نشریه مهندسی برق و مهندسی کامپیوتر ایران
سال دوازدهم شماره 1 (پیاپی 34، بهار 1393)

Identification and classification of power quality disturbances (PQDs) are one of the most important functions of monitoring and protection of modern power systems. One of the most important issues in PQ analysis is automatic diagnosis of waveforms using an effective algorithm. This paper presents an effective method, for extracting features, using integration of discrete wavelet transform (DWT) and hyperbolic S transform (HST). Moreover, an efficient feature selection method namely Orthogonal Forward Selection (OFS) by incorporating Gram Schmidt (GS) procedure and forward selection is applied for selection of the best subset features. Multi support vector machines (MSVM), as famous classifier, is applied. Also, the variable parameters of the classifier are optimized using a powerful method namely particle swarm optimization (PSO). Six single disturbances and two complex disturbances as well pure sine (normal) selected as reference are considered for the classification. Sensitivity of the proposed expert system under different noisy conditions is investigated. Also, efficiency of the proposed methods by comparing the results of this study with the results of other papers is examined.

With the decreasing of the fossil fuels and increasing of the environmental pollution, using of renewable energy resources is growing rapidly. On the other hand, the restructured electricity industry causes to cooperation of the distributed generation resources in the competitive electricity market. In such situation, the presence of the wind farms in the power system in order to provide the system loads is quite favorable. However, wind farm generation depends on the wind speed and the uncertainty in the generation cause to some concerns about the connection and operation of the power system. So, in this paper, a probabilistic approach for small signal stability analysis with considering the wind farm generation uncertainty based on PCM method is proposed. The PCM method is based on the orthogonal polynomials which provide a linear model for desired output. The continuous changes of the wind farm generation level cause to variation on the operating point that the control equipment parameters should be adjusted based on the new operation conditions. Therefore, genetic algorithm and the approximate models which are obtained from the PCM method are used. In order to validate the proposed method, the IEEE 10-machine and IEEE 16-machine test system are used.

Many embedded systems and mobile devices use batteries as their energy suppliers. The lifetime of these devices is thus dependent on the battery behavior. Accordingly, battery management besides reducing the energy consumption of the respective system helps to increase the efficiency of such systems. Maximizing the battery lifetime is a quiet challenging problem due to the nonlinear behavior of batteries and its dependence on the characteristics of the discharge profile. This paper employs dynamic voltage scaling (DVS) to extend the lifetime of battery-operated real-time embedded systems. We propose a battery-aware scheduling algorithm to maximize the lifetime and efficiency of the battery. The proposed algorithm is based on greedy heuristics suggested by battery characteristic and power consumption of tasks to employs DVS. Two methods are used to evaluate the mentioned algorithms; the first one is based on the cost function derived from a high-level analytical model of battery, and the second one is based on Dualfoil, a low-level li-ion battery simulator. Experimental results show that the system lifetime can be increased about 4.3% to 19.6%in various situations (in terms of system workload and tasks power consumption).

Distribution system companies (DISCOs) can reduce their cost by reconfiguration as the economic way for loss reduction. This paper presents a new method for reducing DISCO costs in deregulated environment by loss reduction and power generation control of Distributed Generators (DGs). Because of changing the price of energy in this environment, different network load levels with different prices were considered. This complex optimization problem is solved by a new method based on shuffled frog leaping algorithm (SFLA). Also, influence of DG presence on objective function and load flow is considered. The proposed method is applied to IEEE 33-bus and 69-bus test systems to decrease the activity cost of DISCO in deregulated environment and its capability relative to other methods is shown.

In this article, we designed a novel monolithic integrated optical transceiver based on the ring resonator structure on semi-insulating InP substrate at 1.55 μm wavelength. To separate the incoming continuous (λ2) and modulated (λ1) optical waves from the network, an optical ring resonator is utilized. The ring resonator has the p-i-n layer stack that also detects the incoming modulated optical wave (λ1). The continuous optical wave (λ2) is guided to the ring-resonator based modulator where it is modulated and finally directed toward a pair of ring resonator to reflected back to the network. Channel spacing between λ1 and λ2 is 200 GHz (1.6 nm) at wavelength ranges of 1520 to 1570 nm. This transceiver can illustrate a 40 GHz bandwidth.

In competitive electricity market, maximizing the profit is the main objective in company’s decision making. Hence, Transmission companies (Trans Cos) are not interested in improving reliability and expanding existing structures without financial benefits. On the other hand, consumers demand more reliable and high quality power. In this paper, transmission insurance plan is proposed as an incentive method to improve the reliability of electrical power transmission. In this method, an insurance contract concluded between insurance company and every customer. Insurance company spend a part of its revenue to increases the reliability of the transmission system and also pays for compensation of consumers not supplied energies. The proposed method is studied in a network with six buses. Results show that the proposed method increases network reliability.

In this paper a joint energy and reserve market with transmission switching considering dynamic constraints has been proposed to minimize the cost of supplying load, reliability expenses and avoidance of transient instability in line switching.Transmission switching is used during contingencies and steady state to determine optimal required energy and reserve values. To investigate the efficiency of the proposed strategy IEEE 14 bus test is studied. According to the obtained results, this strategy decreases energy and reserve marginal prices, as well as reliability cost.