The current study proposed a novel Traveling Wave (TW)-based Protection algorithm for power transmission lines using Intelligent systems. This algorithm is composed of two parts: the first part of the algorithm distinguishes the internal faults from the external ones, and the other one classifies the fault types and determines the faulted phases. In this research, first, Teager Energy Operator (TEO) was employed to extract TW signals and then, Hidden Markov Model (HMM) was utilized to distinguish the internal faults from the external ones according to the output of TEO. Of note, classification of the fault types and selection of the faulted phases are two important tasks in Protection algorithms. In this regard, this study presented a very accurate and robust classification algorithm based on fuzzy systems. This algorithm took into account different ratios of the modal components of the faulted current signal as the input variable of fuzzy systems. The test system was then simulated in PSCAD software and the algorithm was applied in MATLAB. Testing the proposed algorithm with a large number of test signals under different fault conditions confirmed the robustness of both algorithms in terms of internal fault and fault type classifications.

The rapid growth of grid-connected embedded distributed generations (DGs) is changing the operational characteristics of distribution networks (DNs). In order to implement DNs with DGs, some challenges should be faced, especially concerning Protection issues, that may make conventional Protection schemes ineffective. MAS techniques can enable the power grid to becomes smarter, reliable, selfhealing, and robust. Its decentralized nature and operational robustness make the MAS application a leading technology. Despite the fast, reliable and multi-purpose operation of MAS-based Protection schemes, the inherent delay or failure of communication system must not affect the vital role of fault clearing, i. e., the ever-increasing DGs in DNs as well as network size increase has resulted in a heavy communication burden yielding to delay or even failure in communication. In this paper, an Intelligent Protection algorithm is presented that protect the grid, when the connection between agents is lost, by using point-to-point communication between relay agents in the first layer of the MAS. Reduction of the agents used and no need to connect to the higher layers of the MAS are the benefits of this method. For simulation, 16 bus Test DN is used, that The results confirm the applicability of the proposed model for grid Protection coordination.

An Intelligent strategy for the Protection of AC microgrids is presented in this paper. This method was halving to an initial signal processing step and a machine learning-based forecasting step. The initial stage investigates currents and voltages with a window-based approach based on the dynamic decomposition method (DDM) and then involves the norms of the signals to the resultant DDM data. The results of the currents and voltages norms are applied as features for a topology data analysis algorithm for fault type classifying in the AC microgrid for fault location purposes. The Algorithm was tested on a microgrid that operates with precision equal to 100% in fault classification and a mean error lower than 20 m when forecasting the fault location. The proposed method robustly operates in sampling frequency, fault resistance variation, and noisy and high impedance fault conditions.

By increasing the penetration level of renewable distributed generations and increasing the size of the distribution networks, the more number of agent-based Protection systems with its communication infrastruture will be used. Such systems play a vital role in the Protection system to detect the faults and maintain the Protection coordination. Despite the fast and reliable nature of multi-agent systems, there is a possibility of poor performance especially in Protection coordination schemes with heavy communication load. For this purpose, this paper presents an Intelligent self-healing method under fault conditions, which provides the Protection coordination in a single control level without dependence on a higher communication level. The decentralized performance of the proposed scheme is expressed by using Intelligent electronic devices and distributed communication. Accordingly, the coordination is done using the high-speed point-to-point communication capability of the IEC-61850 GOOSE protocol. Also, to avoid power outages due to the Protection system malfunction, an algorithm independent of DG peneration and based on GOOSE message service mechanism is proposed, which does not need a central processor. Finally, the performance of the proposed algorithm is evaluated under different scenarios in a practical distribution network using ETAP software environment.

As the penetration of distributed generation sources increases at the distribution level, the necessity of designing microgrids is highlighted. Microgrids can operate in either islanded (separated from the utility grid) or grid-connected mode. Apart from the technical and economic bene ts of microgrids, they may cause some Protection issues in distribution systems. The most important of these issues is the di erence between the short circuit levels in islanded and grid-connected operation modes. In this paper, an Intelligent overcurrent relay that can adapt to the microgrid operation mode is proposed; that is, the relay detects the microgrid operation mode by means of an adaptive algorithm. The proposed adaptive method optimizes the accuracy and speed of the algorithm for detecting the microgrid operation mode. Then, the optimal settings that have been already stored in the relay are activated according to the microgrid operation mode. All internal processes of the relay use the voltage and current sampled at the relay location. As a result, the relay can be used in all networks without communication infrastructures. Finally, the proposed method is implemented in a sample microgrid. The superiority of the Intelligent relay performance over conventional overcurrent relays is shown by numerical results.

