Detection of islanding, operation and reconnection of microgrids to utility grid using local information

Summary For proper performance of protection and control systems in microgrids, an islanding event must be detected as soon as possible. In this paper, a novel algorithm is proposed to detect the microgrid operation mode using only the voltage and current samples at the relay location. This approach can be used in all microgrids with any type of source such as synchronous or inverter‐based distributed generators. An optimal method is proposed to determine the input parameters of a classification method by using local information. The goal of the optimization is to minimize the time and maximize the accuracy of microgrid connection state detection. Moreover, in the classification method, three states, that is, islanding, reconnection to the utility grid and other events are considered. The objective function of this problem is defined as the summation of the weighted time factor and detection error. The inputs of the islanding detection problem can be a large number of network parameters, such as frequency, voltage, current, power, their sequence components or rates of changes. Consequently, the variables of the classification problem are the number and the type of input parameters of the classification problem. The optimization problem is solved by using a genetic algorithm‐based, and a support vector machine is used for the classification process. In order to evaluate the validity of the proposed method, different situations are considered for the operation of the grid, and in each case, different events are simulated. The results are compared with similar methods, and the advantage of the proposed method is shown.