltaic-based DC microgrid by suppressing overcurrents and stabilising bus voltage. The study establishes the framework for an interdisciplinary application spanning power electronics, microgrids, and applied superconductivity that is superconductor-semiconductor linked. The article expands the possible use of superconductor-semiconductor coupling into microgrids and gives a preliminary analysis on its use. It is a realistic solution for fail-safe protection of power electronic switches and devices, especially in situations with millisecond-level transients and faults, thanks to the self-acting features and advantages of the proposed compact-size, low-cost SFCL. This innovative security method based on superconductors shows potential for integration. Gorji (2022) propose in the event of an open-circuit defect in its power switch, three reconfigurable topologies of quadratic buck DC-DC converters can seamlessly switch to semi-quadratic buck-boost converters. We establish a topology that enables a secure switch transition while preserving optimal power conversion with all other components by implementing graph-based circuit synthesis techniques. It is well known that quadratic buck converters are efficient at providing certain loads, like as electrolyzers, which need high current and low voltage. Reconfigurability provides an added measure of security by ensuring that such loads will always receive power. The proposed reconfigurable topologies are very advantageous since an unwanted shutdown could have a negative effect on the life- cycle of the load. We create three quadratic buck topologies and combine them with three semi-quadratic buck-boost topologies using graph theory for electrical circuits. These topologies effectively manage open-circuit faults by switching to a different topology automatically using the other switch and using different routes for power conversion. The high step-down voltage conversion ratio required by electrolyzer 18 applications makes the quadratic buck topologies ideal. The needs of the life-cycle of an electrolyzer, where a constant power supply is essential, are well-aligned with the reconfigurability of these circuits. Through simulations and lab prototypes, we verify the suggested circuits' functionality. Future research can look at using the same method for isolated topologies with input-output isolation requirements or look into more degrees of freedom for altering the voltage gain ratio, like using transformers. Thakur and Jain (2022) investigates the transient stability of DC microgrids, whose integration into the distribution network is challenging because to nonlinearities generated by converters. The analysis takes into account a number of situations, including pole-to-ground failure, nonlinear load, nonlinear load with dispersed generation, and linear load. A nonlinear decoupling method is used for transient stability assessment in order to effectively analyse the high-order and nonlinear character of DC microgrids. The findings demonstrate the importance of DG as active power compensation when nonlinear loads are present, considerably enhancing system active power as a whole. DG serves as a backup during faults, powering the load. The nonlinear decoupling technique successfully addresses nonlinear difficulties and is particularly suitable for evaluating transient stability in DC microgrids. Results from simulations also show that certain system adjustments. Mishra et al (2022) provides a thorough and current analysis of DC microgrids (DCMG) and all of their facets. Researchers have been drawn to this area of study by the growing interest in DCMGs as a practical means of supplying local loads while strengthening the stability, reliability, and controllability of power systems. DCMGs offer distinctive compared to AC microgrids, there are difficulties and variances in topology, configuration, protection needs, and grounding. The review technique calls for duties including compiling pertinent papers on microgrid protection, weeding out the crucial ones using inclusion/exclusion criteria, and evaluating each article critically. The paper discusses a wide range of DCMG protection and grounding-related subjects and offers helpful insights into the approaches put forth by diverse academics. It also makes suggestions and poses queries for additional research in this field. The electrical utility sector has paid a lot 19 of attention to DC-based power generation, transmission, and distribution, which has sparked the development of DC microgrids. While DCMGs have several advantages over AC microgrids, they also have operational, control, and safety-related technical difficulties. This study conducts a thorough analysis of the DCMG topology, protection standards, problems, and difficulties, as well as safety equipment and fixes. It covers the significance of grounding in the DC distribution network and outlines the essential requirements for DCMG protection, such as fault detection, location, and classification. Comparisons with AC microgrid protection systems and high voltage DC transmission show that DCMG protection is still an area that needs more investigation. The study highlights the possibility that protection measures and equipment used in AC systems. Baidya and Nandi (2022) study It turns out that, despite the fact that each mode of DC Microgrids provides unique issues linked to faults, the majority of protection strategies are made to accommodate both islanded and grid-connected modes. Continuous study is needed in this