Mohammadmehdi Seyedmahmoudian

Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.

Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: a particle swarm optimization technique

Partial shading is one of the unavoidable complications in the field of solar power generation. Although the most common approach in increasing a photovoltaic (PV) arrays efficiency has always been to introduce a bypass diode to the said array, this poses another problem in the form of multi-peaks curves whenever the modules are partially shaded. To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (MPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This study aims to employ an evolutionary algorithm technique, also known as particle swarm optimization, in MPP detection.

Structure and Thickness Optimization of Active Layer in Nanoscale Organic Solar Cells

This paper presents the development of a two-dimensional model of multilayer bulk heterojunction organic nanoscale solar cells, consisting of the thickness of active layer and morphology of the device. The proposed model is utilized to optimize the device parameters in order to achieve the best performance using particle swarm optimization algorithm. The organic solar cells under research are from poly (3-hexylthiophene) and [6,6]-phenyl C61-butyric acid methyl ester type which are modelled to be investigated for performance enhancement. A three-dimensional fitness function is proposed involving domain size and active layer thickness as variables. The best results out of 20 runs of optimization show that the optimized value for domain size is 17 nm, while the short-circuit current vs. voltage characteristic shows a very good agreement with the experimental results obtained by previous researchers.

Designing precision fuzzy controller for load swing of an overhead crane

AbstractIn this paper, a fuzzy logic controller is designed and proposed for controlling load swing of an overhead crane. To consider a complete model of the plant, the quadratic derivative of state variables is added to the conventional model which causes an extra weighting. The aim of the controller designed is to keep the load angle (ϕ) zero, all the time, which means no physical swinging in the load’s position. The results obtained are compared with the optimal control method, as one of the well-known control techniques, to verify the designed controller. The results show that the designed fuzzy controller is able to dampen the oscillations in the load swing angle and load’s angular velocity, in a reasonable time.

A comparative study on procedure and state of the art of conventional maximum power point tracking techniques for photovoltaic system

Due to the increasing world energy demand, renewable energy systems have been significantly applied in the power generation sector. Among the renewable energy options, photovoltaic system is one of the most popular resources which has been experiencing a huge attention during recent decades. The remarkable advantages, such as static and movement free characteristics, low maintenance costs, and longevity are the primary factors for the popularity of solar generation in the late years. Nevertheless, the low PV conversion efficiency in one side and high PV material cost in the other side have made PV generation comparably expensive system. Consequently, a capable maximum power point tracking (MPPT) is all important to elicit the maximum energy from the production of PV systems. Different researches have been conducted to design a fast, simple and robust MPPT technique under uniform conditions. However, due to the series and parallel connection of PV modules and according to the use of bypass diodes, in the structure of PV modules, a conventional techniques are unable to track a true MPP. Recently, several studies have been undertaken to modify these conventional methods and enable them to track the global MPP under rapidly changing environments and partial shading (PS) conditions. This report concentrates on the state of the art of these methods and their evolution to apply under PS conditions. The recent developments and modifications are analyzed through a comparison based on design complexity, cost, speed and the ability to track the MPP under rapid environmental variations and PS conditions.

Optimum design and analysis study of Stand-alone residential solar PV Microgrid

Todays power system network has become more complex and it has more responsibilities and challenges to provide secure, reliable and quality energy supply to the communities. A small entity of electrical network known as Microgrid (MG) is more popular nowadays to enhance reliablity and secure level of energy supply, in case of any energy crisis in the utility network. The MG can also provide clean energy supply by integrating renewable energy sources effectively. The MG with small scale solar photovoltaic (PV) power system is more suitable to provide reliable and clean energy supply for remote or urban communities in residential level. This paper presents the basic analysis study of stand-alone solar photovoltaic (PV) MG power system which has been developed with the aid of Matlab-Simulink software, on the basis of residential load profile and solar exposure level in a particular area of Geelong, Victoria State. The simulation result depicts the control behavior of MG power system with optimum sizing of PV (4.385 kW)and battery storage (480 Ah/48V) facility, fulfills daily energy needs in residential load level. This study provides a good platform to develop an effective and reliable stand-alone MG power system for the remote communities in the near future.

