فهرست مطالب حسین شایقی

This paper presents a modified single stage single phase inverter with four switches. The proposed inverter has important features such as continuous input current, voltage buck and boost with single stage conversion, short circuit safety and operation in various duty cycles same as qZSI and qSBI converters. In the rest of the paper, the suggested inverter operation mode and its switching method are described first and then, the steady state analysis is presented. To validate the merits of the proposed inverter, a comparison of the converter with similar topologies is provided. To verify the proper operation of the converter and also, to prove the presented theoretical calculations, a prototype of the introduced topology has been implemented in the laboratory. Test measurement results of the suggested inverter in 150 W with 10kHz frequency is derived. The obtained results and waveforms from test measurement present proposed inverter operation, steady state analysis and performance.

Multi-level inverters (MLIs) have now become an essential component for medium and high power applications with medium voltage levels. Low switches multi-level inverters are very popular due to their high efficiency, low cost, and easy control for output with higher levels. In this paper, a new multi-level inverter structure based on a switched DC voltage source is proposed by reducing the number of switches for single-phase applications. The proposed structure can be used in grid-connected applications, such as grid connections for renewable energy sources. The proposed structure is developed with a higher number of levels at the output using a smaller number of devices. The proposed topology can also be used in symmetric and asymmetric configurations. Two switching methods including pulse width modulation (PWM) switching and ladder switching based on selective harmonic elimination (SHE) have been used to generate the output voltage. Comparative studies with multilevel inverters were presented recently to show the advantage of the proposed structure in terms of reducing the number of devices. Simulation and experimental results are presented to confirm the performance of the proposed topology. In addition, the performance of the proposed multilevel structure for energy transfer from renewable sources to the low-power grid has also been investigated.

In this study, a new multi-objective method is proposed to optimal manage the local energy resources and customers’ load in a microgrid in the presence of demand response programs. The wind turbine and photovoltaic panel are the renewable energy sources of the microgrid. The time of use and critical peak pricing programs are also used to improve the consumption pattern of customers. Moreover, consumers try to use electrical energy when renewable sources are available. Maximizing the profit of microgrid and minimizing the pollutant gases of the microgrid are the objective functions of the demand side management problem. The multi-objective ant lion optimizer algorithm is used to optimize the indices of the microgrid and create the Pareto front. Then, the fuzzy method is utilized to select the best particle equal to the optimal management plan of the microgrid. Ultimately, the proposed method is evaluated in a sample microgrid. The results demonstrate the high efficiency of the proposed method in improving the performance of the microgrid by optimal managing the local energy sources and customers’ load. The proposed method of energy management increases the profitability of the distribution company and decreases the environmental pollution of the microgrid.

Recently due to technical, economical, and environmental reasons, penetration of renewable energy resources has increased in the power systems. On the other hand, the utilization of these resources in remote areas and capable regions as isolated microgrids has several advantages. In this paper, a hybrid microgrid, which includes photovoltaic (PV)/wind/energy storage, is investigated. It has been located in Iran-Khalkhal. The purposes of this study are optimal energy management and sizing of the microgrid. Since the magnitude of the harvested renewable energy deals severely and complexly with season and climate issues, planning of the system based on their specific values is an oversimplification. Therefore, in addition to conventional constraints such as environmental and operational ones, estimation of the wind speed at the site is considered. The Monte Carlo method is employed to model and estimate wind behavior. Also, for regulating production and demand in the microgrid the Demand Response (DR) program is conducted to improve the contribution of the renewable energy resources. The planning is constructed as an optimization problem. It is formulated as a Mixed Integer Linear Programming (MILP). By solving it, the size and production magnitude of energy sources, as well as storage conditions, are determined. Finally, the proposed method is simulated by GAMS for all seasons of two scenarios. The results show desirable energy management and cost reduction in the studied grid.

