Accurate fault location is challenging due to the distribution network’s various branches, complicated topology, and the increasing penetration of distributed energy resources (DERs). The diagnostics for power system faults are based on fault localization, isolation, and smart power restoration. Adaptive multi-agent systems (MAS) can improve the reliability, speed, selectivity, and robustness of power system protection. This paper proposes a MAS-based adaptive protection mechanism for fault location in smart grid applications. This study developed a novel distributed intelligent-based multi-agent prevention and mitigation technique for power systems against electrical faults and cyber-attacks. Simulation studies are performed on a platform constructed by interconnecting the power distribution system of Kenitra city developed in MATLAB/SIMULINK and the multi-agent system implemented in the JADE platform. The simulation results demonstrate the effectiveness of the proposed technique.

Accurate Fault location in an electric Power Distribution System (EPDS) is important in maintaining system reliability. Several methods have been proposed in the past. However, these methods require a radial power flow systems to be studied. Nowadays diverse technologies for distributed electricity production or generation (DG) such us Wind, PV... are developed. The integration of these self-productions to the conventional networks modifies the classical power transit and changes the fault signals amplitudes. In this paper, a new impedance-based Fault Location (FL) method is presented. It is based on the voltage-sag calculation. The effectiveness of the proposed technique is demonstrated using a radial power flow system first, and then, by connecting a second generator to the network. The test results are achieved from the numerical simulation using the data of a distribution line recognized in the literature.

The smart grid concept is predicated upon the pervasive use of advanced digital communication, information techniques, and artificial intelligence for the current power system, to be more characteristics of the real-time monitoring and controlling of the supply/demand. Microgrids are modern types of power systems used for distributed energy resource (DER) integration. However, the microgrid energy management, the control, and protection of microgrid components (energy sources, loads, and local storage units) is an important challenge. In this paper, the distributed energy management algorithm and control strategy of a smart microgrid is proposed using an intelligent multi-agent system (MAS) approach to achieve multiple objectives in real-time. The MAS proposed is developed with co-simulation tools, which the microgrid model, simulated using MATLAB/Simulink, and the MAS algorithm implemented in JADE through a middleware MACSimJX. The main study is to develop a new approach, able to communicate a multi-task environment such as MAS inside the S-function block of Simulink, to achieve the optimal energy management objectives.

A doubly-fed induction generator is the most widely used as a wind turbine generator. Due to its drawbacks, doubly fed induction generator (DFIG) is extremely sensitive to grid disturbances, and the fragility of some components which are costly to the producer. Also, its acquisition value is very high in terms of maintenance time or component cost, causing substantial harm to both the energy production and power supplier. It is required that the DFIG components must be protected, especially power electronics devices and DC-Link capacitor. Therefore, this paper presents an improved crowbar strategy for DFIG. This method is based on the AI technique concept of utilizing a fuzzy logic controller. The main goal of this project is to improve the system performance by reducing the dangerous oscillations of electromagnetic torque, DC-link voltage, and rotor current during fault. This work consists of replacing the hysteresis control for the crowbar with fuzzy logic to realize crowbar-FLC. The proposed crowbar is based on free light chain (FLC) depending on rotor currents and DC-link voltage measurements. The control strategy is simulated in the MATLAB Simulink platform to evaluate the efficiency of the suggested technique.