mehdi nafar

In this article, the optimal participation of energy hubs (EHs) connected to the grid in the day-to-day and real-time energy markets is presented. The proposed system consists of an electricity distribution network, a private transportation system, and a public transportation system, a water system, a thermal energy system. In addition, reconfiguration, and metro regenerative braking energy have been investigated. The proposed power distribution system is an on-grid hybrid microgrid. Improved gray wolf optimization algorithm for finding the best solution for scheduling the proposed system. Also, the reduced unscented transform scheme is applied to capture the uncertainty in the system. We demonstrate the effectiveness of the proposed method using a 33-bus IEEE test system in Matlab software package. Reductions in costs and pollution of the environment are demonstrated by the results. This study has demonstrated the completeness of the proposed smart network and the efficiency of the desired system by comparing it with the results of other studies and similar systems.

Achieving optimal and safe energy management and planning, taking into account the reduction of electricity production, transmission and distribution costs, as well as the reduction of environmental pollutants, has become increasingly important in many power companies in developing countries. With the optimal use of renewable energy sources and the use of a secure platform, including blockchain technology, the aforementioned goals can be achieved. To solve optimization problem, after modeling the hybrid AC-DC microgrid and considering the high complexity of the proposed formulation, the grey wolf optimization algorithm is proposed to solve the problem. In order to check the efficiency of the system under cyber-attacks, the system is subjected to false data injection attacks in different parts of the system, and then the operation is done under normal conditions and cyber-attacks. In this paper, MATLAB software package is used to solve the optimization problem and modeling the cyber-attacks. The operation results have been examined in different scenarios and the negative effects of such attacks are shown by comparing with the normal state. Then, to enhance the security of the system and prevent attacks, blockchain technology is presented to increase the security of the data exchanged in the system.

The capability of a neuro-fuzzy control approach for frequency fluctuation damping in an isolated hybrid microgrid (IHMG) system (DEG/WTG /PV/FC/ESSs) is investigated in this paper. Due to the intermittent behavior of renewable energy sources (RESs) like wind turbines and photovoltaic arrays and the time-varying nature of demands, frequency fluctuation is more likely, specifically in the grid-connected mode. Model parametric uncertainties as well as load changes, wind power, and solar irradiation variations are the main uncertainty sources of the IHMG system. In the suggested approach, a neuro-fuzzy output feedback controller with three inputs that are inspired by PID control is designed considering the power balance between demands and generations, by optimizing fuzzy membership functions’ locations. The proposed controller is compared with two popular other methods on the investigated IHMG system in terms of time-domain characteristics. The outcome illustrates remarkable merit compared to the state-of-the-art methods in the presence of simultaneous disturbances and the model parametric uncertainties.

In this paper particle swarm optimasation algorithm (PSO) based sliding mode controller(SMC) introduced to control invrters of Uniefied power quality Controllers(UPQC) to control and improve the power quality in microgrids through controlling the output power of the distributed generation source. In the proposed control scheme, the standard sliding mode controller (SMC) is used as a robust nonlinear controller, with the addition of the particle swarm optimization (PSO) algorithm - to determine the optimal parameters of the SMC controller. Using PSO added extra advantages like reducing chattering problems and increasing accuracy and tracking capability to the commonly knowns SMC benefits. To confirm the accuracy of the proposed controller's performance, computer simulation is performed under different system load conditions in the MATLAB/Simulink software environment. The obtained results show the effectiveness of the proposed control compared to the standard sliding mode controller in reducing harmonics, reducing voltage imbalance and improving other power quality indicators.

