نشریه تحقیقات نوین در سیستم های قدرت هوشمند
سال پنجم شماره 1 (پیاپی 11، بهار و تابستان 1395)

One common problem in power systems is contingencies. Since the system is likely to enter an emergency condition, the various possible failures likely to occur in a system should be evaluated and ranked beforehand and the necessary measures should be accordingly taken so as to cope with such upcoming conditions by the system operator. According to the today’s increase in the use of renewable energies in power systems, a solution that can play a considerable part in reducing the adverse effects of such failures is the purposive use of such production entities for improving the power system security. Thus, the present study deals with the investigation of the methods of maximizing wind farms and their optimal location effects on the improvement of the post-contingency conditions of the system. Meanwhile taking the wind farms’ production power into consideration, the current research tries to find the best location for wind farms in such a manner that they could exert the largest effect on improving the system security. To do so, Particle Swarm Optimization (PSO) algorithm and Monte Carlo Simulation (MCS) using MATLAB are applied and the proposed method has been tested on IEEE-RTS and the numerical results have been analyzed.

Since distribution networks incorporate a large share of the losses in power systems, reducing losses in these networks is one of the most important issues of global networks, including issues that have always been taken into consideration. There are several ways to reduce losses in distribution networks, one of which is the installation of distributed generation units. Renewable sources can supply a clean and smart solution to the increased demands. Thus, Photovoltaic (PV) and Wind Turbine (WT) are taken here as resources of Distributed Generation (DG). Location and sizing of distributed generation have affected largely on the system losses. In this article, Exchange Market Optimization Algorithm (EMA) is proposed for optimal location and sizing of DG based renewable sources for the 69 buses distribution system. The exchange market algorithm on IEEE radial distribution system is simulated and studied using Matlab software and the results of the exchange market algorithm are compared with other algorithms. The results show the effectiveness of the exchange market algorithm in finding the optimal location and sizing of DG to reduce losses and improve the voltage profile.

In this paper, a new structure of Dynamic Voltage Restorer (DVR) based on a mixed modular multi-level inverter (M3I) is proposed, which is capable of compensating for voltage sag, swell and flickers for sensitive loads. The mixed modular multi-level inverter is made up of fewer IGBTs and less circuitry than similar structures. Due to the low number of DC inputs and the lack of electrolyte capacitors in the inverter structure, the control of this inverter is simple to produce the desired voltage. This inverter is made up of three inverters, a single-phase bridge, a triple-inverters, and auxiliary cells to increase the number of line-to-line voltage levels. The inverter also has the ability to produce a number of higher output voltage levels and less harmonic distortion, which makes this structure possible in the power quality compensation grid. The switching method of controlling the closest NLC level in the proposed inverter is used to create the desired waveform. The pre-sag control method was used to control the proposed DVR and use the synchronous reference frame (SRF) method to anomalous detection of grid voltage fluctuations. To investigate and validate the proposed DVR performance, simulations are carried out in the MATLAB / SIMULINK software environment, and the results indicate that the proposed DVR is desirable for optimum performance and performance in voltage sag, swell, and flicker of the power distribution grids.

Increased demand for electrical energy and the lack of development of the transmission network, has made transmission systems, as an intermediary between production and consumption, be more pressed. If the transmission network is not able to correct the desired interactions in the market congestion occurs in the electricity market. If this density is not controlled leading to a rise in market prices and monopolies in sales. One of the effective ways to deal with the issue is the use of FACTS devices such as TCSC, by changing the transmission line impedance, it has the ability to control the power flow of the transmission lines. Therefore, finding the capacity and location of these devices, it is a necessity for power system operators. In this thesis, an optimization method is used to find the number, the installation location and optimal capacity of the TCSC are intended to control network congestion. The goal of the optimization problem is to improve the voltage profile, improve transient stability and reduce operating costs. For this purpose, the Multi-objective particle swarm optimization based on global margin ranking has been used to solve the problem. In this research, several scenarios have been presented to illustrate the effect of adding TCSC to the network. The proposed method has been implemented on the New England Testing System, which has been used for this purpose by the Matlab software environment. The results obtained by the proposed algorithm indicate the accuracy and efficiency of the proposed method.

The usage of scattered sources of production and capacitor banks is increasing due to the development of distribution networks as well as increasing demand for electricity. Discontinued power plants and capacitors, if connected to a power grid in the right place, will have various effects, including loss reduction, improved voltage profiles, and increased network reliability. This dissertation is devoted to reducing losses of the distribution system to the simultaneous optimal location of distributed generation sources and capacitors in radial distribution systems. For this purpose, the sinus cosine algorithm (SCA), which is inspired by simple maths, is used. Simulation on the 69 IEEE bus interfaces. The simulation results show the efficiency of the proposed algorithm in the problem of optimal location of simultaneous distributed generation sources and capacitors in radial distribution systems to reduce losses and improve the voltage profile compared to other optimization algorithms used in this field.

In this paper, the location of the FACTS system in ring power systems with the presence of wind turbines and thermal units has been made. Equipment required by STATCOM and TCSC. Using this equipment can increase the operation of the system. Therefore, the location of this equipment is considered with optimal load distribution. The purpose of optimal load distribution is to minimize the cost of generating power generation. Simulation is implemented by MATLAB software. The gravitational search algorithm has been used to solve the problem and the IEEE 39-channel network has been used to implement the proposed method.