مجله مهندسی برق و الکترونیک ایران
سال هفدهم شماره 2 (تابستان 1399)

In this paper, an improved controller design for a three-phase, four- switch rectifier is designed to balance the voltage of DC capacitors. Today, the four-switch rectifiers have been considered due to the reduction of the two switches to the old six-switch rectifiers. However, the dividing of the same voltage across the capacitors as well as the current balance drawn from the rectifier input is one of the challenges facing these converters. Hence, in this paper, the design of internal and external loop controllers are described step by step. Also, to compensate for the capacitor voltage, the auxiliary signal is added to the internal control loop. Additionally, since the old space vector modulation (SVM) method is unable to control the converter to the purpose of balancing the input current, an improved SVM method is proposed to balance the input current of the converter. The simulation results performed in Matlab/Simulink show that using the proposed SVM method and the auxiliary signal, added to the controller, significantly compensates the capacitor voltage and the converter input current. With sensitivity analysis, it is also shown that the controller is resistant to load variations, output, and input voltage appropriately.

Wireless energy transfer is of high interest, and applications such as RFID, implantable devices, electric vehicles, and charging cell phones are widely used. Power dissipation of power MOSFETs used in these applications affect efficiency of such circuits. In this paper a special method has been used to lower energy dissipation of inverters and replace MOSFETs with energy storing elements in the circuit. In the new method two MOSFETs have been omitted from the inverter bridge circuit. A self-oscillating full-bridge MOSFET-inductor circuit with high efficiency and low power dissipation has been implemented with minimum component. The implemented circuit has 24% efficiency at 20cm distance for energy transfer.

In this paper, a new control method is proposed that it is suitable for half bridge Z-source inverters. Due to extend of half bridge Z-source inverters and lack of a suitable control method, it is necessary to present a control method with capability to generate low frequency output voltage. According to this fact that, the switching pattern of the half bridge Z-source inverters are different because of their topologies and applications, therefore, each switching method create specific conditions in values of voltage and current ripples, voltage and current stresses and design considerations. This paper while propose a new control method for half bridge Z-source inverters, it is presented completely analyses of a half bridge Z-source inverter based on the proposed method. Different conditions to generate shoot through (ST) modes in the proposed method are presented and mathematical relations between duty cycle and modulation index is shown. Finally, in order to reconfirm the theoretical analyses, the simulation results by using PSCAD/EMTDC are presented.

Today, due to the expansion of nonlinear loads, harmonic distortion has increased in power networks and has led to a decrease in power quality (PQ) in them. Regarding to the fact that utilities are responsible for supplying the quality of voltage at the points of sale of electrical energy to customer. Hence, the exact determination of the harmonic contribution of each customer in them is very important. In this paper, a new method based on the crossed frequency admittance matrix is proposed to determine the contribution of each customer on the harmonic distortion of interconnected networks. The basis of this method is the separation of linear and nonlinear load behavior and its effect on harmonic distortion in whole of network. The proposed method is tested in a 5-buses interconnected network, which results show the of the proposed method's accuracy.

The inverter is one of the main components of photovoltaic power plants. Since the power output of the power plant is directly related to the inverter's performance, the inverter losses have an important effect on the generation and efficiency of the photovoltaic plant. The most important of inverter losses are the inverter clipping and inverter efficiency losses. Some factors affecting clipping losses and inverter efficiency are the sea surface height, ambient temperature, input power DC, wind speed, air density, radiation, and so on. Due to the high radiation potential, the wide area, and the variety of climate in Kerman province, in this article, Kerman province has been selected for the installation of photovoltaic power plants and the effects of environmental factors on inverter clipping losses and inverter efficiency are studied in different areas of Kerman. In simulating the effects of several factors such as wind speed, radiation, altitude, ambient temperature, wiring losses, inverter power consumption during operation and at the night, shadow and dust losses are considered. In addition, the effect of the inverter DC to AC ratio on the inverter clipping losses, power generation capacity, and on the capacity factor of photovoltaic plant have been investigated.