Using bidirectional parallel converters improves system reliability as they can bypass faults. Therefore, the bidirectional parallel converters structure is adopted for the DC micr ogrid connected to the grid. There is a circulating current between the bidirectional parallel converters that limits the overall capacity of the system and can damage switching devices. To solve this problem, in this paper, the mechanism of generating circulating current on the AC side when several bidirectional parallel converters work together was taken into consideration with the effect of constant power loads by the droop strategy Pdc-vdc2-f to share DC power and network frequency adaptation. The PI coefficients of the bidirectional parallel converters controller were optimized by online genetic algorithm and neural networks and updated with system conditions. Both the stable and dynamic relationships between Pdc and vdc2 are linear and did not create constant power loads of unstable poles for the system. The results indicated that compared with conventional idc-vdc droop control, the proposed Pdc-vdc2-f strategy can increase dc power control and system stability, consequently increasing the dc voltage regulation dynamics.

This paper studies a new method for reconfiguration of the distribution network that considers access to energy storage devices. Initially, a new distribution network reconfiguration model is being created that takes into account access to energy storage devices. This model takes as an objective function the minimum of network losses and takes into account the current power and voltage constraints induced by energy storage devices. In reconfiguration schemes, the dual power flow directions are also deliberated. To solve the proposed model, the Binary Particle Swarm Optimization (BPSO) is implemented to get the optimal reconfiguration scheme. Finally, to check the correctness and efficacy of the proposed process, two distribution networks with admission to energy storage systems are being checked (Initial topology of 12-bus system - Optimal topology without considering energy storage - Optimal topology considering energy storage), Then proposed more suitable method for solving the proposed reconfiguration models in this manuscript.

Today, the use of distributed generation resources connected to the network has remarkable growth therefore network-connected to the converters must be able to provide services beyond the injection of power into network, including maintaining network stability. In this paper the control and management of energy for battery wind, photovoltaic and diesel connected to a three-phase network by activating the current limitation under unbalanced fault has been introduced. In this method injected currents are limited to a certain amount along the faults Also, the operation mode without tracking the maximum power point for the converter is included. This state is activated during severe faults, when the converter cannot control Maximum power of the system. Therefore, in a microgrid with, the operation of a fuzzy logic-based controller the transformation operation of DC to DC converter control is performed sparsely by two-way battery and distributed generation resources management. Also proportional resonance controller is used due to its proper performance. In fact, with the use of reference current generation, sinusoidal current with a total harmonic distortion (THD) value of less than 5% is injected. The results show that the control strategy along with energy management with multiple energy generation resources is able to limit and maintain DC link voltage within an acceptable range in addition to The existence of an asymmetric fault. Therefore, the fault crossing operation has been performed correctly without the operation of the protection relays and secondly in comparison with microgridsolely with the presence of one photovoltaic production source the process of injecting active and reactive power in the upstream network is more appropriate.

A reconfiguration model for the distribution network with the optimization objective of reducing three -phase disequilibrium is suggested in order to cope with an increasingly serious three -phase unbalance in distribution network. Second, the distribution network reconfiguration problem is transformed into a problem of constructing the spanning tree of the graph by evaluating the distribution network in topology, which is solved by the process of breaking -cycle -basis. Then an improved Binary Particle Swarm Optimization (BPSO) algorithm is suggested to solve the reconfiguration problem by randomly choosing the first-branch and canceling the heuristic value of the network, which will extend the search scope and prevent search stagnation. Relevant examples of verification show that, relative to traditional approaches, the proposed algorithm can achieve the best global solution with less computational time and greater probability. The proposed algorithm is tested in 33 bus system and the results show the load balancing in distribution network.

Human life and the economy of a country are becoming more and more dependent on electricity. However, events that occur due to various factors in the power grids, affect the quality of electrical energy delivered to subscribers. The human error of maintenance teams is one of the most important causes of automatic outputs of electrical equipment. Human error, in addition to the economic consequences of not transiting electrical energy due to equipment outages, may also cause health damage to personnel. The purpose of this study is to propose a method for analyzing the human reliability of maintenance teams in power transmission grids, which has been implemented as a case study on power transmission grids teams in Fars. The first step is to identify the roots of human error. So far, no comprehensive studies have been conducted on the root causes of human error in power transmission grids. Therefore, in this article, the actual and potential roots of various aspects such as organization, individual moods, supervision, etc. are identified and predicted in the framework of the method of human factors analysis and classification system. Then, a method is proposed to estimate the probability of the root event to use its results to prioritize the necessary control and corrective measures to reduce human error.

