javad olamaei

Due to the extensive range and diversity of equipment within distribution networks, this part of the power system is responsible for a considerable proportion of customer outages, as reported by electricity departments. A viable solution to mitigate these outages and prevent associated economic losses is the strategic placement of switches along distributed generation resources within the network. This paper presents an optimal placement of sectionalizing switch and fuse in the presence of distributed generation using a fuzzy multi-objective function. Uncertainties in load, failure rates, and repair times are also considered to allow for devising a superior design. The primary objectives of the plant are to elevate the system’s reliability and simultaneously reduce the cost of switches, defined via fuzzy membership functions. The use of a fuzzy multi-objective function helps propose various plans tailored to economic and technical conditions. The HBMO algorithm is employed for optimization. To validate the proposed method’s efficiency, tests are finally conducted on an RBTS test network and real distribution network.

As the penetration of renewable energy resources increases, as well as advances in battery technologies, optimal expansion planning of the high-capacity batteries in power systems has become important. In this manuscript, a new model for the stochastic development of the batteries in transmission networks is presented. In the proposed method, the production of the wind unit is probabilistically modeled based on scenarios. In this method, in addition to the conventional relationships in the formulation of the problem of optimal energy storage systems expansion planning, the limitation of charging and discharging capability of storage devices has also been addressed. In the proposed model, a new relationship is proposed to determine the capability of charging and discharging cycles of storage devices. Also, the relationship between the maximum capability of charge and discharge cycles and the depth of discharge is presented and added to the previous formulations. The nonlinear relations in the proposed model are linearized and become a linear problem. The optimization problem generated by GAMs software has been solved. In order to demonstrate the capability of the proposed method, this method has been implemented on the 14-bus IEEE test network, which the simulation results show its capability.

current study focuses on optimizing the efficiency of an LCLCL-T compensated topology in wireless power transfer systems with load-independent output current capability for battery charging. Wireless battery chargers play key devices in smart homes. To improve efficiency in these chargers, various compensated topologies are employed. In particular, the symmetric compensated LCLCL-T topology has been extensively used due to its inherent features, such as constant current output (CC), and high ability to absorb parasitic elements. However, one of the main deficits of this resonant compensation is decreased load regulation despite controlling the frequency, and on the other hand, its efficiency decreases owing to an increase in the circulating current. Therefore, in this study, the parameters of the proposed topology are reconfigured by adjusting the KW/KVA as an index to a reduction of voltage/current stresses on their elements without changing the specified system-level parameters, such as the system operating frequency, and specified CC output. Moreover, the circuit performance in the high-frequency response under different conditions is analyzed in detail, to optimize the system efficiency. Finally, the proposed system is simulated in PSIM to design the specific parameter values, the sample topology is also carried out. Analytical results show that the proposed compensation has the minimum output current fluctuation versus variations of the coupling coefficient and other parameters. Moreover, the analysis proves that, compared with the conventional design method, the proposed method improves the topology efficiency under various loads, especially under light loads.

The Microgrid is a small-scale controlled power system, which can be used in islanded mode or in a grid-connected one to provide power. In the islanded Microgrid, the system frequency will be affected severely by the smallest disturbance which can happen due to light inertia in the system. In the independent Microgrid, several generation sources such as solar, wind, and so on can be considered. In addition to these power plants, the discussion of energy conversion as a result of temperature changes can be considered as a thermoelectric converter. In the present article, the effort has been made to propose a microgrid model which incorporates a Thermoelectric Generator (TEG) system. In this system, due to the variety of uncertainties and load variations, an advanced controller must be developed to improve the dynamic stability and reliability of the microgrid system. The Improved Fuzzy Fractional-Order PID is the suggested controller. The proposed controller is applied to a sample islanded microgrid to establish a robust evaluation and to be checked under parametric changes, great demands, and disturbances. The offered controller is compared with those of other PID, FOPID and FPID controllers. The results of simulations reveal that the proposed controller has a proper and robust performance.

