In current distribution automations design, fault flags generated by overcurrent relays are used to detect the feeder fault section. With the integration of distributed generations (DG), fault currents could be contributed from different directions and jeopardize the fault detection function. A large fault current contributed by a DG flows from downstream of a feeder could be detected by the overcurrent relay and lead to the confusion in fault detection function. In this thesis, adjunction current measurements and fault flags are utilized to minimize the possibility of mis-identification of fault section. The structure and data flow of a Java agent development framework (JADE) is adopted for feeder fault detection, identification and service restoration (FDIR). Based on information from local measurements and other agents, the FDIR function can be better conducted by local agents. Test results indicate that multi-agent systems can be used to improve system reliability and reduce service interruption time.

Fault location reveals the exact information needed for utility crews to timely and promptly perform maintenance and system restoration. Therefore, accurate fault location is a key function in reducing outage time and enhancing power system reliability. Modern power systems are witnessing a trend of integrating more distributed generations (DG) into the grid. DG power outputs may be intermittent and can no longer be treated as constants in fault location method development. DG modeling is also difficult for fault location purpose. Moreover, most existing fault location methods are not applicable to simultaneous faults. To solve the challenges, this dissertation proposes three impedance-based fault location algorithms to pinpoint simultaneous faults for power transmission systems and distribution systems with high penetration of DGs. The proposed fault location algorithms utilize the voltage and/or current phasors that are captured by phasor measurement units. Bus impedance matrix technique is harnessed to establish the relationship between the measurements and unknown simultaneous fault locations. The distinct features of the proposed algorithms are that no fault types and fault resistances are needed to determine the fault locations. In particular, Type I and Type III algorithms do not need the information of source impedances and prefault measurements to locate the faults. Moreover, the effects of shunt capacitance are fully considered to improve fault location accuracy. The proposed algorithms for distribution systems are validated by evaluation studies using Matlab and Simulink SimPowerSystems on a 21 bus distribution system and the modified IEEE 34 node test system. Type II fault location algorithm for transmission systems is applicable to untransposed lines and is validated by simulation studies using EMTP on a 27 bus transmission system. Fault area identification method is proposed to reduce the number of line segments to be examined for fault location. In addition, an optimal fault location method that can identify possible bad measurement is proposed for enhanced fault location estimate. Evaluation studies show that the optimal fault location method is accurate and effective. The proposed algorithms can be integrated into the existing energy management system for enhanced fault management capability for power systems.

Classical view of power system is characterized by a unidirectional power flow from centralized generation to consumers. Power system deregulation gave impetus to a modern view by introducing distributed generations (DGs) into distribution systems, leading to a bi-directional power flow. Several benefits of embedding DGs into distribution systems, such as increased reliability and reduced system losses, can be achieved. However, when a zone of the distribution system remains energized after being disconnected from the grid, DGs become islanded and early detection is needed to avoid several operational issues. In response to this call, a wavelet-based approach that uses the mean voltage index is proposed in this work to detect islanding operation in distribution systems embedding DGs. The proposed approach has been tested in several islanding and non-islanding scenarios using IEEE 13-bus distribution system. The results have shown the effectiveness of the proposed approach compared to other islanding approaches previously published in the literature. / UOIT

Electrical distribution networks face many operational challenges as various renewable distributed generation (DG), such as solar photovoltaic (PV) systems and wind, become part of their structure. Unlike conventional distribution systems, where the only unpredictable aspect is the load level, the intermittent nature of DG poses additional uncertainty levels for distribution system operators (DSO). The voltage quality problem considers the most restrictive issue that hinders high DG integration into distribution grids. Voltage deviates from the nominal grid voltage limits due to the excess power from the DG. DSOs are accustomed to improving the voltage profile by optimal adjustments of the on-load tap changers, voltage regulator taps and capacitor banks. Nevertheless, due to the frequent variability of the output energy from DG, these devices may fail in doing the needful. Battery energy storage systems (BESS) and smart PV inverter functionalities are regarded as promising solutions to promote the seamless integration of renewable resources into distribution networks. BESS are utilized to store the surplus energy during the high penetration of renewable DG that causes high voltage levels and discharge the stored energy when the distribution grid is heavily loaded, which leads to the low voltage levels. Smart PV inverters regulate the network voltage by controlling the reactive power injection or absorption at the inverter end. This dissertation proposes a management strategy that coordinates BESS and smart PV inverter reactive power capability to improve voltage quality in the distribution systems with high PV and wind penetrations. The proposed management method is based on a bi-level optimization algorithm consisting of upper and lower optimization levels. The proposed method determines the optimal location, capacity, numbers and BESS charging and discharging rates to support the distribution system voltage and to ensure optimal deployment of BESS. Case studies are conducted to evaluate the proposed voltage control method. The large size PV system and wind turbine impacts are studied and simulated on the modified IEEE-34 bus test feeder. In addition, the proposed method is applied to the modified IEEE low voltage test feeder to investigate the effectiveness of installing residential rooftop PV systems on the distribution system's voltage. Experimental results show promising outcomes of the proposed method in controlling the distribution networks' voltage. In addition, a day-ahead forecast of PV power output is developed in this dissertation to assist the DSOs to accurately predict the future amounts of PV energy available and reinforcing the decision-making process of batteries operation. Hybrid forecasting models are proposed based on machine learning algorithms, which utilize support vector regression and backpropagation neural network, optimized with three metaheuristic optimization algorithms, namely Social Spider Optimization (SSO), Particle Swarm Optimization (PSO) and Cuckoo Search Optimization (CSO). These algorithms are used to improve the predictive efficacy of the selected algorithms, where the optimal selection of their hyperparameters and architectures plays a significant role in yielding precise forecasting outcomes. / Doctor of Philosophy / The need for more renewable energy has grown significantly, and many countries are embracing these technologies. However, the integration of distributed generation (DG), such as PV systems and wind turbines, poses several operational problems to the distribution system. The voltage problem represents the most significant issue that needs to be addressed. The traditional voltage control equipment may not cope with the rapid fluctuation and may impact their service life. The continuous developments in the battery energy storage systems (BESS) and the smart PV inverter technologies result in increasing the hosting capacity of DG. BESS can store the excess power from the distributed generators and supply this energy to the grid for different operational objectives. On the other hand, the advanced PV inverter's reactive power capability can be exploited from which the grid can attain many benefits. This dissertation aims at providing a reliable control method to the voltage profile in distribution networks embedded with high PV and wind energy by optimal coordination between the operation of the BESS and the smart PV inverter. In addition, the solar forecasting can mitigate the uncertainty associated with PV system generation. In this dissertation, the PV power forecasting application is applied in the distribution system to control the voltage. Through utilizing PV power forecasting, the decision-making for battery operation can be upheld and reinforced. The BESS can store the surplus energy from the PV system as needed and supply it back in low PV power incidents. Experimental results indicate that proper coordination between the BESS and smart PV inverter is beneficial for distribution system operation that can seamlessly integrate PV and wind energy.