area to build a protection strategy that is both economical and sensible. While identifying and isolating defective components from the functioning system, the optimum protection solution should provide precision, sensitivity, quick response, low power loss, small size, long life, and cost effectiveness. Future research must focus on managing both protection units and upstream and downstream devices. Extending research on protective areas including converter topology, IoT, Blockchain Technology, AI, Machine Learning, and Deep Learning holds enormous potential given the sizeable amount of electronic devices in DC Microgrids, such as converters and communication networks. To address various situations and scenarios in DC Microgrids, it will take more work to overcome the drawbacks of current protection schemes due to the absence of standardised procedures and restricted participation. Future studies should concentrate on developing and improving protection plans while assuring their adaptability and efficacy for a range of operational circumstances. Due to their self-sustaining character and incorporation of distributed energy resources (DERs) that may function independently during grid outages, DC Microgrids are becoming more and more popular. DC Microgrids have a number of benefits, including increased energy efficiency, cost-effectiveness, dependability, safety, and simplicity. However, DC Microgrids face considerable issues with regard to protection. 20  Sharma et al (2022) introduces a cutting-edge protection strategy based on transient power characteristics for DC microgrids. To ensure accurate failure detection, the method includes main and localised backup protection. Without relying on synchronous data or high-speed communication, the primary protection checks the polarity of transient power at both ends of the cable to identify internal problems. However, the primary defence might not be enough in the event of a communication breakdown. In order to detect failures as a backup, the localised backup method measures the variation in average transient power at one end of the cable. Performance of the suggested protection plan is assessed at various points throughout the system for various low resistance and high resistance pole-to-pole and pole-to- ground fault types. According to simulation data, the localised backup protection scheme identifies faults in less than 1 ms overall, while the primary protection scheme does so in less than 70 and 200 milliseconds, respectively. This total detection time takes into account communication latency. Further system transients, such as AC side faults, loud surroundings, load changes, DG outages, and generation uncertainty are used to confirm the proposed scheme's robustness. The suggested scheme's advantages in terms of speed, accuracy, and sensitivity for fault detection and transients in the system are highlighted by comparison with existing techniques in the literature. Rao and Jena (2022) proposed the resistance is estimated using the local measurements that are available on the bus. Faults can be quickly found by comparing the sign of the predicted resistance at the line segment's two ends. By doing away with time synchronisation, this method makes detection easier. The proposed method is applicable to DC microgrids with radial and ring configurations. Using EMTDC software simulations on a ring main DC microgrid system, we verify the methodology. Additionally, using technology that simulates different conditions, we experimentally test the suggested approach. The simulation and experimental findings show how well the suggested method works for precisely identifying faults, such as close-in faults and high-resistance faults, within the DC microgrid. This line parameter-based strategy exhibits encouraging potential as a trustworthy. Prince et al (2021) propose a fault detection system for the DC microgrid system using IEEE 9-bus. Our defence system includes 18 protective devices (PDs), 21 which can quickly identify and isolate problematic bus segments without shutting down the entire system. The total fault current contributes significantly to quickly locating the defective wires. Our technique achieves a remarkable accuracy of 95% in estimating the threshold value by examining the maximum threshold peak of the difference between forward and backward fault current. Our suggested solution achieves effective defective line detection and isolation under pole-pole fault circumstances while being less sophisticated than existing algorithms. Due to the availability of low-passivity-based distributed energy, DC microgrids demonstrate rapid changes in fault current compared to typical AC power systems. This feature creates extra difficulties in fault detection and identification, along with the small magnitude of the fault current. In the 9-bus DC microgrid system, our cutting-edge protection system effectively locates short-circuits and isolates faults. This is done by using a solid-state circuit breaker to isolate faults using a cumulative sum-based method. Analysing locally obtained current and voltage signals at the borders reveals the defective line. After that, the defective branch is isolated by tripping at each system node. Zubieta et al (2021) proposed the protection idea is that it can identify defects that conventional approaches could miss, such as high resistance faults as well as low impedance faults. Furthermore, the idea enables the addition of impedance to the distribution line, which effectively causes