Swarm robotic (SR) draws inspiration from nature and is emerged as synthesis of swarm intelligence and robotic. Due to special properties like feasibility, robustness and scalability, swarm robotic has several advantages in comparison to other multi robot systems. In this paper, firstly, SR source of inspiration is introduced, and a precise definition along with desirable properties of swarm robotic is presented. Secondly, SR application domains, well-known projects and simulation environments are reviewed. Thirdly, an overview of various modelling approaches and algorithms is reported. The presented algorithms are divided into task-specific categories. So some of common tasks that could be profitably tackled using swarm robotic can be understood. Finally SR open problems and challenges are discussed. We expect this paper can give a comprehensive view of swarm robotic to researchers.

Single-phase motors are among the most widely-used motors in low-power applications. These motors are omnipresent in residential applications and make up a majority of this sector. Previously these motors were specifically employed in constant velocities. Over time the need for speed control in these motors has brought this problem into focus of many research investigations. Sensorless control of single-phase motors is particularly appealing due to mechanical and economic considerations. In the present paper, one attempts to control motor speed by influencing rotor flux orientation through a vector control method and propose a new method of speed estimation based on extended Kalman filter algorithm. In order to estimate single-phase induction motor speed together with on-line rotor resistance estimation, the measurement noises have been accounted in EKF algorithm. The proposed method is validated with a simulation that includes rotor resistance changes and measurement noise.

Bearings are one of the most important components of an electric machine that are continuously exposed to the electromagnetic and mechanical forces. Vibration caused by various mechanical and electrical faults can impose an irregular rotor-motion in the machine air-gap. In this paper, with the augmented modeling of the electromagnetic and mechanical equations of an induction machine, the dynamics of rotor movement in the air gap are introduced. For this purpose, using the principle of the energy conservation and the Lagrangian theorem, the electromagnetic forces and torques generated from the electromagnetic field of an induction machine are applied by in the mechanical equations of the rotor with three degrees of freedom. Then, the instantaneous position of the rotor in the air-gap and the electromagnetic redial forces on bearing surfaces are identified based on the electrical and mechanical parameters. The numerical analysis is backed up with the experimental results as well in order to validate the accuracy of the proposed model.‎

A significant number of electrical motors producing annually are on the basis of small AC commutating series motor. The application of such motors is more considered in some appliances like vacuum cleaners, mixers, juicer machines, drills and etc. Therefore, regarding the trial and error mechanism, a proper design procedure of such types of electrical machines eventuates to a significant decline in saving the overall manufacturing cost. Hence, in this paper through a smart optimizing method based on particle swarm optimization (PSO) algorithm, a design consideration for an universal AC commutating series motor is presented. By the definition, a combination of geometric parameters and operating point of motor is used as the cost function of the proposed optimizing method. Here, in order to show the effectiveness of the proposed method, the overall optimizing results derived from the PSO algorithm will be compared with its counterpart based on Firefly algorithm. Also, to further confirm the obtained results from the proposed designing procedure, the design of a sample universal motor is implemented into the two-dimension Maxwell software with a contribution of finite element analysis. The simulation results show the robustness and high flexibility of the proposed method.

Readiness of power systems to cope with emergencies, especially those of sabotage origins, can improve the resiliency and minimize the restoration cost and time. In the current paper, in a tri-level robust decision making framework, system operator (SO) schedules the power generation for a base case in the upper level while a rational attacker tries to disrupt the most sensitive substation and consequently the connected generation units and transmission lines which leads to maximum load shedding in the middle level. Meanwhile, the SO once again tries to minimize the load shedding by redispatching the generation fleet in the lower level. In addition, in power systems with high wind penetration rates the SO should also consider the impacts of wind generation uncertainty for a more realistic robust scheduling. In contrast with two-stage robust methods with full recourse which immunize solutions against worst economic scenario (over-conservative solutions), the proposed column and constraint generation (CCG)-based model tries to find the base case solution while ensuring that in case of malicious attacks or wind realizations the solution can be adaptively adjusted with least load shedding. The performance of the proposed model is examined in 118-bus IEEE test system.

