Mehrdad Gholami

BLDCM brushless direct current motors are among the motors that have quickly gained widespread use. BLDCM brushless direct current motors are widely used for a number of industrial applications due to their high range, high torque, and small volume. BLDC motor does not use brush for commutation. Rather, commutation is done electronically. BLDC motor is conventionally known as permanent magnet synchronous motor with back EMF with trapezoidal waveform. In this research, an attempt is made to design a controller that has stable performance with the presence of uncertainties in the engine parameters. The main idea of sliding mode control is to control a first-order system instead of a non-linear and uncertain n-order system. The resulting control method will be much simpler and more practical, and the use of this algorithm will result in stable performance in the presence of uncertainties.

Considering the wide use of single-phase induction motor in various household, office, store and even industrial applications, it is necessary to discuss the drive control of these types of motors, one of the necessary things for better and more optimal use of them. The commonly used control methods for this type of motors are usually using the method of adjusting the voltage along with the frequency or vector control of the field orientation type. The purpose of this research is to deal with vector control. In the discussion of vector control, for the design of speed control loops and other variables, we need to measure the speed and know the position of the rotor. Since speed control is costly and moreover there are limitations in using the sensor in some environments and special conditions, for example, in environments with high temperature and humidity the sensor-less approaches are more likely to address the speed estimation method During the estimation, the motor speed is estimated based on the variables and the motor model depending on the type of method. The purpose of this research is to provide an efficient, simple and uncomplicated method to calculate the motor speed through the indirect vector control method of the stator field orientation type, which is used to improve the response quality of the nonlinear controller and viewer, the correctness of this method is verified through the simulation in MATLAB/SIMULINK.

Water pumping is one of the significant applications of solar energy. The solar pumping system can be categorized into two types based on the number of power conversion stages: single-stage and multi-stage. In multi-stage systems, a DC-DC converter is required to ensure the maximum power point tracking (MPPT). However, this power conversion block leads to increased costs, size, complexity, and reduced system efficiency. In this study, a single-stage solar pumping system using a brushless DC (BLDC) motor is designed to eliminate the need for a DC-DC converter. The single-stage structure is preferred over the multi-stage structure due to its advantages, and the BLDC motor is chosen for its suitability in solar pumping systems. In the proposed system, a hybrid photovoltaic (PV) and battery source is utilized to ensure consistent pumping volume regardless of weather conditions. The PV array serves as the primary power source, while the battery acts as a backup. The battery is discharged only during unfavorable weather conditions or at night when the PV array cannot provide power to the motor-pump. Conversely, when water pumping is not required or the PV power exceeds the motor-pump's power demand, the extra power is stored in the battery, which is then charged. A bidirectional charging control system is employed to automatically switch the battery's mode of operation using a bidirectional converter. To control the BLDC motor, a simple control technique is proposed, which allows the solar PV array to operate at its peak power using a common voltage source inverter (VSI). The controller regulates the motor speed based on the reference speed value.

In order to improve the efficiency of production lines or use non-petroleum energy sources for road transportation, electric-hybrid cars and cars with fuel cells are produced by automobile companies all over the world. The launch lines of these vehicles use electric motors and electric energy storage to supplement the output of the engine or fuel cell during acceleration or to recover energy during braking. The electrical energy storage technologies used are rechargeable batteries and super capacitors (electrochemical capacitors). Electric energy storage units can be charged from an engine or fuel cell or from the power grid just like an electrical appliance. In later variants (often called plug-in hybrids), vehicles can run on liquid or gaseous fuels as well as grid electricity. One of the attractive features of the plug-in hybrid car is that it allows the use of grid electricity using renewable energy sources. In fact, the main idea is to design a rechargeable battery that has the distinctive feature of fast and accessible charging (efficient), so that it can be connected to a household electrical outlet (single phase) and can be used in charging stations for specially charged. In the charging mode through household electricity (single phase), the input of the charger will be 230V AC, and in the charging mode through special stations, the input of the charger will be in the form of three-phase AC; But if you have a residential house with three-phase electricity input, you can also use the second type. The purpose of doing this is to be able to charge your car in any place with the minimum possible infrastructure, but the problem is that the car takes a longer time to charge through the AC charger in the first case when the input voltage is single-phase compared to the three-phase input. To reduce the charging time of the batteries, it can be mentioned that the charging input to the car in the form of DC, that all the operation of generating electric power takes place outside the car, but it is out of the discussion of this topic. The desired charger set can be divided into three parts, the first part is in the single-phase part and the second part is in the three-phase part. The third part is also used jointly between the three-phase and single-phase parts. The verification of this idea is done through simulation software, but in the real world, such ideas have been made to make it easier to charge cars and expand this industry.

The requirements and performance of power systems have changed by the significant influence of renewable energy and distributed generation (DG) sources on the grid. Until a few years ago, DG sources did not contribute significantly to total energy generation. However, alternatively generated energy is currently available for overall electrical generation. Despite the considerable advantages of these sources, the extensive integration of DGs can jeopardize overall system reliability in turbulences such as voltage dips [1-2]. Distributed photovoltaic power generation can generally be controlled by a voltage source inverter (VSI). Disruption in the grid (as in voltage drop) may cause significant economic harm. LVRT is a crucial indicator of grid connection, which is of great significance for the security and sustainable performance of the power grid. LVRT must be implemented at the PCC concerning distributed generation upon grid error or disruption causing voltage fluctuation. Distributed generation using a grid-connected inverter must perform consistently within a specific range and provide the grid with the desired reactive power. In this thesis, a fuzzy controller is designed for optimal control of reactive power injection in error conditions based on the restrictions on operation codes. It is based on the injected reactive flow with variable ratios between positive and negative sequences. The controller also determines the reactive power required to return the amounts of voltage reduced to the new reference values limited to the range of consistent performance set by the grid codes. These reference values are reported to ensure low flow injection upon realization of the purpose of voltage support. The selected simulation results are reported to confirm the effectiveness of the proposed control.