the current di/dt to slow down in the event of a short circuit problem. This lessens the strain on the components in charge of cutting off the fault current. The protection strategy is especially well suited for power distribution systems based on DC microgrids, where all loads or prosumers supplied by the distribution network have energy storage resources. The protection strategy can successfully separate load and local generation transients from the power exchanged with the DC distribution line by making use of the energy storage resources present at prosumers. Experimental implementation and deployment have been conducted at a DC microgrid demonstration in Albuquerque, New Mexico, as part of the Emera Technologies Block Energy System development, to confirm the concept's efficacy. This demonstration's actual use of the protection concept is evidence of its viability and potential for use in future DC microgrid-based power distribution systems. 22  Zhang et al (2021) presented Ring microgrids are given a revolutionary differential protection system that emphasises the bus's power change rate as a crucial factor. In order to ensure optimum detection sensitivity during short-circuit occurrences and rapid fault indication, the technique makes use of the differential power change rate between the two sides of the bus. This strategy dramatically shortens the time it takes for the fault current to reach the action threshold in contrast to traditional protection methods based on current, speeding up the total fault detection procedure. The proportionality to the square of the current and consideration of higher orders strengthen the scheme's effectiveness by enhancing change rate responsiveness and sensitivity to even little flaws. Additionally, its proportionality to the short-circuit impedance greatly widens the range of fault detection, improving protection sensitivity throughout the entire microgrid. Numerous simulations have been run to verify the effectiveness of the suggested protection system. The findings show considerable advances in responsiveness, speed, and interference resistance. Notably, the plan retains good selectivity for differential protection, guaranteeing that, in the event of a malfunction, the system as a whole is protected while just the afflicted portion of the microgrid is isolated. Bayati et al (2019) takes advantage of current transients seen during faults to create a localised framework for locating faults and figuring out resistance. A distinguishing feature is the lack of communication linkages because the fault location and resistance calculation are carried out independently. The suggested method makes computation of fault resistance and location easier by developing a mathematical equation defining current and voltage behaviour. Importantly, this approach does not require any communication linkages to be established during fault resistance or location assessment. Experimental results show that the technique is effective, with fault location and resistance calculation precision for component and line faults of less than 5%. It's significant that the suggested approach is easily adaptable to ring-configured DC microgrids, supporting faults with different resistance levels. Additionally, the plan can adjust to dynamic changes in operational modes and topology, providing complete protection for DC microgrids. Results from simulations confirm the proposed algorithm's efficacy and demonstrate its superiority when compared to existing alternatives. The proposed protection strategy's ability to accommodate the bidirectional current flow that is innate to ring systems makes it 23 stand out from other approaches. Only locally acquired measurements are used in the developed mathematical equations for fault location and resistance computation. On the Digsilent platform, a multi-source ring-type DC microgrid is used to rigorously evaluate the fault location technique. The results support the suggested method's robustness in the face of various fault locations and resistances. 24  CHAPTER 3 PROBLEM FORMULATION AND OBJECTIVES 3.1 Problem Formulation DC microgrids are a novel approach to effective and dependable electricity distribution as a result of the rapid development in energy consumption and the emergent obligation for justifiable power generation. An area-specific power system called a DC microgrid allows for the assimilation of renewable power sources, increased energy efficiency, and increased grid dependability. It can run independently or in cooperation using the primary grid. The development of DC microgrids as a possible substitute for conventional AC grids is a result of the increasing requirements for clean and sustainable energy resolutions as well as the requirement for efficient and reliable power delivery. A DC microgrid is a minor measure power system that runs independently of or concurrently with the higher grid, enabling the use of green energy options, enhancing energy efficiency, and improving overall grid stability. Designing an effective DC microgrid involves addressing various challenges related to system requirements, component selection, control strategies, simulation modeling, optimization, and implementation. The first step in designing a DC microgrid is to define the system requirements accurately. This involves determining the power demand, load characteristics, voltage levels, and operational modes. The power demand serves as a fundamental parameter that influences the selection of components and the design