NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ
Year:2020 | Volume:17 | Issue:4 |Papers Count:8

The majority of the power transformers failures are caused by the thermal stresses under abnormal operating conditions, such as harmonic loads. Therefore, it is of great interest to determine the temperature distribution inside the power transformers. In this paper, a new thermal equivalent circuit is presented by which the temperature in different regions of the transformer is estimated under harmonic loads. Also, the three-dimensional Finite Element (FE) Model of the power transformer is developed to calculate the power losses in each part of the transformer that are considered as the heat sources in the proposed equivalent circuit. The computed hotspot and average oil temperatures are compared with those obtained from IEEE Std C57. 91 method, thereby the accuracy of the proposed method for calculating the temperature rise due to harmonic loads, is investigated. Finally, derating of the power transformer is discussed under harmonic loads.

In this paper, an adaptive non-singular terminal sliding mode control based on disturbance observer is proposed for detection process and control of the micro-electromechanical vibratory gyroscope stimulation process. For this purpose, the dynamical equations of the vibrational gyroscope system are initially expressed. In the following, the dynamical equations of this system are transmitted to the domain of state-space equations and then to the domain of tracking error. After that, the dynamic structure of the finite time disturbance observer is presented. Then, the design of the adaptive non-singular terminal sliding mode control based on finite time disturbance observer is expressed. The proposed strategy carries out the control of the stimulation process in the presence of structured and un-structured uncertainties existing in the dynamic equations of the microelectromechanical vibrational gyroscope system, and performs the detection process through only an adaptive law. The mathematical proof shows that the closed-loop system with the proposed control, and in the presence of the existing uncertainties, has the finite time global asymptotic stability. The presence of a disturbance observer in the proposed control structure will weaken the role of un-structured uncertainties in the gyroscope control process and reduce the control input amplitude. In order to evaluate the proposed control performance, simulations in 3 steps are implemented on the electromechanical vibrational gyroscope system. Simulation results confirm the desired performance of the proposed control.

In this paper, a new wide-input-wide-output non-isolated buck-boost DC-DC converter is presented. The proposed converter has continuous current and is able to buck and boost the input voltage with shorter duty-cycles of the power switch compared to conventional buck-boost converters. A smaller duty cycle for a given voltage gain translates to lower current ripple of the inductors, reduced conduction losses, alleviated voltage stresses of the semiconductor switches and improved overall efficiency. The proposed converter also benefits from a simpler structure and control scheme. In this paper, the steady state operation of the proposed converter is investigated under both continuous conduction mode (CCM). The simulation and experimental results confirm the validity of theoretical analysis as well as the proper performance of the proposed converter.

The steady state error in voltage amplitude and frequency and improper reactive power sharing are main disadvantages of droop control in primary level of control of distributed resources (DERs) in microgrid. Secondary control can compensate these problems. In contrary to centralize control, distributed secondary control may bring merits such as reliability, flexibility and scalability improvement. The distributed secondary control is usually implemented using consensus algorithm whose communication network is very important. Communication network is usually modeled continuously with a constant transfer rate. In this paper, the consensus algorithm with communication network are implemented in discrete domain because of discrete nature of them. Two aperiodic data transfer strategies state dependent and state independent are also proposed for releasing communication network burden where data rate is not fixed. Time delay as a non-desirable effect is evaluated. The proposed method applied on an islanded microgrid, and simulation results show the effectiveness of the proposed method.

Power system stabilizer (PSS) does not have a significant impact on inter-area modes and FACTS devices are used to damping these modes and to enhance power system stability. In this article, an objective function based on different and variable weight coefficients according to eigenvalues condition is proposed and optimization parameters of power system stabilizer and variable impedance parameters include static VAR compensator (SVC) and thyristor controlled series capacitor (TCSC), (Including amplifying gain rate and time constant of phase-compensating blocks) is done using genetic algorithm in harmony. Also, in the process of optimization, the location of the FACTS devices and the control signal are considered as optimization parameters. Simulation results on IEEE 68-bus system show improvement damping of inter-area modes using the proposed method.

The purpose of distribution networks restoration is to re-energize the out-of-service loads after fault occurrence which is accomplished by changing the status of network switches and considering the network constraints. In this paper a multi-stage restoration method by the help of the modified decision-making tree algorithm is proposed to maximize the restored loads and also to minimize switching operations. The main stages of this method include initial restoration, reconfiguration and optimal load shedding. To reduce the search space, the network switches are categorized into different sets which avoid having any inappropriate result space. The proposed method is tested on two IEEE 69-bus and 119-bus distribution networks. The simulation results confirm the accuracy and efficiency of the proposed method in distribution network restoration.

In this paper, the optimal allocation of battery energy storage in the distribution network is performed for peak shaving and maximizing profitability. To this end, indicator shave been introduced using hourly load information, feeder upgrade cost and electricity sales price to various tariffs. Then, using the Analytic Hierarchy Process (AHP), the indicators are weighted and a suitable feeder is indicated for installing energy storage. Then, to achieve the maximum possible peak shaving and maximize profit, an economic objective function is defined to determine the optimal sizing and charge-discharge of the energy storage. The objective function includes the investment and operating cost of battery energy storage and the profits of energy arbitrage, deferring facility investment, environmental issues, and reducing the upstream access cost. Appropriate constraints are considered according to the peak shaving, range of battery power and energy capacity as well as balance in the amount of charge and discharge. Due to the nonlinearity of the objective function, the components involved in the nonlinearity of the objective function are determined according to the heuristic algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Tabu Search (TS)) and then the objective function is solved by the Interior-point linear programming. The results provide the most suitable battery type and optimization method among the introduced batteries and methods while fulfilling the objectives.

Lateral vehicle’ s control with constant longitudinal velocity using adaptive dynamic programming, backstepping and zero-sum games theory is investigated in this paper. The nonlinear dynamics is considered and the steering torque is chosen to be the control input instead of the steering angle. At first, a subsystem is created by augmenting the lateral vehicle’ s dynamics with lane keeping ones considering the steering angle as the control input and the road curvature as a disturbance. Utilizing adaptive dynamic programming, neural networks and zero-sum games theory, the optimal control law is obtained and then, the results exerted on the second subsystem which is the dynamics of the steering angle and a control law is captured for which using the backstepping control method. Finally, performance of the proposed algorithm is demonstrated by applying it on a typical vehicle model.