Due to the high cost and price of photovoltaic systems and their low efficiency, operating the system at its maximum power point is necessary. Due to the dependence of this point on the load and the effect of changing environmental conditions, a control system in the photovoltaic system should be used to identify and track the maximum power point. There are problems in placing the solar panels at the maximum power point, which is the non-linearity of the solar cell output characteristic and the variability of this characteristic concerning light radiation and even cell temperature. This dissertation proposes a power point tracking algorithm for the photovoltaic (PV) system of an adaptive and observed perturbation combined with the gray wolf algorithm. The algorithm combines the Gray Wolf Optimization (GWO) and Perturb & Observe (P&O) techniques to extract the maximum power point from a Photovoltaic (PV) system subject to rapidly changing solar radiation and partial shadow conditions (PSC) GWO. We manage the initial stages of maximum power point (MPP) tracking, followed by the P&O algorithm in the final stage by achieving faster convergence to the prominent peak (GP). The goal is to reduce typical P&O constraints, such as steady-state oscillation, divergent tracking, and the inability to detect maximum power during partial shading. In this GWO-based MPPT algorithm, it is observed that MPPT overcomes the computational overhead. The idea of using this hybrid technique is to reduce the GWO search space to help the Achievement speed reach convergence quickly. The proposed idea is validated using Matlab simulation by applying precise dynamic radiation and partial shadow experiments and validation at the end of each step. This method is compared with other algorithms such as the flower pollination algorithm [6], cuckoo search algorithm [2], and particle swarm optimization [8]. The obtained results confirm that the proposed MPPT provides superior tracking performance in partial shadow conditions compared to other algorithms. It successfully follows the proposed maximum method under different partial shadow conditions, while other algorithms Sometimes they fail. In addition, it improves the tracking speed and maintains efficiency with the desired percentage. The importance of this strategy is that when tracking the maximum power point, the output voltage of the solar cell fluctuates, which causes the output power of the solar array to fluctuate. The proposed algorithmcalculates the maximum power point voltage when detecting radiation changes then uses a boost converter to keep the output voltage of the solar array constant at the value calculated by the proposed algorithm. Therefore, the output power of the solar array is always kept constant at a maximum value.

استفاده از انرژی خورشیدی به واسطه سیستم های فتوولتائیک در جهان، با نرخ قابل توجهی رو به افزایش است. مطالعه ی چشم اندازهای صنعت فتوولتائیک بر تداوم و تسریع نرخ توسعه ی این صنعت دلالت دارد. با وجود رشد سریع صنعت فتوولتائیک، مشکلات مربوط به بازده پایین سلول های خورشیدی همچنان باقیست. مطالعات نشان داده است که در هر لحظه، فقط یک نقطه عملکردی مرتبط با یک سلول خورشیدی که در آن نقطه، توان انتقال حداکثر می شود وجود دارد. به این نقطه، نقطه توان ماکزیمم سیستم فتوولتائیک می گویند، که البته با تغییرات تابش و دما تغییر پیدا می کنند. از اینرو جهت استخراج ماکزیمم توان در اغلب ماژول های فتوولتائیک از سیستم ردیابی نقطه توان ماکزیمم استفاده می-شود. روش های متعددی برای ردیابی نقطه توان ماکزیمم ارائه شده است، که در این پایان نامه به صوت دقیق به بررسی سه روش کنترلی P&O، IC و PSO خواهیم پرداخت. بنا بر بررسی های انجام شده و مشاهدات شبیه سازی و نتایج عملی مشاهده خواهد شد که، روش IC دارای سرعت همگرایی بالایی در پیدا کردن نقطه توان ماکزیمم است، اما در تابش ثابت، حول نقطه توان ماکزیمم نوسانات زیادی دارد. روش کنترلی PSO سرعت همگرایی پایینی در پیدا کردن نقطه توان ماکزیمم دارد، چراکه نقاط تصادفی زیادی را برای پیدا کردن دقیق نقطه توان ماکزیمم بررسی می کند. مدل PSO در تابش های ثابت دارای عملکردی مطلوب است و توان خروجی با ریپل خیلی کمتری نسبت به روش IC دارد، به این منزله که روشPSO حول نقطه توان ماکزیمم دارای نوسانات خیلی کمی است. عملکرد روش کنترلی P&O از لحاظ سرعت همگرایی به نقطه توان ماکزیمم، بهتر از عملکرد روش PSO است، اما در مقایسه با روش کنترلی IC، از سرعت همگرایی پایین تری برخوردار است. از لحاظ ریپل حول نقطه توان ماکزیمم در تابش های ثابت، روش کنترلی P&O، در مقایسه با روش کنترلی PSO، دارای نوسانات زیادی است، اما تقریبا مشابه روش کنترلی IC عمل می کند. بر همین اساس با ادغام دو روش کنترلی IC و PSO و استفاده از نقاط مثبت این روش ها، روشی را برای بهبود عملکرد ردیابی نقطه توان ماکزیمم ارائه کرده ایم. در این روش ارائه شده، سیستم کنترلی به نحوی عمل می کند که، در تابش های متغییر روش کنترلی IC را برای ردیابی نقطه توان ماکزیمم به کار بگیرد، چراکه این روش از سرعت همگرایی بالایی برخوردار است، اما در تابش ها و شرایط جوی ثابت و پایدار، روش کنترلی ارائه شده، از روش PSO برای عمل ردیابی نقطه توان ماکزیمم استفاده می کند، چون این روش حول نقطه توان ماکزیمم نوسانات بسیار کمی دارد.