Today, energy carriers are addressed as one of the main pillars of energy generation due to the increased growth of industries in developed and developing countries. According to the global view, increased consumption of energy carriers has increased the production of greenhouse gases, the global average temperature, resulting in the faster melting of ice in Antarctica. Moreover, increased pollution due to consumption of fossil fuels for electricity generation is causing numerous problems for industrial cities, photochemical smog, and numerous lung diseases for humans and often living organisms. Due to the above reasons, using methods to minimize energy carriers consumption and applying renewable energy in order to reduce the extent of generated pollution is highly important. Using energy HUB systems might help manage energy resources properly and minimize the extent of pollution. This article has proposed a smart management system of an energy hub that includes an input (consisting of fossil fuels, renewable energy, and electricity grid) and output (consisting of consumers). The proposed system can manage energy carries and maximize the use of renewable energies, and it can absorb high levels of generated CO2 and transform it to gas energy carries in addition to save energy. Such an approach has reduced CO2 level inside the energy hub, and reduced the total cost of the system and this is because a part of gas fuel needed by the system is supplied. This article has shown that using such a system reduces the cost imposed by system pollution by 9.08%.

Energy carriers are addressed today as one of the main pillars of energy generation due to the increased growth of industries in developed and developing countries. According to the global view, increased consumption of energy carriers is causing an increase in the production of greenhouse gases, the global average temperature, and this, in turn, results in the quicker melting of ice in Antarctica. Moreover, increased pollution stemming from the consumption of fossil fuels for generating electricity is causing numerous problems for industrial cities, photochemical smog, and numerous lung diseases for humans and often living organisms. For the above reasons, using methods to minimize the consumption of energy carriers and applying renewable energy in order to reduce the extent of generated pollution is highly important. Using integrated energy systems (IES) may help manage energy resources in a proper manner and minimize the extent of pollution. This article has proposed a smart management system of an energy hub that includes an input (consisting of fossil fuels, renewable energy, and electricity grid) and output (consisting of consumers). Not only is the proposed system capable of managing energy carries and maximizing the use of renewable energies, but also capable of absorbing high levels of generated CO2 and transforming it to gas energy carries in addition to saving energy.  Such an approach has caused the reduction of CO2 level and its derivatives inside the energy hub and also, reduction of the total cost of the system and this is because a part of gas fuel needed by the system is supplied. This article has shown that using such a system reduces the cost stemming from system pollution generation by 9.08% and the total cost of the system by 13.57%.

High pressure insulators are exposed to different environmental and climatic conditions. The interaction of environmental conditions and insulation pollution makes the insulation of the insulators themselves a suitable substrate for conducting current and leaving its effects on power systems. Knowledge of potential distribution and electric field of high voltage equipment is an important aspect of the design, operation and performance of high pressure insulators. This can be useful for detecting defects in insulation. The purpose of this study is to show the behavior of contaminated insulators under voltage. Therefore, electric field simulation and potential distribution in the vicinity of different insulation levels were discussed. Insulators are modeled in two ways: 2D, 3D and Multiphysics Comsol software analysis, which is one of the best software used in modeling for finite elements. Finally, the results of potential distribution and electric field along the insulation in different contaminated and clean conditions, which are simulated using different conductivity values, are shown.

Multi-level inverters (MLIs) have made great strides in the use of renewable and industrial energy compared to conventional two-level inverters in terms of output voltage quality, filters and high efficiency requirements. This paper describes a new topology for single-phase multi-level invereter. This topology is presented with the aim of reducing the number of isolated voltage sources, switches and drivers that are able to modularly increase the number of output levels. The proposed structure has been improved to achieve a higher number of output voltage levels relative to the number of switches, drivers and DC voltage source. To confirm the superiority of the proposed structure, a detailed comparison has been performed with other multi-level inverter topologies. In this paper, the Nearest Level Modulation (NLM) is used to generate the output voltage and is simulated in Matlab/Simulink environment. The performance of the designed structure is comprehensively evaluated in symmetric and asymmetric topologies.

