مجله کیفیت و بهره وری صنعت برق ایران
سال ششم شماره 1 (پیاپی 11، بهار و تابستان 1396)

Privatization of power sector and establishment of competition in power supplying process, raised unprecedented challenges in power system operation and planning fields, such as preventive maintenance scheduling which was formerly, in traditional environment, managed centrally by dispatching center. Dispatching center role having been changed in restructured power systems, power producing companies play a more important role in PM scheduling process. The conflict between dispatching center being concerned about power system reliability and stability, and power generating companies profit maximization based behavior which cannot be defined properly thorough traditional optimization theory, may be modeled satisfactory thorough Game theory approaches. In this paper, after modeling and solving PM scheduling process thorough game theory, discusses about resultant equilibrium states and predicts different power generation technologies behavior.

Adaptive protection coordination which realizes using communication links is an efficient method to solve problems in microgrid protection coordination. An issue that can affect the efficiency of this method is uncertainty in communication links. In order to evaluate the effectiveness of uncertainty in communication links on adaptive protection and reliability of microgrids, a new Markov Chain Monte Carlo (MCMC) is proposed. In the proposed method, the probability of correct operation of circuit breakers (CBs) and communication links is not considered to be constant; it can vary according to the fault current flowing through CBs and the latency of communication links, respectively. The performance of the proposed method is tested on a sample microgrid equipped by central server and communication links. In order to assess the impact of uncertainty in communication links on the reliability of the microgrid, System Average Interruption Duration (SAIDI), Expected Energy Not Supplied (EENS), and Expected COST of Interruption (ECOST) indices are used. Results prove that the traditional protection coordination schemes have more effectiveness of the uncertainty in communication links compare to schemes which use global decisions.

Considering to advantages of renewable energies as Distribution Generations, are applied so widely in all over of the world. In this paper is attempted to usage of these resources with power system to provide the consume power of electrical trains, but to reason of single phase power supply of electrical trains in 25 KV AC power systems and varying consuming power during time and distance, make power quality problems in upstream power systems. So purpose of paper is decrease of unbalance, cancel of current harmonics and achievement to unity power factor from upstream grid in spite of providing consume power of trains, these are achieved by implement of Instantaneous Power Theory on control of inverters interface Flexible Distribution Generation and upstream grid.

In this paper, a heuristic algorithm is proposed to calculate the optimum rating of dynamic voltage restorer (DVR) in an interline DVR (IDVR) considering load variations in feeders. Due to the limitation of active power exchange between DVRs in an IDVR, selection of the appropriate voltage for each DVR in an IDVR should be such that, first, voltage sags in each of the feeders are compensated, and second, IDVR rated kVA and total cost are reduced. For this purpose, an optimization problem in previous studies was proposed to select the rated voltage of DVRs in an IDVR. In that problem, feeder load is assumed to be constant and equal to the rated values, while load variations in feeders affect active power exchange between the DVRs and their injected voltages. Therefore, load variations in feeders in the optimum design of IDVR must be considered. This is the main contribution of current research. Given that in practice the number of time intervals in load curve is high, the solution space of optimization problem will be very large and search the entire solution space is not possible. Thus, in this paper by proposing a convenient strategy based on PSO and GA methods sum of rated kVAs of DVRs is minimized. Furthermore, to demonstrate the capability of proposed method, a comparison with the results of the search of the entire solution space is done.

High consumption of electric energy in urban railway systems have prompted many researchers to look for strategies of energy saving. Suitable service with high speed and accuracy is what passengers, as the main costumers of these systems, anticipate. In this regard, energy-efficient train operation due to its considering energy saving and punctuality simultaneously, is very important. In this paper, a solution for energy saving is proposed, so that the constraints related to traveling time are met. Meanwhile, the effect of employing variable regenerative energy recovery rate for each inter-station distance was shown in reducing total input energy of network. This work is conducted over a two-stage optimization process. First, considering the net energy of train and inter-station trip time as the objective functions, optimal speed profiles were provided for single train system. Then, by distributing traveling time over the inter-stations and using predetermined optimal speed profiles, the total input energy of the upstream network is minimized. The simulation results, based on actual operating data of line 1 Mashhad urban railway system confirm the effectiveness of proposed method.

