This thesis experimentally validates the performance of an active islanding detection method under various scenarios. It is also analytically shown that the islanding detection method has a non-detection zone (NDZ), and a method to eliminate the NDZ is proposed. Moreover, the performance of an autonomous mode controller for islanded DG units is experimentally evaluated. Based on a robustness analysis, it is shown that the controller, which is basically designed for the nominal plant, can maintain the stability of the system despite of significant load uncertainties. The feasibility of the islanding detection method for islanding detection in two-DG systems is also experimentally investigated. Moreover, a control strategy for autonomous operation of two-DG systems is proposed, and its performance is experimentally evaluated. Then, adopting the islanding detection method and the proposed control strategy, the viability of smooth transitions from grid-connected modes to autonomous (islanded) modes in two-parallel DG systems is experimentally validated.

This thesis experimentally validates the performance of an active islanding detection method under various scenarios. It is also analytically shown that the islanding detection method has a non-detection zone (NDZ), and a method to eliminate the NDZ is proposed. Moreover, the performance of an autonomous mode controller for islanded DG units is experimentally evaluated. Based on a robustness analysis, it is shown that the controller, which is basically designed for the nominal plant, can maintain the stability of the system despite of significant load uncertainties. The feasibility of the islanding detection method for islanding detection in two-DG systems is also experimentally investigated. Moreover, a control strategy for autonomous operation of two-DG systems is proposed, and its performance is experimentally evaluated. Then, adopting the islanding detection method and the proposed control strategy, the viability of smooth transitions from grid-connected modes to autonomous (islanded) modes in two-parallel DG systems is experimentally validated.

This thesis proposes and evaluates the application of a low-frequency disturbance injection, as an active islanding detection method, in a microgrid with multiple electronically-interfaced Distributed Generation (DG) units. Each DG unit is interfaced to the microgrid through a two-level Voltage-Sourced Converter (VSC). The low-frequency disturbance signal for islanding detection is injected through the q-axis control of each VSC unit. The low-frequency signal is at 1 Hz with an amplitude of up to 2.5 % of the rated VA of the VSC unit and augments the reference signal of the q-axis control. The effectiveness of the low-frequency injection for islanding detection is examined under two distinct VSC control scenarios. In the first scenario, each VSC only injects pre-determined real- and reactive-power components in the system and does not participate in frequency/voltage control. In the second scenario, the VSC controls are also equipped with frequency/real-power and voltage/reactive-power droop characteristics and thus share power and participate in frequency and voltage control of the microgrid, specifically in the islanded mode. The investigations reported in this thesis show that the proposed islanding detection method can effectively detect an islanding event under both VSC control strategies, subject to the conditions that UL and/or IEEE anti-islanding standards impose. The studies show that an islanding event can be detected within 536 ms subsequent to the instant of islanding. As part of this thesis, an eigen analysis software tool has been developed that can systematically investigate the impact of low-frequency disturbance injection on the small-signal stability and dynamic performance of the microgrid, prior and subsequent to an islanding event. This thesis concludes that the low-frequency disturbance injection-based method can be successfully applied to a multi-DG system, since (i) islanding detection is achieved within applicable standards requirements by all DG units in the system, and (ii) the low-frequency disturbance injection signal has no noticeable impact on the dynamics nor the small-signal stability of the system if its magnitude is kept below a pre specified limit.