The use of distributed generation units in distribution networks has attracted the attention of network managers due to their great benefits. In this research, the location and determination of the capacity of distributed generation (DG) units for different purposes has been studied simultaneously. The multi-objective functions in optimization model are reducing the losses of the system line, reducing voltage deviation, increasing voltage stability margin, and decreasing network's short circuit when DG units are considered in the distribution network (DN). To calculate the values ​​of mentioned multi-objective functions, a backward and forward sweep load-flow and a short circuit calculation are used. To solve the problem, a multi-objective optimization algorithm called improved non-dominated sorting genetic algorithm–II (INSGA-II) is used. This algorithm leads to the creation of various responses that the user can choose, as needed, for each one. A tradeoff method, based on fuzzy set theory, is used to obtain the best optimal solution.The proposed method is examined on the IEEE 33-bus test case while considering different scenarios. In the end, the feasibility and the effectiveness of the proposed algorithm for optimal placement and the sizing of DG in distribution systems have been proved.

Voltage instability is one of the most important issues in power systems. In recent years, with the restructuring of power systems, system operators to operate the system at a point near the border of stable conditions to maximize profits and reduce costs. When an event occurs in the power system, if the power system is not able to maintain voltage in its various parts, the phenomenon of voltage instability in the power system has occurred which can lead to widespread blackouts in the system. In addition to causing great economic losses, these blackouts will also cause customer dissatisfaction with the electricity network. Therefore, identifying the voltage instability in the network, which can be followed by deciding on control measures, will play an important role in increasing the quality and security of the system. In this paper, various methods of voltage stability and control are introduced, studied and reviewed.

Robust algorithm is known as the one of high potential models for strengthening in optimization of large and complex distribution networks considering uncertainty. In this research we are looking for some suitable template and appropriate clustering pattern in order to analyze the operation of distribution network. The analysis of optimization process in both individual and adaptive cases of distributed generation sources applied to some standard distribution network shows that the adaptive case of DGs determines less partial and total operation cost. except in islanded case of DGs. The results of clustering approach based on choosing the candidate points which includes DGs and feeders are used in medium voltage (MV) network level. By investigating the software data in both single cluster with first up to fifth and tenth repeatition, one to five clusters and finally ten clusters case shows the superiority of mean data besed clustering. because of having the three following properties such as being sensitive to all weighted candidate points, the speed of acceptable operation and feeding the clusters in islanded case in multiplicity of clusters, it is suitable to designate the robust optimization method using pattern random clustering.

Under unbalanced grid condition, in a Doubly-Fed Induction Generator (DFIG), voltage, current, and flux of the stator become asymmetric. Therefore, active-reactive power and torque will be oscillating.In DFIG controlling Rotor Side Converter (RSC) aims toeliminate power and torque oscillations. However, simultaneous elimination of the power and torque oscillations is not possible. Also, Grid Side Converter (GSC) aims to regulate DC-Link voltage. In this paper, in order to regulate DC-Link voltage, an Extended State Observer (ESO) based on a Generalized Proportional-Integral (GPI) controller, is employed. In this controlling method, DC-Link voltage is controlled without measuring the GSC current, and due to using the GPI controller, the improved dynamic response is resistant against voltage changes, and the settling time is reduced.To improve the transient stability and Low Voltage Fault Ride Through (LVRT) capability of DFIG,Statistic Fault Current Limiter (S-FCL) and Magnetic Energy Storage Fault Current Limiter (MES-FCL) areproposed in this paper. The proposed FCL doesnot only limit the fault current but also fastenvoltage recovery. The simulations are implemented by MATLAB software in the synchronous positive and negative sequence reference (d-q)

In this paper, a comparative study of optimization algorithms for determining the optimal size of hybrid stand-alone power systems at the lowest total cost is proposed. In this regard, the performance of the components of hybrid power system including wind turbine, fuel cell, anaerobic reactor, reformer, electrolyzer and hydrogen tank has been studied and several different optimization algorithms are taken into account. The proposed method can meet the load demand using wind energy and biomass as an available energy resource. In the stand-alone power system, power produced by the wind turbine and fuel cell (fed by the reformer) are applied to the demand. When these generations are more than the demand, additional power is delivered to the electrolyzer. Otherwise, the hybrid system is fed by the hydrogen tanks. The proposed method has been tested in Kahnooj region located in the southeastern of Iran and the results of various optimization methods have been presented in order to determine the optimal size of the hybrid power system.

