## 1 Introduction  
Distribution generation (DG) based on renewable energy resources provides power to local loads in coordination with the main power grid [1; 2; 3]. DG is now commonly installed in electric power systems (EPSs) [4]. At present, EPSs have become increasingly complex in terms of their operation and controls because of the significant penetration of DGs [5]. The islanding phenomenon of DG has been regarded as one of the major issues of increased DGs in EPSs. Islanding is defined as a condition in which a portion of the utility with a DG and load remains energized even though that portion is disconnected from the remainder of the utility system, as shown in Figure 1[6]. Since islanding causes safety issues for both utility service personnel and power system equipment, it is desirable that it is prevented [7]. However, as the utilization of DG has increased rapidly in EPSs, a possible significant loss of DG due to a short disturbance could potentially aggravate the problem and cause a wide-spread blackout.  
As a result of this issue, new requirements for grid-connected technology, including ride-through and anti-islanding technology, which are more sophisticated and complex, have been recently proposed [8, 9]. According to these new requirements, ride-through is the ability to withstand voltage and frequency disturbances, whereas trip is the cessation of output without immediate return to service. As trip requirements are related to the islanding of DG, a requirement for anti-islanding within two seconds is applied when DG is isolated from the upstream part of the area EPS. To date, as shown in Figure 2, a variety of anti-islanding methods (AIMs), including local techniques and remote techniques, have been developed and implemented. Remote methods depend on communication techniques between DG and the EPS but tend to be more costly than local methods [10]. Local methods are usually implemented into the grid-connected inverter of DG and they are typically classified as passive and active methods. Passive methods, based on power mismatches between DG power and local loads, detect islanding only by monitoring several system parameters such as voltage magnitude [11], frequency [12], phase jump [13], and harmonic detection [14]. On the other hand, active islanding methods perturb the DG inverter current in order to break the power balance between DG and local loads in the form of frequency drifting [15, 16] and reactive power drifting [17, 18]. In addition, neural network, pattern recognition and machine learning-based AIMs have been proposed [19, 20]. Since most anti-islanding functions of inverter-based DG have been based on the frequency of the inverter voltage, it is more difficult to detect islanding under wider frequency trip settings. To solve this technical barrier, this paper is based on a correlation technique [21].  
In this paper, study of a correlation-based AIM under wider frequency trip settings for distributed generation is presented. A non-detection zone (NDZ) by frequency trip settings is analyzed under IEEE Std. 1547-2018, compared with the previous settings under IEEE Std. 1547-2003. Then, a newly proposed correlation-based AIM method is presented with a corresponding simulation for its verification.