In this paper, a new day ahead energy management system is proposed for a smart grid in which distribution company and residential customers are involved. The interaction between customers and the distribution company is modeled as a single leader-multiple followers Stackelberg game. The leader of Stackelberg game is the distribution company which calculates the price of energy by maximizing its profit in a stochastic optimization framework. The residential customers, who are the followers of Stackelberg game, consider the common constraint of maximum aggregated load regulating in their optimization problem and thus play a general Nash game with each other. It is proved the customers’ general Nash game is strongly monotone and consequently has a unique equilibrium. To achieve the unique Stackelberg equilibrium, the best response-based energy management algorithm is devised, and its convergence condition is proved. It is also proved that the Stackelberg equilibrium is an optimal social equilibrium, in which the sum of customers’ cost is minimized, and the profit of the distribution company is maximized. The proposed energy management mechanism decreases the maximum aggregated load by 21.89% and increases the load factor by 27.72%.

One of the important issue in isolated microgrid is load-frequency control. This paper proposes a fractional order PID (FOPID) controller for load-frequency control of microgrid by considering nonlinear factors of Distributed energy resources. The parameters of FOPID are optimized using hybrid Craziness-based Particle Swarm Optimization (CRPSO) and Pattern Search (PS), which the first is used for global search and the other is used for local search. The simulation is carried out in MATLAB/SIMULINK environment. Different senrios are simulated for studying the effects of different disturbances such as load changes (in step form), changes of output power of photovoltaic and wind turbine generators, all with and without considering parameters uncertainties. The results shows the better performance of the proposed controller as compared with fractional order PID (FOPID) and PID, which is optimized by optimized by particle swarm optimization, and fuzzy PI, which is optimized by particle swarm optimization.

In this paper, a Real Time Pricing (RTP) design is proposed for Demand Response Programs (DRP) that it increases the benefit of the consumers and Load Serving Entity (LSE), in addition, improves the load factor (LF) of the network. It is possible for consumers to buy their energy from the retail market or participate in the LSE scheme and they will be paid the LSE price. The LSE ensures consumers that the dynamic price determined is less or equal to the retail price to encourage consumers to participate in the proposed scheme and maximize its profits. On the other hand, The LSE is tried to design prices that prevent a new peak demand. The proposed model is modeled as a multi-objective and bi-level optimization. The upper level of optimization is multi-objective, and it maximizes the LSE benefit and improves the network load factor. The benefit of customers is modeled in the lower level of this problem. The proposed model is solved using GAMS software and the results show the efficiency of the proposed model.

In this paper, a new approach is proposed for optimal bidding of strategic units in day ahead energy market and market clearing process. This method describes the multi objective scheduling of strategic units that is going to maximize its profit in presence of rivals and minimize its emission. In order to achieve this goal, a bi-level mathematical optimization model with equilibrium constraints Is provided. The first level maximizes the profit of strategic units and the second level maximizes the level of social welfare. The bi-level model is converted to a mixed integer linear programming model using a duality theory and Karush-Kuhn-Tucker (KKT). Another goal is to solve the bi-level problem in a multi-objective method using augmented Epsilon constraint method in order to maximize profit of linearized model and reduce the emission of strategic units. Finally, the best answer is selected using fuzzy decision method. The power transmission distribution factor (PTDF) method has been used to model the network structure.

During recent years, increment of incentives for deliberate subversive activities against power systems along with the restrictions on the allocation of financial resources for protection of these infrastructures have absorbed significant attentions of researchers toward the necessity of optimal allocation of these finances; and such the way, to minimize damages and consequently energy not supplied in case of future events. Planners of subversive activities as fully strategic actors target those low probability events which are no considered in protection schemes to maximize quantity of damages to power system. In this study, a new game theory based scheme is proposed in form of a zero sum playoff in order to provide an optimal allocation strategy. In this paper, two budget allocation algorithms have been presented to protect transmission lines and substations against deliberate threats. In the first algorithm, allocation of a certain amount of annual funding to transmission lines and substations is formulated with the aim of attaining the best possible condition of power grid in term of system reliability; while, required budget and procedure of allocation of this budget to targeted system utilities against undefined strategy of malicious individuals are calculated in second algorithm, in order to reach a predefined level of system reliability. Proposed model is implemented employing MATLAB (i.e. to execute single-objective Cuckoo optimization algorithm as well as multi-objective non-dominated sorting genetic algorithm II) and GAMS (i.e. to determine reliability of grid by use of power system load flow) software. Totally, optimized game strategy of protectors to acquire the best condition of system reliability has been obtained. Results validate effectiveness and applicability of proposed method in cases of optimality of allocation technique and subsequently increase of reliability indices.