of control schemes to encounter the vitality needs of the microgrid. The scheme requirements also encompass factors such as grid connection options, islanded operation capabilities, and the desired level of reliability and stability. Once the system requirements are established, the next step is to select appropriate components for the DC microgrid. This includes PV panels, wind turbines, battery energy storage systems (BESS), power converters, and other auxiliary equipment. Component selection is based on factors such as power generation capacity, efficiency, cost, reliability, and compatibility with the overall system design. The chosen components should align with the available renewable energy sources and meet the load requirements of the microgrid. To accurately simulate the behavior of the components within the DC 25 microgrid, mathematical models need to be developed. These models capture the power generation characteristics of the PV panels and wind turbines, the dynamics of the BESS, and other relevant components. The mathematical models serve as the foundation for simulating and analyzing the performance of the microgrid under various load scenarios and operating characteristics. The models should accurately represent the nonlinear characteristics, time-varying dynamics, and interactions between the components. Designing effective control strategies is crucial for managing power flow, voltage regulation, and energy management within the DC microgrid. Control algorithms need to be developed for numerous aspects, including maximum power point tracking (MPPT) to optimize renewable energy generation, energy storage management, load balancing, and unified switching among electrically linked and island operating modes. These control strategies ensure efficient utilization of available resources, stable grid operation, and effective management of energy storage systems. Once the microgrid design is validated, it can be implemented in a hardware setup for further testing. Comprehensive testing is accompanied to authenticate the enactment, stability, and reliability of the microgrid under real-world conditions. This testing phase ensures that the design functions as intended and meets the desired objectives, such as power demand fulfillment, voltage stability, and energy efficiency. Field tests can involve connecting actual sources of green energy, energy storage devices, and demands to evaluate the system's behavior and validate its performance. The design of a DC microgrid using MATLAB requires a systematic and comprehensive approach that considers system requirements, component selection, mathematical modeling, control strategy design, simulation model development, fine-tuning, validation, implementation, and continuous monitoring. By following this methodology, engineers and researchers can design and analyze DC microgrids that integrate renewable energy sources, meet power demand requirements, enhance energy efficiency, and improve overall grid stability. The utilization of MATLAB provides powerful tools for modeling, simulation, control algorithm development, and optimization, enabling the efficient design and optimization of DC microgrids. The successful implementation of a well-designed DC microgrid can contribute significantly to the transition concerning a more viable and resilient energy future. 26 3.2 Problem Statement The problem statement of this research work revolves around the design and analysis of a DC microgrid using MATLAB. A DC microgrid is a confined power distribution system that integrates various components, such as photovoltaic (PV) panels, wind turbines, energy storage systems (ESS), and power converters, to efficiently generate, store, and distribute electricity. The aim of this research is to address the challenges associated with the design and optimization of a DC microgrid, focusing on maximizing the utilization of renewable energy sources, managing power flow and voltage regulation, and ensuring reliable and efficient energy management within the microgrid. One of the primary challenges in designing a DC microgrid is to effectively utilize renewable energy sources, such as PV panels and wind turbines. These sources are inherently intermittent and highly dependent on environmental conditions, which makes it crucial to implement. The research aims to investigate and develop efficient MPPT algorithms that can optimize the power generation from renewable sources, thereby maximizing the utilization of clean energy and reducing reliance on conventional energy sources. 3.3 Objectives  To design the hybrid renewable system (wind energy, photovoltaic power, and a battery) in MATLAB/Simulink.  Implementation of Hybrid renewable sources in DC Microgrid for maximum Output Power.  Analysis of Faults a) Analysis of Faults with grid and PV system b) Analysis of Faults with grid and wind form. c) Analysis of Faults PV, wind and AC source. 