This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE TRANSACTIONS ON POWER DELIVERY 1 Adaptive Fuzzy Sandia Frequency-Shift Method for Islanding Protection of Inverter-Based Distributed Generation Hesan Vahedi, Student Member, IEEE, and Mehdi Karrari Abstract—Sandia Frequency Shift (SFS) is one of the active is- landing detection methods that rely on frequency drift to detect an islanding condition. Recently, SFS has been widely applied to inverter-based distributed generations due to its small Non-Detec- tion Zone (NDZ). The NDZ in SFS method highly depends on its design parameters. Improper tuning of these parameters may re- sult in failure of the method. In the proposed method in this paper, the load parameters are estimated online and the SFS parameter is adaptively tuned to eliminate NDZ using fuzzy load parameter estimation (FLPE) method. Simulation results verify the excellent performance of the proposed method. Index Terms—Distributed generation (DG), fuzzy estimation, in- verter, islanding, Sandia frequency shift. I. INTRODUCTION T HE integration of small converters connected to distribu- tion networks (DNs) has experienced fast development during the last few decades, mainly due to the massive pen- etration of renewable energy sources. This has given rise to certain technical issues, such as islanding of distributed gen- eration (DG). According to IEEE 1547 and UL 1741 in [1] and [2], islanding protection was mandated and defined as a condition where a portion of an electric power system is en- ergized solely and separated from the rest of the electric power system. The main part of islanding protection is to accurately detect the moment of islanding and isolate the DG from the DN in a timely manner. Unintentional islanding of DG may result in power-quality (PQ) issues, interference with grid protection devices, and low safety for consumers. There is profound and extended research on different islanding detection methods in [3]–[8]. Despite mandating on isolation of the DG during the islanding condition, some researchers are investigating the situ- ation where DG has the ridethrough capability and is authorized to energize the load after islanding [9]–[12]. This option can add more complexity to the control system and costs as well. In general, islanding detection methods are categorized into three main topics; namely: passive, active, and communication- based methods [3]. Passive methods continuously monitor the system parameters, such as voltage, frequency, harmonic distor- tion, etc. In this islanding detection method, one or more of these Manuscript received August 09, 2011; revised March 22, 2012; accepted September 16, 2012. Paper no. TPWRD-00652-2011. The authors are with the Electrical Engineering Department, Amirkabir University of Technology, Tehran 15914, Iran (e-mail: h.vahedi@aut.ac.ir; karrari@aut.ac.ir). Digital Object Identifier 10.1109/TPWRD.2012.2219628 parameters has been considerably changed when the grid is dis- connected. Setting a proper threshold can help to differentiate between the islanding and grid-connected conditions. Upper and lower thresholds have been provided to avoid undesirable trip- ping of the DG due to other system disturbances. Sometimes, the load closely matches the DG capacity. In such cases, the amount of frequency or voltage deviation will not be sufficient to trigger the islanding detection system [14]. Passive islanding detection methods suffer from large nondetection zones (NDZs) [13], [14]. NDZs are defined as loading conditions for which an islanding detection method would fail to operate in a timely manner. Active methods are cheaper and more reliable options which have been designed to force the DG to be unstable in islanding mode. This methods use the positive feedback feature to drift the voltage frequency or magnitude during the islanding con- dition. The main advantage of the active techniques over pas- sive techniques is their small NDZ [14]. Active methods in- clude slide-mode frequency shift (SMS) [8], active frequency drift (AFD) [6] and Sandia frequency shift (SFS) [7]. In [6] and [7], by analyzing the NDZ, it was inferred that SFS is the most effective islanding detection method among the others. SFS, like most of other methods, has been shown to have an NDZ for loads with a large , a small , and/or high ; or in other words, a high value of load-quality factor . How- ever, it has also been shown experimentally that this NDZ can be made extremely small. A mapping of this NDZ in the load space can be found in the literature [7]. A great protec- tion against the islanding condition can be manufactured for any practical , if the SFS gain factor “ ” is sufficiently large, but this may lead to false trips and reduced power quality [3]. Also in [15], the impact of frequency-dependent load’s active power on the SFS performance and the solution for increased accuracy is presented. This paper presents a new strategy for NDZ elimination of the SFS method based on fuzzy-load parameter estimation (FLPE). The amount of load parameters and can be estimated and, consequently, the load quality factor can be calculated from mathematical formulation in the context [16]. With estimation of the load quality factor, a proper amount of “ ” can be set in the SFS formulation to prevent disability of islanding protection and nuisance tripping. The results are then validated through MATLAB/Simulink software. This paper is organized as follows: Section II presents a system under study. Section III consists of a brief review on SFS method. Section IV presents fuzzy parameter estimation, 0885-8977/$31.00 © 2012 IEEE