This thesis proposes and evaluates the application of a low-frequency disturbance injection, as an active islanding detection method, in a microgrid with multiple electronically-interfaced Distributed Generation (DG) units. Each DG unit is interfaced to the microgrid through a two-level Voltage-Sourced Converter (VSC). The low-frequency disturbance signal for islanding detection is injected through the q-axis control of each VSC unit. The low-frequency signal is at 1 Hz with an amplitude of up to 2.5 % of the rated VA of the VSC unit and augments the reference signal of the q-axis control. The effectiveness of the low-frequency injection for islanding detection is examined under two distinct VSC control scenarios. In the first scenario, each VSC only injects pre-determined real- and reactive-power components in the system and does not participate in frequency/voltage control. In the second scenario, the VSC controls are also equipped with frequency/real-power and voltage/reactive-power droop characteristics and thus share power and participate in frequency and voltage control of the microgrid, specifically in the islanded mode. The investigations reported in this thesis show that the proposed islanding detection method can effectively detect an islanding event under both VSC control strategies, subject to the conditions that UL and/or IEEE anti-islanding standards impose. The studies show that an islanding event can be detected within 536 ms subsequent to the instant of islanding. As part of this thesis, an eigen analysis software tool has been developed that can systematically investigate the impact of low-frequency disturbance injection on the small-signal stability and dynamic performance of the microgrid, prior and subsequent to an islanding event. This thesis concludes that the low-frequency disturbance injection-based method can be successfully applied to a multi-DG system, since (i) islanding detection is achieved within applicable standards requirements by all DG units in the system, and (ii) the low-frequency disturbance injection signal has no noticeable impact on the dynamics nor the small-signal stability of the system if its magnitude is kept below a pre specified limit.

This thesis presents a method of detecting electrical islands in low voltage distributed generator networks by measuring negative sequence impedance differences between islanded and utility connections. Extensive testing was conducted on a commercial building and 25 kV distributed generator fed network by measuring naturally occurring and artificially injected negative sequence components. Similarly, this technique was tested using the IEEE 399-1990 bus test case using the EMTP software. The practical measurements have been matched to simulations where further system performance characteristics of detecting power system islands has been successfully demonstrated. Measured results indicate that unbalanced load conditions are naturally occurring and readily measurable while deliberately unbalanced loads can increase the accuracy of negative sequence impedance islanding detection. The typically low negative sequence impedance of induction motors was found to have only a small effect in low voltage busses, though large machines can effect the threshold settings. Careful placement of the island detector is required in these situations. The negative sequence impedance measurement method is an improvement on previous impedance measurement techniques for islanding detection due to its accuracy, and distinctly large threshold window which have challenged previous impedance based islanding detection techniques.

This thesis presents a method of detecting electrical islands in low voltage distributed generator networks by measuring negative sequence impedance differences between islanded and utility connections. Extensive testing was conducted on a commercial building and 25 kV distributed generator fed network by measuring naturally occurring and artificially injected negative sequence components. Similarly, this technique was tested using the IEEE 399-1990 bus test case using the EMTP software. The practical measurements have been matched to simulations where further system performance characteristics of detecting power system islands has been successfully demonstrated. Measured results indicate that unbalanced load conditions are naturally occurring and readily measurable while deliberately unbalanced loads can increase the accuracy of negative sequence impedance islanding detection. The typically low negative sequence impedance of induction motors was found to have only a small effect in low voltage busses, though large machines can effect the threshold settings. Careful placement of the island detector is required in these situations. The negative sequence impedance measurement method is an improvement on previous impedance measurement techniques for islanding detection due to its accuracy, and distinctly large threshold window which have challenged previous impedance based islanding detection techniques.

Opportunities for enhancing the security and reliability of power supply as well as the utilization of renewable and efficient energy sources have generated major interest in Microgrids. A microgrid typically consists of interconnected loads, distributed generators (DG) and energy storages, and should be able to operate in parallel with the utility grid or as a power-island. The main focus of this thesis is on the transition between parallel and islanded operation of a microgrid. A literature review on existing microgrids was carried out. Based on the survey, a microgrid test system was implemented on PSCAD/EMTDC simulation program. The microgrid controls essential for the study and a load shedding scheme were designed and implemented. When the microgrid changes from parallel to islanded operation, its controls need to be changed. It was found that delays in microgrid control mode transition can impact the amount of load need to be shed to preserve the frequency stability and the power quality of the islanded microgrid. The importance of fast detection of islanding was therefore highlighted. The IEEE standard 1547.4-2011 recommends application of the existing DG synchronization criteria for microgrid synchronization. The adequacy of these criteria for synchronization of a microgrid with highly unbalanced loading was investigated. It was found that the required criteria can be met with the support of switched capacitors for voltage balancing, and a circuit breaker supervised by a synchro-check relay is sufficient to successfully reconnect an islanded microgrid back to the utility. In order to meet the requirement for fast detection of islanding of microgrids, new islanding detection technique was proposed. In the proposed scheme, Discrete Wavelet Transform was used to extract features from transient current and voltage signals, and then a Decision Tree classifier was employed to distinguish islanding events from other transients. Simulation based tests asserted that the proposed technique has a high reliability and fast response compared to most existing islanding detection methods. Also, the detection time of the proposed method was invariant with the power imbalance in the microgrid, and gave a zero non-detection-zone with any type of generator.