27  CHAPTER 4 METHODOLOGY 4.1 Introduction Since their capability to completely alter the way power is distributed, DC microgrids have attracted a lot of attention lately. A DC localised electrical network called a "microgrid" incorporates various distributed energy resources (DERs), energy storage systems, and loads in a DC distribution network. Unlike traditional AC grids, DC microgrids offer numerous advantages, including higher efficiency, improved power quality, expanded use of green power resources. The increasing demand for clean and sustainable energy sources has led to a pattern modification in the way power systems are designed and operated. One promising solution to address this challenge is the perception of a DC microgrid. A DC microgrid is a localized power distribution network that operates primarily on direct current (DC) and DERs such as solar photovoltaic (PV) panels, wind turbines, ESS, and loads. Unlike traditional AC grids, which are prevalent in most power systems, DC microgrids suggestion several compensations in relations of efficiency, reliability, and flexibility. By utilizing DC power, the need for multiple power conversions, as required in AC grids, is significantly reduced, resulting in lower energy losses and improved overall system efficiency. 4.2 Methodology Designing a DC microgrid with PV panels, an AC grid connection, a wind farm, an AC to DC converter, and analyzing fault occurrences on the DC line begins with configuring the system. Figure 4.1 shows the complete dc-microgrid. Integrated PV panels, wind turbines, and grid into the DC microgrid to harness renewable energy sources. Design and model the PV and wind systems to capture maximum power output based on solar irradiance and wind speed variations. Implement maximum power point tracking (MPPT) algorithms for both the PV and wind systems to continuously track and extract the maximum available power from these sources. Consider different MPPT techniques and their compatibility with PV and wind systems. Incorporate a battery storage system into the DC microgrid to store excess energy from PV and wind sources. 28 Figure 4.1 DC-microgrid designed using MATLAB/Simulink 29 Design the battery system to handle charging and discharging cycles efficiently and manage the energy flow within the microgrid. DC microgrid that integrates PV, wind, battery storage, and grid connection. This system provides green energy generation, energy storage capabilities, and the flexibility to function together in grid connected and islanded modes, ensuring reliable and sustainable power supply. The power ratings and specifications of each component are determined based on the desired power demand and renewable energy generation capacity. Next, a mathematical model is developed for the PV panels to simulate their power generation characteristics, considering factors such as irradiance and temperature. An AC grid connection is comprised in the microgrid to provide backup power and facilitate a seamless switch among linked to the grid and isolated options. A control method is designed to manage power transfer between microgrids and the AC grid, while protection mechanisms are implemented to ensure safe operation during grid- connected mode. Figure 4.2 shows the PV system designed for dc-microgrid. Developed model of the PV array based on current-voltage (I/V) and power-voltage (P/V) are two examples of its electrical properties. Current-voltage (I/V) and power- voltage (P/V) are two examples of its electrical properties curves. This model should consider factors like solar irradiance, temperature, and shading effects. Design and simulate a DC-DC converter, such as a buck or boost converter, to regulate the voltage from the PV array to match the DC microgrid voltage level. The converter design should consider efficiency, stability, and control strategies. The incorporation of energy storage, such as batteries or supercapacitors, in the PV system. Develop control algorithms to manage the charge/discharge cycles of the energy storage system built on the PV power generation and load demand. 30  Figure 4.2 Designed PV system in MATLAB/Simulink Figure 4.3 shows the designed wind generator for dc-microgrid. Model of the wind turbine based on its aerodynamic characteristics, turbine power curve, and wind speed. Consider factors such as wind speed variations, turbulence, and wind direction. Implement a maximum power extraction algorithm to apprehension the extreme available power from the wind turbine. a rectifier and DC-DC converter to convert the variable AC output of the wind turbine into a regulated DC voltage suitable for the microgrid. The designed wind generator system in MATLAB to analyze its performance under varying wind speeds, turbulence, and load fluctuations. Evaluate metrics such as power output, efficiency, and response time. design and optimize a wind generator system for a DC microgrid, ensuring efficient power generation, integration with energy storage, and reliable operation in different modes. 31  Figure 4.3 Wind farm model designed in MATLAB/Simulink Figure 4.4 shows the energy storage system in MATLAB. The appropriate battery equipment (e.g., lithium ion, lead-acid, flow battery) based on the requirements of the DC microgrid, such as energy capacity, power capability, efficiency, cycle life, and cost. Consider factors like load demand, renewable energy generation, and expected discharge duration. the optimal size (capacity) of the battery storage system to meet the energy requirements of the DC microgrid. Consider factors like peak load demand, renewable energy availability, desired backup duration, and system reliability. Figure 4.4 Designed storage system for dc-microgrid 32  CHAPTER 5 RESULTS AND DISCUSSIONS 5.1 Introduction DC microgrids have gained significant attention as a promising solution for efficient and sustainable power distribution. They provide an alternative to traditional AC- based grids, offering advantages such as higher efficiency, reduced transmission losses, and the ability to integrate renewable energy sources effectively. In this project, a DC microgrid