Low cost MPPT controller for a photovoltaic-based microgrid

Photovoltaic based microgrid have been increasingly investigated in recent years, ascribable to their fundamental advantages such as the infinite energy source, environmentally friendly aspect and low upkeep cost. However, in practice, they are still considered as an expensive and low output option of renewable energy resources. To extract the maximum possible power from the output of the PV system, a reliable maximum power point tracker (MPPT) is required. Numerous studies have been conducted to introduce the best MPPT techniques suitable for different types of PV systems. However, they are mostly able to track the MPP from the PV system when the output signals (Voltage and Current) of individual array are available. In this study, a meta-heuristic method, based on particle swarm optimization theory, is used to determine the actual MPP of PV system, including several PV arrays, by only single current sensor at the output terminal. The results of the proposed PSO based technique, for tracking the global MPP in a multidimensional search space, have been presented at the end of this paper.

Using particle swarm optimization for PID optimization for altitude control on a quadrotor

The proportional-integral-derivate (PID) controller has been relied on by control engineers due to its easy implementation and good performance. Although PID controllers are readily available, they still have limitations. Tuning these controllers often require a deep understanding of control theory to adjust their parameters correctly, which is often time consuming and may not result in an optimal performance. In this study, the use of particle swarm optimization (PSO) is proposed to improve a PID controller on a quadrotor. The PID controller is used to control the height of the quadrotor. Moreover, a simulation run in MATLAB is constructed to increase the height of the quadrotor from 0 m to 1 m. The PSO algorithm is used to tune the controller against a cost function that considers the squared error, maximum overshoot, and the integral of absolute error, which are used to evaluate the performance of the PID values. The PSO should converge on a global minimum, which will be the optimal values of the PID controller. Results from the simulation reveal the performance of the PSO algorithm and the efficiency of the PID controller compared with other methods.

Building a Relationship between Robot Characteristics and Teleoperation User Interfaces

The Robot Operating System (ROS) provides roboticists with a standardized and distributed framework for real-time communication between robotic systems using a microkernel environment. This paper looks at how ROS metadata, Unified Robot Description Format (URDF), Semantic Robot Description Format (SRDF), and its message description language, can be used to identify key robot characteristics to inform User Interface (UI) design for the teleoperation of heterogeneous robot teams. Logical relationships between UI components and robot characteristics are defined by a set of relationship rules created using relevant and available information including developer expertise and ROS metadata. This provides a significant opportunity to move towards a rule-driven approach for generating the designs of teleoperation UIs; in particular the reduction of the number of different UI configurations required to teleoperate each individual robot within a heterogeneous robot team. This approach is based on using an underlying rule set identifying robots that can be teleoperated using the same UI configuration due to having the same or similar robot characteristics. Aside from reducing the number of different UI configurations an operator needs to be familiar with, this approach also supports consistency in UI configurations when a teleoperator is periodically switching between different robots. To achieve this aim, a Matlab toolbox is developed providing users with the ability to define rules specifying the relationship between robot characteristics and UI components. Once rules are defined, selections that best describe the characteristics of the robot type within a particular heterogeneous robot team can be made. A main advantage of this approach is that rather than specifying discrete robots comprising the team, the user can specify characteristics of the team more generally allowing the system to deal with slight variations that may occur in the future. In fact, by using the defined relationship rules and characteristic selections, the toolbox can automatically identify a reduced set of UI configurations required to control possible robot team configurations, as opposed to the traditional ad-hoc approach to teleoperation UI design. In the results section, three test cases are presented to demonstrate how the selection of different robot characteristics builds a number of robot characteristic combinations, and how the relationship rules are used to determine a reduced set of required UI configurations needed to control each individual robot in the robot team.

Viable approaches for increasing the efficiency of buiding integrated photovoltaic systems

Nowadays, there is growing interest towards the area of building integrated photovoltaic (BIPV) systems and PV microgrids (MGs) in the field of power generation and distribution systems. This is mainly due to the higher adaptability and compatibility of these systems with preplanned sustainable development strategies in the most urban areas. The quiet operating process and movement free characteristic of photovoltaic systems brought them to the roof tops of the buildings in urban and rural areas and made them the most demanded means of renewable energy systems. This study highlights the problems affecting the performance and efficiency of BIPV systems and presents miscellaneous solutions and recommendations to solve these problems.