Application of sunscreens is one of the most important ways for skin Protection against sunburn, early skin aging and skin cancer.Due to variety of sunscreen products, it is necessary to assure their Protection ability against the suns damages. Performance assessment of sunscreens against UVB expressed by sun Protection factor. Due to great cost of determination methods of this factor in foreign countries, developing a comprehensive protocol for in vivo SPF determination in Iran would have distinct benefits.In this study four international standards have been reviewed and compared for Sun Protection Factor (SPF) determination including ISO24444, FDA2011, AS/NZS 2604: 2012 and CEN 2006. The general process of in vivo SPF determination is similar in these protocols but there are some obvious differences in details that leading to advantages and disadvantages for each of them.In this study a complete document were collected, then regarding to available facilities and with cooperation of Iran food and drug organization a comprehensive in vivo SPF determination protocol will be developed.

In this paper, a new method for fault detection, location, and classification in multi-terminal DC microgrid (MTDC) is proposed. MTDC grids have expanded due to some issues such as the expansion of DC resources, loads, and aims to increase power quality. Diagnosing the types and location of faults is important to continue the service and prevent further outages. In this method, a circuit kit is connected to the grid. In fault time, the fault in the network is detected by passing the current through the connected kits and measuring the traveling waves derived from the fault current as well as applying it to a mathematical morphological filter. Determining the location of the fault is done using circuit equations and current calculations. Phaselet output and fuzzy inference systems are used to determine the type of faults. The presented method was tested in an MTDC microgrid connected to renewable and energy storages with many faults. The results show the ability of the proposed method. The error of the proposed fault location method is less than 7%. This method is resistant towards the change in sampling frequency (between 500 Hz and 50 kHz), fault resistance (up to 125 ohms), and loading (up to 120% of the nominal load); it acts very well in high impedance faults.

Factorizing a system is one of the best ways to make a system Intelligent. Factorizing the Protection system, providing the right connecting agents, and transmitting the information faster and more reliably can improve the performance of a Protection system and maintain system reliability against distributed generation resources. This study presents a new method for coordinating network Protection system at the presence of distributed generation resources using smart electrical devices, control algorithms, and telecommu nications infrastructure. The proposed method is evaluated and validated on an experimental network simulated by ETAP software. also It provides a an opportunity to detect current fluctuations and network structure, which contribute to identify new Protection modes using the information table as well as to determine the Protection area. By using the information obtained from current fluctuations, the performance of the backup relay is improved.

The ever-increasing of renewable distributed generation sources in distribution networks, as well as increasing network size, have faced agent-based Protection schemes with a heavy communicational load. Accordingly, despite the fast and reliable nature of multi-agent systems, they have the possibility of improper performance, especially in centralized Protection systems. This paper presents an Intelligent self-healing method that has the ability to replace common multi-agent systems during fault conditions. Therefore, Protection tasks are performed in a single control level, without dependence on higher communicational levels, to clear the fault. Decentralized operation of this structure is provided by using Intelligent electronic devices and distributed communications. In this way, the proposed scheme is described with high-speed peer-to-peer communication capability using the IEC-61850 GOOSE protocol. Then, a penetration-free algorithm, without the help of a central controller, is provided by using GOOSE message capabilities, to prevent any electricity interruption due to insufficient Protection settings. Finally, by planning different scenarios and simulating a practical distribution network via ETAP software, the accuracy of the proposed algorithm has been proven.

This paper is directed to the question of how to model and design an efficient tool for the Intelligent mapping which is based on both dynamic and efficient storage of data and soft computing. The former is performed by our method that learns how to store, search and delete the data. After pointing out the limitation of the crisp evaluation of the distance between two points, we argue in favor of soft computing which is based on the extension of metric space to interval one and then to the fuzzy metric. A-Star algorithm is used to illustrate our model along with the injection of competitive data structures.