is designed, incorporating photovoltaic (PV) power, wind power, battery storage, and grid connection. The performance of the designed DC microgrid was evaluated through simulations and analysis. The integration of PV panels and wind turbines allowed for the effective utilization of renewable energy sources. The PV system generated power during daylight hours, while the wind system produced power during windy periods. This combination ensured continuous power generation, reducing dependency on the grid. DC microgrids have emerged as a promising solution for achieving efficient, reliable, and sustainable power distribution in various applications. Unlike traditional AC grids, DC microgrids utilize direct current (DC) for power transmission and distribution, offering several advantages such as reduced conversion losses, improved system stability, and seamless integration of renewable energy sources. In this research, a comprehensive analysis of a DC microgrid is conducted to assess its performance, efficiency, and feasibility in meeting the growing demand for clean and resilient energy solutions. CASE 1: 5.2 Analysis of Fault with Grid and PV Based DC-Microgrid A DC microgrid with an AC grid and PV system with DC converters combines both DC and AC power sources within a microgrid infrastructure. The PV panels generate DC electricity from sunlight. These panels convert solar energy into electrical energy through the photovoltaic effect. In the event of a fault on the grid, where the power supply from the grid becomes unavailable or unstable, a PV-based system can be designed to switch to the PV source to provide power to the load. This can be achieved through the use of appropriate control and switching mechanisms. Analysis 33 of the fault occurring at different intervals of time on ac-grid which causing the switching on the PV source are carried out. Figure 5.1 shows the irradiance of the PV plant started at t=0 sec which helps to assume that ac-grid is off at t =0 sec. The power delivered to load is solely by the PV plant. Figure 5.2 shows the power delivered to the load which is 10 kW. Figure. 5.1 Irradiance of the PV plant started at t=0 sec Figure. 5.2 Power delivered to load by PV plant Figure 5.3 shows the ac-grid three phase output which is approximately 50 kV. At t=1 sec an fault occurs at ac-grid causing disruption at the output. Figure 5.4 shows the irradiance of the PV plant started at t=1 sec to continue the flow of power to load. 34  Figure 5.3 Output from ac-grid from t =0 to t=1 sec Figure 5.4 Irradiance of the PV plant started at t=1 sec The combined power delivered to load by ac-grid and PV plant is shown in Figure 5.5. A small glitch is seen at t=1 sec due to the fault occurring in the transmission and switching of the supply to the PV plant. The power delivered to the load by ac-grid and PV plant is approximately 10 kW. The recovery time for constant flow of power is 0.1 sec. 35 Figure 5.5 Combined power delivered to load by ac-grid (from t=0 to t=1 sec) and PV plant (from t =1 to t=5 sec) Figure 5.6 illustrates the three-phase AC grid output, which has an approximate voltage level of 50 kV. At t=2 sec, a fault occurs in the AC grid, causing a disruption in the output. Conversely, Figure 5.7 displays the irradiance of the PV plant, which starts at t=2 sec. The purpose of this figure is to demonstrate that despite the fault on the AC grid, the PV plant continues to receive solar radiation. As a result, it can generate power to supply the load.. Figure 5.6 Output from ac-grid from t =0 to t=2 sec 36  Figure 5.7 Irradiance of the PV plant started at t=2 sec Figure 5.8 depicts the combined power delivered to the load by the AC grid and PV plant. At t=2 sec, a fault occurs in the transmission and switching process, resulting in a minor disruption seen as a glitch in the power delivery. The total power supplied to the load by the AC grid and PV plant throughout the entire simulation cycle is approximately 10 kW. The system exhibits a fast recovery time of 0.1 sec to restore a consistent and uninterrupted flow of power to the load. Figure 5.8 Combined power delivered to load by ac-grid (from t=0 to t=2 sec) and PV plant (from t =2 to t=5 sec) Figure 5.9 shows the ac-grid three phase output which is approximately 50 kV which is converted in to dc voltage. At t=3 sec a fault occurs at ac-grid causing disruption at the output. Figure 5.10 shows the irradiance of the PV plant started at t=3 sec to continue the flow of power to load. 37  Figure 5.9 Output from ac-grid from t =0 to t=3 sec Figure 5.10 Irradiance of the PV plant started at t=3 sec The combined power delivered to load by ac-grid and PV plant is shown in Figure 5.11. A small glitch is seen at t=3 sec due to the fault occurring in the transmission and switching of the supply to the PV plant. The power delivered to the load by ac- grid (from t=0 to t=3sec) and PV (from t = 3 to t= 5sec) plant is for complete simulation cycle is approximately 10 kW. The recovery time for constant flow of power is 0.1 sec. 38  Figure 5.11 Combined power delivered to load by ac-grid (from t=0 to t=3 sec) and PV plant (from t =3 to t=5 sec) Figure 5.12 shows the ac-grid three phase output which is approximately 50 kV which is converted in to dc voltage. At t=4 sec a fault occurs at ac-grid causing disruption at the output. Figure 5.13 shows the irradiance of the PV plant started at t=4 sec to continue the flow of power to load. Figure 5.12 Output from ac-grid from t =0 to t=4 sec. 39  Figure 5.13 Irradiance of the