Grid-connected inverter-based photovoltaic (PV) systems play an important role in Distributed Power Generation (DPG). For this application, quasi impedance source inverter is very suitable due to its ability to increase or decrease the output voltage of the inverter in a single-stage and high reliable condition. Conventionally, to remove the harmonics, which are yielded by switching the grid-connected inverter, LCL filters are utilized at the inverter output. These filters can cause some problems at the Point of Common Coupling (PCC). The aim of this paper is to improve the quality of the injected power of the photovoltaic array, which is connected to the low voltage grid by quasi-Z-source inverter (QZSI). For this purpose, a two-stage control procedure containing DC and AC stages is performed. In the DC stage, the dynamic characteristics of the quasi-Z-source network are investigated by small-signal analysis. Using the transfer functions obtained from the dynamic model, the capacitor voltage of the quasi-Z-source network is suitably controlled to generate the appropriate voltage to the grid interface inverter. In the AC stage, in order to inject high-quality current into the grid as well as eliminating the resonance peak caused by the LCL filter, a systematic procedure is used to design the PR controller parameters and active damping coefficient. Simulation of the overall system includes solar panels, maximum power point tracking algorithm, quasi-Z-source inverter, and LCL filter to model the grid-tied PV system with the possible details. Simulations are carried out in MATLAB/Simulink environment, and results depict suitable performance of the studied power conditioning system with designed parameters.

In this paper, an optimal design of the renewable combustion plant has been investigated with the aim of ensuring the required load on the Gorgor station. The purpose of this study is to minimize the cost of the proposed hybrid unit during the period of operation of the designed system simultaneously. Information on the intensity of solar radiation and the intensity of wind blowing in the area are taken and applied in the simulation of the system. The intended target function includes the cost of investment, replacement cost and maintenance cost. After the design phase, the main objective is to check the economic benefits of the project's utilization from the grid and compare it with the renewable electricity system, as well as to calculate the initial investment return in renewable electricity. First, the initial cost of consuming electricity from this project is calculated using a renewable electricity system, and then the cost of project is determined using the national grid. Further, by calculating the annual current cost of each of these combinations, the investment return in each mode is obtained. Various options for the use of renewable energies are surveyed separately and in combination. The technical-economic analysis is done on each of these options and ultimately the best one is presented.

A new optimization method is proposed in this paper for finding the firing angles in multi-level voltage source inverters to eliminate low-order selective harmonics and reduce total harmonic distortion (THD) value of the output voltage. For thid end, Fourier series is used for calculating objective function and selecting specific harmonics. Regarding the nature and complexity of the employed non-algebraic equations in the optimization problem for achieving the optimal angle in the multi-level inverter, a recent developed meta-heuristic method known as Salp Swarm Algorithm (SSA) is presented. In the proposed method, the optimal angles for a given multi-level inverter are obtained based on the objective function such that the magnitudes of the selective harmonics and the THD value of the output voltage are reduced. The method is applied on a cascaded H-bridge type five-level inverter. The simulation results illustrate that the magnitudes of the selective harmonics and the THD percentage of the output voltage have been reduced through selecting the optimal switching angle by the proposed optimization algorithm. The result of this method are compared with those of SPWM method. Moreover, the performance of SSA algorithm with respect to PSO algorithm is compared which shows its rapid convergence speed and less THD value.

The main purpose of this paper is to develop a supplementary signal using reinforcement learning (RL) to improve the performance of power system stabilizer (PSS). RL is one of the most important issues in the field of artificial intelligence and is the popular method for solving Markov decision procedure (MDP). In this paper, a control method is developed based on Q-learning and used to improve the performance of a three band PSS (PSS3B) in a single machine infinite bus power system (SMIB). For this purpose, first the parameters of PSS3B are optimized using krill heard (KH) algorithm based on system eigenvalues. Then, using the proposed Q-learning method its performance will improve. The fundamental properties of the proposed Q-learning based control method are its simplicity and independency to system model and operational conditions. In order to evaluate the proposed control method, its dynamic response is compared to conventional PSS (CPSS) and PSS3B. According the simulation results, it is evident that, the developed adaptive controller is superb compared to the other methods in the view of settling time and damping low-frequency oscillations.