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This paper proposes a new method of fault detection and classification in asymmetrical distribution systems with dispersed generation to detect islanding and perform protective action based on applying a combination of wavelet singular entropy and fuzzy logic. In this method, positive components of currents at common coupling points are decomposed to adjust detailed coefficients of wavelet transforms and singular value matrices, and expected entropy values are calculated via stochastic process. Indexes are defined based on the wavelet singular entropy in positive components and three phase currents to detect and classify the fault. This protection scheme is put forward for fault detection and is investigated in different types of faults such as single-phase to ground, double-phase to ground, three-phase to ground and line to line in distribution lines in the presence of distributed generations, and different locations of faults are verified when the distributed generation is connected to the utility. The major priority of the proposed protection scheme is its reduction in time (10 ms from the event inception) in distinguishing islanding and protection transmission lines in the presence of distributed generations. [ABSTRACT FROM AUTHOR]

To control a smart-island (which comprises three distributed generation (DG) units with their autonomous converters), based on a nonlinear backstepping control (BSC) scheme, an adaptive reference signal, and a state observer are designed to improve the steady-state performance of the system. An adaptive reference value has been designed and used instead of a constant reference signal to improve the system's steady-state performance, e.g., total harmonic distortion (THD), peak value, and effective value in the voltage control mode. The presented adaptive reference is changed based on the error between the reference signal and the output voltage signal to tend the error to zero. Compared to the classical backstepping controllers, the reference signal is pursued with a fast response and a low steady-state of loads alternations. To demonstrate the efficiency, authenticity, and compatibility of the proposed control strategy, offline digital time-domain simulation studies are carried out on a master-slave organized inverter-based microgrids in various load variations like linear and nonlinear loads in MATLAB/Simulink software environment. The obtained results are compared with previously reported techniques. Moreover, the obtained simulation results are verified by performing laboratory-based experimental tests based on digital signal processing (DSP), which validate the proposed control strategy's accuracy, authenticity, and effectiveness under different conditions. [Display omitted] • A Novel adaptive reference signal has been presented. • The system steady-state performance has been enhanced by applying a state observer in a classic backstepping controller. • The reference signal is pursued with a fast response and a low steady-state ahead of loads alternations. • a master-slave organized inverter-based microgrids has been proposed. [ABSTRACT FROM AUTHOR]

Smart Island (SI) refers to the condition where distributed generation (DG) units e.g. wind turbines (WT), fuel cell (FC), and photovoltaic cells (PV) have to control current, voltage, and frequency of the grid by themselves without any support from the main grid. Therefore, design and implementation of robust controller to overcome disturbances and load variations is very crucial. This paper presents a new approach using General Type-II Fuzzy controller to control smart island in combination with a novel modified optimization algorithm to increase the load sharing throughout the DGs operating in an islanding mode. This case study assumes that there are two DGs in the smart island where each DG has its own responsibilities. In particular, one of the DGs regulates the frequency and voltage based on a reference feedback, while the other DG operates in load current control mode to share load between each DG properly. The simulation results indicate that the suggested controller has a quick response to load alternations with a low steady state error and low THD. Moreover, the proposed controller is independent from system states and other units. The experimental analysis indicate that the suggested control system is effectively capable to coordinate the operations of the DG units in smart island to validate the stable operation of the overall smart island. Image 1 • The main contributions of this paper are as follows: • Introducing a novel and intelligent control model for controlling the smart island, • Establishing a fuzzy based control over load sharing between DG units, voltage, frequency, and current, • Applying fixed frequency PWM modulation which leads to the switching frequency to be constant, • Developing a real-time measuring and amount of desired (reference) signal as an exact proportion of load current. [ABSTRACT FROM AUTHOR]

• Different methods and possible solutions in cyber security in SGs are summarized. • The interactive features of cyber security, modeling and mechanisms are discussed in detail. • The characteristics and applicability of various cyber-attack models are technically presented and analyzed. • The cutting-edge cyber security techniques in SGs and energy systems in various research are discussed. • Possible potential research directions regarding CPSs are highlighted. • Decisive problem-solving approaches are analyzed and concluded comprehensively. Due to the advancement in communication networks, metering and smart control systems, as well as the prevalent use of Internet-based structures, new forms of power systems have seen moderate changes with respect to several aspects of contradictory Cyber–Physical Power Systems (CPPSs). These structures usually have connections between power sections and cyber parts. CPPSs confront newly emerging issues including stability, resiliency, reliability, vulnerability and also security. Studying, analyzing and providing solutions to mitigate or solve these problems highly depend on accurate modeling methods and examining the interaction mechanisms associated with the cyber-security of Smart Grids (SGs). This paper aims to systematically summarize different methods and techniques and to review corresponding solution approaches in cyber-security in energy systems. In the first step, we discuss the interactive features of cyber-security; then, their modeling and mechanisms are reviewed and summarized in detail. Furthermore, the characteristics and applicability of different cyber-attack models are technically discussed and analyzed. The cutting-edge cyber security approaches such as blockchain and quantum computing in SGs and power systems are stated, and recent research directions are highlighted. The decisive problem-solving approaches and defense mechanisms are presented. Finally, some points regarding the role of cyber-security in the future of SGs are presented. [ABSTRACT FROM AUTHOR]

• Optimal allocation of various automation equipment in a real distribution network. • Switches optimal configuration plan is guided to the actual project in various cases. • Branch lines influence is modeled on the automatic equipment configuration. Sectionalizing switches (SSs) have been installed in Distribution networks with the aim of providing maneuver and ring points, so raising service reliability. It is usually assumed that these switches are totally reliable although, in practice, they have not ideal efficiency at all times. In fact, the switches might occasionally face failure, which decreases their capability with the aim of enhancing system reliability. A model with the aim of considering the failure probability of the switches in their optimal placement issue is proposed in this paper. The model aids with the aim of minimizing the whole costs of SSs and the interruption costs incurred through interrupted users. This study uses the discrete Markov chain model with the aim of obtaining the malfunction possibility under various states. Afterwards, the placement problem is solved with the aim of obtaining the global optimal solution with genetic algorithm. The advantage of the suggested model has been investigated according to sensitivity analysis and various scenarios. The research illustrates how the outcomes of the placement issue have been influenced through the uncertainty arising from the possible failure of the switches and how ignoring the uncertainty is able to cause deviation of the anticipated profit from the real one. The efficiency of the suggested procedure has been evaluated and shown through investigating on the Ahwaz city distribution network. The outcomes of simulation prove the ability and precision of the suggested procedure. [ABSTRACT FROM AUTHOR]