PV plant started at t=4 sec The combined power delivered to load by ac-grid and PV plant is shown in Figure 5.14. A small glitch is seen at t=4 sec due to the fault occurring in the transmission and switching of the supply to the PV plant. The power delivered to the load by ac- grid (from t=0 to t=4sec) and PV (from t = 4 to t= 5sec) plant is for complete simulation cycle is approximately 10 kW. The recovery time for constant flow of power is 0.1 sec. Figure 5.14 Combined power delivered to load by ac-grid (from t=0 to t=4 sec) and PV plant (from t =4 to t=5 sec) 40 The response of the DC microgrid with a PV source to a fault at the AC-grid section can be observed from the provided table. The fault occurrence causes a noticeable impact on various parameters within the microgrid. Firstly, the PV voltage experiences a significant drop from 11.40 kV to 5.141 kV as the fault occurs, indicating a disturbance in the PV system. However, the bus voltage remains relatively stable throughout the fault, ranging from 245.10 V to 248.50 V. This stability suggests that the microgrid is equipped with mechanisms to regulate the voltage during such events, possibly including voltage control systems or energy storage solutions. Moreover, the bus current shows minimal variation during the fault, maintaining a relatively constant range between 40.84 A and 41.41 A. This indicates that the fault does not result in significant disruptions to the current flow within the microgrid. Similarly, the load power remains relatively stable, with a slight increase from 10.03 kW to 10.34 kW. Table 5.1 Response of dc-microgrid with PV source and fault at ac-grid section. Fault Occurring PV Voltage Bus Voltage Bus Current Load Power Time (sec) (kV) (V) (A) (kW) 0 11.40 245.10 40.84 10.03 1 10.27 246.10 41.02 10.15 2 8.893 246.90 41.15 10.21 3 6.270 247.70 41.28 10.27 4 5.141 248.50 41.41 10.34 CASE 2: 5.3 Analysis of Fault with Grid and Wind Farm Based DC-Microgrid The integration of an AC grid and a wind farm in a DC-grid offers several advantages and poses specific challenges. The AC grid serves as the main power source, providing a reliable and stable electricity supply. Meanwhile, the wind farm contributes renewable energy by harnessing wind power through wind turbines. AC 41 power generated by the wind farm undergoes conversion into DC power using power electronic converters. Analysis of the fault occurring at different intervals of time on ac-grid which causing the switching on the wind farm are carried out. Figure 5.15 shows the nominal wind speed subjected to wind farm for power generation assuming that grid is at fault at t=0. The wind speed of 12 m/sec is applied to the farm and from Figure 5.16 it can be inferred that the power generated by the farm gradually increases and maintains it to 0.95 kW. Figure 5.15 Wind speed profile from t=0 to t=5 sec Figure 5.16 Power delivered to load by wind farm (from t =0 to t=5 sec) Figure 5.17 shows the ac-grid three phase output which is approximately 50 kV which is converted in to dc voltage. At t=1 sec a fault occurs at ac-grid causing disruption at the output. Figure 5.18 shows the nominal wind speed profile started at t=1 to t=5 sec to continue the flow of power to load. 42  Figure 5.17 Output from ac-grid from t =0 to t=1 sec Figure 5.18 Wind speed profile from t=1 to t=5 sec The combined power delivered to load by ac-grid and wind is shown in Figure 5.19. A glitch is seen at t=1 sec due to the fault occurring in the transmission and switching of the supply to the wind farm output. The power delivered to the load by ac-grid (from t = 0 to t = 1 sec) and wind farm (from t = 1 to t = 5sec) is for complete simulation cycle is approximately 10 kW. The recovery time for constant flow of power is 0.15 sec. The minima occurred at t = 1 sec is 0.45 kW. 43  Figure 5.19 Combined power delivered to load by ac-grid (from t=0 to t=1 sec) and wind farm (from t =1 to t=5 sec) Figure 5.20 shows the ac-grid three phase output which is approximately 50 kV which is converted in to dc voltage. At t=2 sec a fault occurs at ac-grid causing disruption at the output. Figure 5.21 shows the nominal wind speed profile started at t=2 to t=5 sec to continue the flow of power to load. Figure 5.20 Output from ac-grid from t =0 to t=2 sec 44  Figure 5.21 Wind speed profile from t=2 to t=5 sec The combined power delivered to load by ac-grid and wind is shown in Figure 5.22. A glitch is seen at t=1 sec due to the fault occurring in the transmission and switching of the supply to the wind farm output. The power delivered to the load by ac-grid (from t = 0 to t = 2 sec) and wind farm (from t = 2 to t = 5 sec) is for complete simulation cycle is approximately 10 kW. The recovery time for constant flow of power is 0.15 sec. The minima occurred at t = 2 sec is 0.45 kW. Figure 5.22 Combined power delivered to load by ac-grid (from t = 0 to t = 2 sec) and wind farm (from t = 2 to t = 5 sec) 45 Figure 5.23 shows the ac-grid three phase output which is approximately 50 kV which is converted in to dc voltage. At t = 3 sec a fault occurs at ac-grid causing disruption at the output. Figure 5.24 shows the nominal wind speed profile started at t = 3 to t = 5 sec to continue the flow of power to load. Figure 5.23 Output from ac-grid from t = 0 to t = 3 sec Figure 5.24 Wind speed profile from t = 3 to t = 5 sec The combined power delivered to load by ac-grid and wind is shown in Figure 5.25. A glitch is seen at t = 3 sec due to the fault occurring in the transmission and switching of the supply to the wind farm output. The power delivered to the load by ac-grid (from t = 0 to t = 3 sec) and wind farm (from t = 3 to t = 5 sec) is for complete simulation cycle is approximately 10 kW. The recovery time for constant flow of power is 0.15 sec. The minima occurred at t = 3 sec is 0.45 kW. 46  Figure 5. 