This paper reviews and compares the most important maximum power point tracking (MPPT) techniques used in photovoltaic systems. There is an abundance of techniques to enhance the efficiency of photovoltaic systems. The crucial distinctions between these techniques are digital or analog implementation, simplicity of the design, sensor requirements, convergence speed, stability, range of effectiveness and costs. Thus, opting for a suitable algorithm is vital as it affects the electrical efficiency of the PV system and lowers the costs by lessening the number of solar panels needed to get the desired power. Moreover, the paper provided a summary of the most used MPPT algorithms.

This paper reviews various algorithms for the implementation of MPPT in a PV module integrated with a DC-DC converter and current mode control strategies for power converters. Also, a novel multi-loop integrated MPPT and current mode control for the Single Ended Primary Inductance Converter (SEPIC) derived from the incremental conductance MPPT technique is proposed. A simulation model is developed using MATLAB/Simulink dynamic system simulation software to verify the operation of the control system developed in the paper. This ensures the efficient operation of the PV power plant by rapid and accurate tracking the maximum power point (MPP) of the PV array. Moreover, the system is seen to offer robust voltage regulation and improved dynamic response in the face of changing environmental variables.

To ensure the reliable delivery of AC power to consumers from renewable energy sources, the photovoltaic inverter has to ensure that the frequency and magnitude of the generated AC voltage are within acceptable limits. This paper develops models and control strategies for the DC-AC converter to ensure that the sinusoidal waveform of the desired frequency voltage and magnitude generated for both single-phase and three-phase operation depend on the robustness of the inverter control system. The paper reviews various topologies and modulation approaches for photovoltaic inverters in both single-phase and three-phase operational modes. Finally, a proposed control strategy is presented to ensure frequency and voltage regulation.

Optimal reactive power dispatch problem in power systems has thrown a growing influence on secure and economic operation, nonlinear and multi- modal problems. Used methods in this issue can be divided into two categories: First, the classical methods like linear programming (LP), nonlinear programing (NLP), quadratic programming (QP), interior point methods (IPM), Newton-bused methods, and the second, heuristic methods like genetic algorithm (GA), evolutionary programming (EP), and particle swarm optimization (PSO). In this paper, projected quasi-Newton method (PQN) is used as an optimal algorithm. This algorithm is applied on a 6-bus micro grid in medium voltage level. To make the problem more realistic, a wind turbine is put in one of the buses to consider uncertainty in power generation. Also two buses data are not available to add state estimation to the problem. For troubleshooting of power generation uncertainty, time series prediction model is used to predict wind speed. To overcome the problems of unavailability of some bases information, maximum likelihood weighted least squares estimation (MLWLSE) is used. Finally obtained information is used to optimize the reactive power in micro grid.

Doubly-fed induction generator (DFIG) is too sensitive to the terminal voltage reduction. Thus, it is essential to choose an appropriate controller for converters in order to have stable voltage as well. In this article, double-fed wind turbines is controlled by vector proportional integrated regulator. For this purpose, a test network using vector proportional integrated (VPI) regulator is applied. Therefore, the stability is examined by evaluating the considered grid under different fault conditions. In addition, the performance of this grid is evaluated in the case of adding DFIG. Next, the effect of VPI regulator is analyzed on performance of this grid. The results showed that application of vector proportional integrated regulator improves grid stability to a further degree than direct vector regulator.

This paper presents a new method based on empirical mode decomposition and Hilbert transform for detecting islanding from non-islanding events in distributed generations. In this paper, the empirical mode decomposition is used to separate out intrinsic mode functions (IMF) from non-stationary power signal disturbance waveforms. Then, the Hilbert transform applied on all the IMFs to extract the instantaneous amplitude and frequency components. The required index is extracted from the energy spectrum density of the signals that introduced as U1, U2, and U3 and we can detect islanding events with high accuracy, low cost and high speed in distributed generations.

