نشریه مهندسی برق و مهندسی کامپیوتر ایران
سال بیست و یکم شماره 2 (پیاپی 78، تابستان 1402)

The increasing rate of distributed generation resources expansion into power systems and the random nature of these resources have altered the operation and design of these networks, and reactive power management in distribution networks belongs to this category. The use of these resources in distribution networks is not without challenges and the lack of optimal management of reactive power may not bring economic efficiency for the network. Energy storage systems have the potential to solve this problem. Therefore, in this article, reactive power management in a microgrid connected to the main grid, taking into account distributed generation sources, energy storage systems and discrete reactive power compensating equipment, including capacitor banks, taking into account uncertainty in network load and Wind and solar power generation has been done. Finally, the efficiency of the method is demonstrated by numerical examinations on the distribution networks of 33 and 69 IEEE buses and in the GAMS optimization software.

False data injection attack (FDIA) is a destructive cyber threat to the economic performance of electricity markets in smart grids. A cyber attacker can make a huge financial profit by implementing an FDIA through penetrating the virtual transactions of the electricity markets and manipulating electricity prices. In this paper, a new approach to planning an absolutely stealthily FDIA is presented with the aim of achieving maximum financial profit from the perspective of a cyber attacker participating in virtual transactions from two markets of day-ahead (DA) and real-time (RT). A common hypothesis in studies of FDIAs against electricity markets is that the attacker has complete information about the smart grid. But the fact is that the attacker has limited resources and can hardly access all the network information. This paper proposes a robust approach in designing an attack strategy under incomplete network information conditions. In particular, it is assumed that the attacker has uncertainties about the network modeling matrices. The validity of the proposed method is evaluated based on the IEEE 14-bus standard system using the Matpower tool. Numerical results confirm the relative success of the proposed attack in cases of varying degrees of incomplete information.

So far, comprehensive and extensive studies have been conducted on the brushless DC motor (BLDC), and a part of these studies focuses on the estimation of the parameters of the transfer function of this motor. Estimation of BLDC motor transfer function parameters is essential to study motor performance and predict its behavior. Therefore, an efficient, accurate and reliable parameter estimation method is needed. In this article, the problem of estimating the parameters of the transfer function of the inverter-fed BLDC motor set has been solved using particle swarm algorithms (PSO). The results of using this algorithm have been compared with the results of other optimization algorithms. The comparison of these results has shown that the PSO algorithm is an efficient, accurate and reliable method for solving the transfer function parameter estimation problem.

Doze and sleep mechanisms are the most common energy-saving solution in GPON networks. Sleep duration is the critical value in the energy-saving domain, and it will affect the QoS metrics with inappropriate value. In this paper, a new energy-saving mechanism is proposed using an optimal point based on gradient descent that calculates sleep duration and keeps QoS metrics acceptable. The historical value of average delay and packet, drop ratio, ONU buffer, and bandwidth request parameters are used as input, and the sleep duration value is calculated. The simulation results show that the proposed method saves up to 17% energy in GPON and keeps the network’s QoS in an acceptable domain.

Lithium-ion batteries are extensively used in fast charging stations because of their high density of energy storage and power. It is critical to know how to charge lithium batteries since their structure is very sensitive to heat. When using fast charging techniques for charging batteries, considerable heat is generated. This heat is caused by the ohmic losses of the battery and its internal reactions. While fast charging reduces the charging time of the battery, it may damage its structure. There are various methods of fast charging. Each has its advantages and limitations. By applying changes to the multi-stage constant current charging method, in addition to reducing the charging time, attempts were made to prevent damage to the battery. This improved method can deal with cases where temperature effects are removable, such as when there is a ventilation system. It minimizes charging time as much as possible.

The 5G network has been created to solve the limitation of communication coverage in large areas. One of the challenges of the 5G is the construction of quadrature oscillators in a wide range of high frequencies. Phase error and amplitude imbalance cause a decrease in the image rejection ratio (IRR), which affects the communication error vector magnitude (EVM). The quadrature phases are generated by a one-stage poly-phase filter (PPF) whose resistors consist of four N-type MOSFETs in triode mode, each of its four gate ends is set by a voltage. The feedback circuit constantly adjusts the center frequency of the PPF according to the input frequency by changing the resistance of the MOSFETs. In this research, the circuit is simulated in the advanced design system software environment in the frequency range of 2 to 6 GHz with a central frequency of 4 GHz, which has reduced the quadrature phase error to less than 1 to 9 degrees. Then, the governing mathematical equations of the circuit were extracted and the network function of the circuit was designed in the Simulink MATLAB environment. The main advantage of the Simulink method is the high speed of simulation.