Opportunities for enhancing the security and reliability of power supply as well as the utilization of renewable and efficient energy sources have generated major interest in Microgrids. A microgrid typically consists of interconnected loads, distributed generators (DG) and energy storages, and should be able to operate in parallel with the utility grid or as a power-island. The main focus of this thesis is on the transition between parallel and islanded operation of a microgrid. A literature review on existing microgrids was carried out. Based on the survey, a microgrid test system was implemented on PSCAD/EMTDC simulation program. The microgrid controls essential for the study and a load shedding scheme were designed and implemented. When the microgrid changes from parallel to islanded operation, its controls need to be changed. It was found that delays in microgrid control mode transition can impact the amount of load need to be shed to preserve the frequency stability and the power quality of the islanded microgrid. The importance of fast detection of islanding was therefore highlighted. The IEEE standard 1547.4-2011 recommends application of the existing DG synchronization criteria for microgrid synchronization. The adequacy of these criteria for synchronization of a microgrid with highly unbalanced loading was investigated. It was found that the required criteria can be met with the support of switched capacitors for voltage balancing, and a circuit breaker supervised by a synchro-check relay is sufficient to successfully reconnect an islanded microgrid back to the utility. In order to meet the requirement for fast detection of islanding of microgrids, new islanding detection technique was proposed. In the proposed scheme, Discrete Wavelet Transform was used to extract features from transient current and voltage signals, and then a Decision Tree classifier was employed to distinguish islanding events from other transients. Simulation based tests asserted that the proposed technique has a high reliability and fast response compared to most existing islanding detection methods. Also, the detection time of the proposed method was invariant with the power imbalance in the microgrid, and gave a zero non-detection-zone with any type of generator.

This thesis presents a method of detecting electrical islands in low voltage distributed generator networks by measuring negative sequence impedance differences between islanded and utility connections. Extensive testing was conducted on a commercial building and 25 kV distributed generator fed network by measuring naturally occurring and artificially injected negative sequence components. Similarly, this technique was tested using the IEEE 399-1990 bus test case using the EMTP software. The practical measurements have been matched to simulations where further system performance characteristics of detecting power system islands has been successfully demonstrated. Measured results indicate that unbalanced load conditions are naturally occurring and readily measurable while deliberately unbalanced loads can increase the accuracy of negative sequence impedance islanding detection. The typically low negative sequence impedance of induction motors was found to have only a small effect in low voltage busses, though large machines can effect the threshold settings. Careful placement of the island detector is required in these situations. The negative sequence impedance measurement method is an improvement on previous impedance measurement techniques for islanding detection due to its accuracy, and distinctly large threshold window which have challenged previous impedance based islanding detection techniques. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

Nowadays islanding has become a big issue with the increasing use of distributed generators in power system. In order to effectively detect islanding after DG disconnects from main source, author first studied two passive islanding methods in this thesis: THD&VU method and wavelet-transform method. Compared with other passive methods, each of them has small non-detection zone, but both of them are based on the threshold limit, which is very hard to set. What’s more, when these two methods were applied to practical signals distorted with noise, they performed worse than anticipated. Thus, a new composite intelligent based method is presented in this thesis to solve the drawbacks above. The proposed method first uses wavelet-transform to detect the occurrence of events (including islanding and non-islanding) due to its sensitivity of sudden change. Then this approach utilizes artificial neural network (ANN) to classify islanding and non-islanding events. In this process, three features based on THD&VU are extracted as the input of ANN classifier. The performance of proposed method was tested on two typical distribution networks. The obtained results of two cases indicated the developed method can effectively detect islanding with low misclassification.