In this paper, the electrical distribution network reconfiguration to achieve loss reduction, load balancing and improve voltage profile in the presence of Distributed Generation (DG) with the gravitational search algorithm (GSA), is investigated. By choosing a 33-bus IEEE sample network and running a computer simulation on it, it is observed that the results of this rearrangement are comparable with similar papers.

This paper presents a method for distribution network expansion planning. The two objectives are: loss reduction and Reliability improvement. First, neural network method is used for long term load forecasting.  Then Genetic algorithm is utilized to solve simultaneous placement of power distribution transformers and feeders. The proposed method is applied on the green field. The effectiveness of the proposed method is tested on a green field system and the results are presented.

The long-term planning of distribution network expansion planning has different complexities, because this problem has a lot of decision-making variable. The optimal placement problem of HV/MV substations with distributed generations simultaneously for supplying the capacity required for power system are analyzed in this paper. In the mathematical model, objective function together with constant, varied variables and constraints related to limitations for the operation of substations and distributed generation resources as well as network limitations are formulated. Despite of distributed generation resources, the simultaneous placement must be so that firstly load points to be supplied and secondly loss costs of the network to be reduced. In addition, the voltage profile improvement and reduction of network reconfiguration costs are considered. At the end, we will observe the power quality improvement in load points. To solve this problem, optimization of one of new algorithms named cuckoo optimization algorithm has been applied. The study period for performing this test by means of dynamic-pseudo method for a long-term study will be within the design period. Finally, tests will be provided for proving the efficiency of this offered optimization algorithm.

In order to prevent energy waste by throttle valve in gas pressure reducing station of Neka thermal power plant, a turbo-expander with a capacity of 9.8 MW for the power plant was prepared and installed. Presence of turbo-expander in Neka power plant due to the absorption of 63 MVAr reactive power at the moment of starting, resulted in severe voltage drops in the auxiliary service system and outage of sensitive equipment to voltage level, which makes impossible the operation of the turbo-expander. In this paper, while pathology of turbo-expander and their performance Improvement using compensator, to review all topologies of dynamic voltage restorer compensator and improved topology will be presented. Then, for optimal performance of compensators the possible points presence of them on the auxiliary service system of Neka power plant in various scenarios under synchronization of fault occurring conditions and starting will be tested. The results of PSCAD / EMTDC software simulation show by using improved topology of dynamic voltage restorer, voltage sag of turbo-expander starting compensated in various scenarios and can be provide the total auxiliary service system power consumption of this power plant by turbo-expander instead of using the generation of power plant.

Selective harmonic elimination (SHE) is a powerful modulation scheme aims to find the required switching angles in order to eliminate the number of undesired harmonics. SHE is a complicated problem which consists of several nonlinear equations which have multiple local minima. In order to eliminate the higher number of undesired harmonics and as a result reducing the total harmonic distortion (THD) much more efficiently, the degrees of freedom must be increased. This means that the number of switching angles gets more and as a result, the problem gets more intricate. As the number of switching angles increases, using either traditional iterative techniques or resultant theory method gets useless. So, in this paper, SHE is treated as an optimization problem where Teaching–Learning-Based Optimization algorithm (TLBO) is found as an efficient tool to solve it. The provided experimental and simulation results of a 7-level multi-level inverter validate the efficiency and practicability of the implemented scheme.

The biggest challenges faced in big cities are greenhouse gas emission and growing energy needs. Efficient utilization of existing infrastructures has a prominent role in response to the challenges. Energy hub approach embraces performance of different energy networks. Energy hub is defined as a super node in electrical system receiving distinctive energy carriers such as gas and electricity in its input, and based on minimum cost decides when and how much of which energy carrier should supply the hub requirements. In this paper, we examine impact of renewable energy resources (wind and solar) and energy storages (electrical and thermal storages) on short term scheduling of energy hub. Effect of the technologies is also investigated on total operation costs of the energy hub in hot and cold climates. Mixed Integer Linear Programming (MILP) model is used for modeling proposed energy hub. CPLEX solver of GAMS software is employed to solve the problem. The results reveal that when and how much of which energy carrier should be exploited to satisfy hub required demands