25 Combined power delivered to load by ac-grid (from t=0 to t=3 sec) and wind farm (from t =3 to t=5 sec) Figure 5.26 shows the ac-grid three phase output which is approximately 50 kV which is converted in to dc voltage. At t = 4 sec a fault occurs at ac-grid causing disruption at the output. Figure 5.27 shows the nominal wind speed profile started at t = 4 to t = 5 sec to continue the flow of power to load. Figure 5.26 Output from ac-grid from t = 0 to t = 4 sec 47  Figure 5.27 Wind speed profile from t = 4 to t = 5 sec The combined power delivered to load by ac-grid and wind is shown in Figure 5.28. A glitch is seen due to the fault occurring in the transmission and switching of the supply to the wind farm output. The power delivered to the load by ac-grid (from t = 0 to t = 4 sec) and wind farm (from t = 4 to t = 5sec) is for complete simulation cycle is approximately 10 kW. The recovery time for constant flow of power is 0.15 sec. The minima occurred at t = 4 sec is 0.45 kW. Figure 5.28 Combined power delivered to load by ac-grid (from t=0 to t=4 sec) and wind farm (from t =4 to t=5 sec) 48 The response of the DC microgrid with a wind farm source to a fault at the AC-grid section is depicted in Table 5.2. The fault occurrence affects various parameters within the microgrid, allowing us to analyze its impact. Firstly, the bus voltage shows an increasing trend throughout the fault, starting from 237.6 V and reaching 244.6 V at the end. This suggests that the wind farm source continues to provide a stable voltage supply despite the fault. The consistent increase in bus voltage indicates the presence of voltage control mechanisms within the microgrid to maintain stable operation. Similarly, the bus current experiences a gradual increase during the fault, starting from 39.60 A and reaching 40.64 A. This indicates that the fault does not disrupt the current flow significantly, and the microgrid manages to maintain a stable current supply. It is worth noting that the load power also exhibits a gradual increase from 9.433 kW to 10.16 kW, which correlates with the increasing bus voltage and current. This suggests that the microgrid successfully delivers a consistent power supply to the connected loads despite the fault. Table 5.2 Response of dc-microgrid with wind farm source and fault at ac-grid section. Fault Occurring Bus Voltage Bus Current Load Power Time (sec) (V) (A) (kW) 0 237.6 39.60 9.433 1 239.5 39.92 9.634 2 241.7 40.28 9.811 3 243.8 40.42 9.987 4 244.6 40.64 10.16 CASE 3: 5.4 Analysis of DC-Microgrid with PV, Wind and AC Source The analysis of a DC microgrid involves examining various aspects of its design, performance, and operation. One key area of analysis is the power generation, where 49 the performance of renewable energy sources like PV panels and wind turbines is evaluated under different conditions. Figure 5.29 shows the three phase output power from the grid. the grid provides the output of 50 kW of approximately 50 kW from t = 0 to t = 1.5 sec. Figure 5.30 represents the irradiance input to a photovoltaic (PV) plant in the DC microgrid. The excitation, or the period of significant irradiance, begins at t = 1.5 seconds and continues until t = 3 seconds. During this specific time zone of irradiance, the PV plant in the DC microgrid was able to generate power as illustrated in Figure 5.31. Based on the details you provided, the power generated by the PV plant during this irradiance period is approximately 12 kW. Figure 5.29 Three phase output from the grid Figure 5.30 Irradiance intensity input to PV panel 50  Figure 5.31 Power output profile of PV plant Figure 5.32 shows the excitation applied to the wind farm. The nominal wind speed of 12 m/sec applied to the farm which was started at t=3 sec to t =5 sec. During this time period power is delivered to the load through batteries. Figure 5.32 Nominal excitation applied to wind farm. The state of charge (SOC) of batteries in a DC microgrid will be influenced by various factors, including the power generation from renewable sources (such as the PV plant and wind farm), the power consumption of loads, and the presence of energy storage systems. If the power generated by the PV plant and wind farm during their respective excitation periods exceeds the power consumption of the loads in the microgrid, the excess power can be used to charge the batteries. This charging will result in an increase in the SOC of the batteries. 51 Figure 5.33 shows the SOC profile of the storage system. During the complete cycle of t =0 to t = 5sec. The SOC of batteries rises from 50% to 50.06%, since the charge is being given load connected to the system, which is evident from the bus voltage which 241.8V shown in Figure 5.34. Figure 5.33 SOC of the batteries Figure 5.34 Bus voltage profile during complete simulation time 52 Figure 5.35 shows the power delivered to the load during the complete simulation time. During the first transition from t=0 to t=1.5 sec power is given by the power grid. During t =1.5 to t=3 sec, power to the load is given by the PV plant and last transition from t= 3 to t=5 sec, power to the load is given by the wind farm. Figure 5.35 Power delivered to load connected to the system 5.5 S