In this paper, optimal participation of the grid-connected energy hubs in the day-ahead energy and reserve markets is presented. The proposed scheme includes objective function that is minimized the difference between flexibility cost of hubs and their revenue in these markets. Also, this problem is constrained to power flow equations in the electrical, gas and heating networks, technical and reserve limits of these networks, and operation model of hubs including different sources and active loads. In the following, the stochastic programming is used to model the uncertainties of load, market price, networks reserve demand, renewable generation power, and energy demand of mobile active loads. Finally, by implement of the proposed scheme on the standard test network, the obtained numerical results confirms the capabilities of this scheme in the improvement of economic and flexibility situation of energy hubs, and improving the operation situation of the energy networks.

Supercapacitors have attracted much attention in the field of electrochemicalenergy storage. However, material preparation and stability limit their applications inmany fields. Herein, a reduced graphene oxide@phosphorus (rGO@P) electrode wasprepared using a simple inexpensive method. The new graphene structure (rGO@P) wascharacterized by X-ray di􀀀raction, Fourier transform infrared spectroscopy, scanningelectron microscopy and Energy-dispersive X-ray spectroscopy.Electrode showed excellent performances (307 F g−1), which seem to be the highestamong many other rGO@P-based electrodes reported so far. It also has an excellentcyclic stability up to 95% after 600 consecutive charge/discharge tests. So, the ease ofthe synthesis method and excellent performance of the prepared electrode materials mathave significant potential for energy storage applications.

Ocean thermal energy conversion (OTEC) systems utilize from the difference between the temperatures of surface and deep water and drive a thermodynamic Rankine cycle for electric power generation. The generated power depend on the temperature of the surface water as warm source and due to the variation in the temperature of surface, the output power of the OTEC system frequently changes. This uncertainty nature results in the variation in the generated power and so, integration of large-scale OTEC generation units to the power system is a challenging problem and new techniques must be developed for studying the effects of resources on the power system. Therefore, the balance between generation and consumption is important and from reliability point of view, spinning reserve must be scheduled to prevent load curtailment in the events such as forced outages of generation units, transmission lines and so on. In a power system containing large-scale OTEC power plants, the uncertainty nature of these plants must be considered in the reserve scheduling and for this purpose, a reliability model considering both failure of composed components and variation in the output power, is developed and for determining a suitable multi-state model, fuzzy c-means clustering technique and XB index is utilized. Then, the proposed multi-state model is used for spinning reserve determination of a power system containing OTEC plants using of the modified PJM method. Numerical results associated to RBTS and IEEE-RTS present the effectiveness of the proposed technique for operation studies of power systems containing OTEC systems.

The topic of distribution network reconfiguration has been recognized as a common problem in the operation of distribution networks. Up to now, reconfiguration of the distribution network has been used to reduce power loss, issues with reliability and emergency problems. As a result of the increasing installation rate of Distributed Generations (DGs) and the increasingly increasing number of Electric Vehicles (EVs), distribution network operators have faced new problems as a result of high sensitive loads. These new facets of the problem of network operation consist of the problem of congestion and enable the business mechanism to be executed by an existing distribution market. With the application of Distribution Locational Marginal Price (DLMP), using Particle Swarm Optimization (PSO), this paper introduces a new methodology to solve this problem. As a suitable case study, the standard IEEE 33-bus network has been selected and simulation results show the compatibility of the proposed system. In the case of not considering DGs and the problem of congestion, comparisons with other papers were also discussed. The participation of DGs in the electricity distribution industry, the issue of congestion and the numerical results have been shown and discussed below.