Power continuation of vital loads is one of the most important feature of self-healing smart grid. It is desired to charge the batteries of Electric Vehicles (EVs) whenever they can be connected to the grid in order to have more energy reserved in the case of emergency. However, this method of charging can deteriorate the load curve, and has several other side effects. Therefore, using the vehicle-to-grid (V2G) for this purpose can be challenging. A multi-objective optimization is formulated that assigns the charging times of EVs in a smart grid by considering two goals; maximizing of energy stored in EVs and minimizing the standard deviation (SD) of the grid load curve counting the charging load. Uncertainty of arrival time, departure time and state of charge at arrival time of EVs are considered. In order to decrease the number of variables of optimization problem in case of high penetration of EVs, the EVs are clustered with statistical methods. The proposed optimization method is based on the artificial immune system algorithm (AISA). Simulation studies are performed on the IEEE 37-bus benchmark, showing that AISA provides better solutions compared to those of the genetic algorithm, as enough energy is stored in EVs while the SD of the load curve is better.

Excessive transient inrush current of the power transformers has some negative impacts such as: transformer lifetime reduction, mal-operation of the relevant protections, and power quality degradation. In some cases, the energization impact on power quality may lead to catastrophic damages to the system such as offshore stations. Therefore, suppression of inrush current is vital in such applications.
In this paper, a new Solid-State Inrush Current Limiter (SSICL) is proposed for medium voltage power transformers with the capability of integration with already existing circuit-breakers. The proposed SSICL consists of three similar sets of bidirectional semiconductor switch and an inrush current limiter resistor. Using a Kalman Filter based strategy, transformer inrush current is suppressed during magnetization process. In fact, built up profile of the inrush current is dictated in accordance with the estimated current by a slow dynamic Kalman filter. The proposed SSICL is simulated in MATLAB-SIMULINK and a single-phase experimental prototype of the limiter is implemented. The proposed control scheme was implemented using dsPIC30F4011. In order to evaluate the performance of the SSICL, some experiments were carried out. Simulation and Experimental results show that the proposed SSICL can considerably suppress inrush current of the transformer.

A dual stator winding squirrel cage induction motor (DSWIM) is a brushless induction motor that it has two separate stator windings wound for a dissimilar number of poles. Each stator winding is fed by an independent three-phase inverter. The main purpose of this paper is reducing the power losses of the inverter units at low speeds. This purpose is achieved by maintaining motor standard mode at low speeds using the idea of rotor flux compensation. In this paper, the flux estimation problem is solved via this idea. Unlike the conventional method, DSWIM is fed by two frequencies that are in the same ratio as the pole number. Therefore, the power losses of the utilized inverters are also reduced to a considerable extent. The proposed methods are simulated in MATLAB/Simulink software, and the results of simulation confirm the assumptions.

Nowadays microgrids have been widely considered due to their economic and technical features. The most important feature of microgrid is its flexibility which means microgrids are be able to operate in both grid-connected and islanded operation modes. This paper presents a bi-level scheduling model for optimal operation of an integrated microgrid between grid-connected and islanded modes by using Benders decomposition method. Also a neighbor microgrid is considered in the model and it is assumed that the main microgrid enables to exchange energy with its neighbor in the islanding mode. The proposed model consists of a master problem for the grid-connected operation mode and a sub-problem for the islanding operation mode. The objective function of the master problem minimizes microgrid operation cost including cost of fuel, start up, spinning reserve as well as purchasing power from main grid or neighbors. However, the objective function of the sub-problem investigates whether the power generation of the microgrid is enough or the loads can be supplied continuously in the islanding mode of microgrid. Uncertainties of distributed energy sources, energy price and load are modelled by two-point estimate method.