One of the common problems of power quality is the occurrence of voltage sags due to different types of balanced and unbalanced short-circuit faults in electrical distribution systems. Dynamic Voltage Restorer (DVR) is the most effective equipment used for voltage recovery in power distribution systems and it injects voltage in series with line voltage for voltage recovery. In this paper, the structure and general components of this equipment are presented. In addition, by applying a control scheme based on Synchronous Reference Frame Theory (SRFT) in its control system, the effective role of this equipment in compensating and maintaining the voltage of a power distribution system under the occurrence of balanced three-phase short-circuit fault and unbalanced single-phase to ground short-circuit fault is investigated and analyzed using Simulink/Matlab software.

One of the ways to increase the reliable and stable performance of power grids and reduce customer shutdowns is the proper planning of power grid maintenance. Many studies have been carried out in the area of selecting the best and most effective maintenance technique for each electrical equipment.  However, in order to ensure the successful design and implementation of these maintenance methods, it is required that a model be provided for assessing the status of power grids in terms of maintenance objectives. This paper proposes an appropriate and comprehensive strategic map based on a balanced scorecard model (BSC) with the help of technical knowledge and experience of the experts. The proposed strategic map describes maintenance strategies and plans for power transmission companies from four perspectives: financial, customer, internal processes, learning and growth along with strategic issues. Using the proposed method managers can identify the maintenance deficiencies by indexing and targeting strategic issues and their ongoing monitoring. At last, the prioritization can be done to eliminate the difficulties. Results show that by continuously evaluating all aspects of the transmission networks maintenance, increase in system availability can be observed.

Dynamic Voltage Restorer (DVR) is one of the voltage compensation equipment. Voltage quality injected by of this equipment depends on the quality of DC link voltage and the type of control system modulation. The photovoltaic array can be used to store the DC link of this equipment. To increase the output voltage of the photovoltaic array to the required DC voltage level, a standard boost chopper is used which reduces the quality of the compensator voltage due to the high voltage ripple. Using well-designed choppers such as interleave can in addition to increasing the photovoltaic array voltage, reduce the ripple DC link voltage and thus the harmonic content of the voltage injected by the compensator. Applying appropriate pulse bandwidth modulation to the control system of this equipment can also be effective in reducing harmonic content and improving voltage quality. In this paper, in order to reduce the total harmonic distortion (THD) of the compensator injected voltage and consequently to improve the load voltage quality, the interleave boost converter at DC compensator link and the hysteresis modulation in the controller scheme of this hybrid compensator are used and the simulation results are presented. The result of the proposed system is compared with the results of the hybrid compensator based on conventional boost chopper and sinusoidal modulation.The simulations are done using Matlab/Simulink.

The aim of the present study is to examine and identify team performance dimensions and factors in Iran’s public organizations. For the purpose of the study exploratory method was used and data were gathered through quantitative approach. The targeted population consisted of two parts including experts in the field and managers and experts in public organizations in Ilam. The sample size included twelve (12) experts in the field and four hundred and seventy two (472) managers and experts. Confirmatory factor analysis was used to analyze the data. Team performance was found to include two dimensions including processes and results (performance). Process dimension consisted of four factors: leadership and goal setting، creativity and innovation، research and development، and partnership and cooperation. Result dimension included three factors: results for the team، results for the organization، and results for society.

In this paper, wDecomposition of energy intensity is one of the basic tools for studying the impacts of structural changes and energy efficiency improvements on the pattern of energy demand in the industrial sector. Based on the theory of price index numbers,e study the factors affecting changes in energy intensity in Iran. We use Fisher Ideal index is used in order to decompose the energy intensity into the structural changes and efficiency improvements components in the Iranian manufacturing industries during 1993-2004. The pattern of energy intensity in the International Standard of Industrial Classification (ISIC) industries during the second and third socio-economic development plans is analyzed. The results show that ththe structural changes have had a little effect in decreasing the energy intensity in the manufacturing industries in Iran.