L’intégration des producteurs décentralisés (DG) dans un réseau de distribution peut modifier le profil de tension et influencer le réglage de tension conventionnel. Pour le bon fonctionnement du réseau, le raccordement des DG ainsi que les charges grosses sont limités par le dimensionnement du réseau. Les travaux de cette thèse ont pour but de proposer une approche du réglage de tension dans un réseau de distribution avec producteur, en appuyant sur la flexibilité de la demande. Les moyens de réglage de tension seront constitués du régleur en charge (OLTC), la régulation de DG ainsi que la demande flexible. Une optimisation centralisée de type MINLP est proposée pour coordonner ces moyens de réglage. Il est montré que si les moyens de l’OLTC et de la puissance réactive ne suffissent pas de lever la contrainte de tension, il faut réduire la puissance active de producteur. Pour le gain de producteur, la demande flexible peut être considérée comme une source active. La modulation de « demand response » (DR) utilisant les charges thermiques est alors proposée au réglage de tension. L’effet de rebond est pris en compte pour les charges thermiques afin de ne pas affecter le profil de tension après l’action de DR. Ces travaux permettent d’envisager un réglage de tension plus active dans le réseau intelligent et augmenter la flexibilité du réseau. / Growth of distributed generations (DG) in actual distribution networks will bring voltage issues that cannot be fixed by conventional voltage control means. For the sake of network safety, the size of DG and load in a distribution network is limited by the network parameters. The research described in this thesis aims to propose a voltage control strategy on distribution networks using the flexibility of demand. The voltage control means will consist of the on load tap changer (OLTC), the regulation of DG, and flexible demand. A centralized optimization of MINLP type is proposed to coordinate these voltage control means. It shows if it is not able to remove the voltage constraint with OLTC and reactive power regulation, then it must reduce the active power of DG. In order not to reduce active power of DG, the flexible demand is considered as an active source to take part in voltage control. The demand response (DR) modulation using thermal loads is thus proposed for voltage control. For the thermal load, the cold load pick-up (CLPU) effect must be taken into account in order not to affect the voltage profile after DR action. This work allows us to consider a voltage control strategy more active in smart distribution network and improve the flexibility of network.

L’intégration des producteurs décentralisés (DG) dans un réseau de distribution peut modifier le profil de tension et influencer le réglage de tension conventionnel. Pour le bon fonctionnement du réseau, le raccordement des DG ainsi que les charges grosses sont limités par le dimensionnement du réseau. Les travaux de cette thèse ont pour but de proposer une approche du réglage de tension dans un réseau de distribution avec producteur, en appuyant sur la flexibilité de la demande. Les moyens de réglage de tension seront constitués du régleur en charge (OLTC), la régulation de DG ainsi que la demande flexible. Une optimisation centralisée de type MINLP est proposée pour coordonner ces moyens de réglage. Il est montré que si les moyens de l’OLTC et de la puissance réactive ne suffissent pas de lever la contrainte de tension, il faut réduire la puissance active de producteur. Pour le gain de producteur, la demande flexible peut être considérée comme une source active. La modulation de « demand response » (DR) utilisant les charges thermiques est alors proposée au réglage de tension. L’effet de rebond est pris en compte pour les charges thermiques afin de ne pas affecter le profil de tension après l’action de DR. Ces travaux permettent d’envisager un réglage de tension plus active dans le réseau intelligent et augmenter la flexibilité du réseau. / Growth of distributed generations (DG) in actual distribution networks will bring voltage issues that cannot be fixed by conventional voltage control means. For the sake of network safety, the size of DG and load in a distribution network is limited by the network parameters. The research described in this thesis aims to propose a voltage control strategy on distribution networks using the flexibility of demand. The voltage control means will consist of the on load tap changer (OLTC), the regulation of DG, and flexible demand. A centralized optimization of MINLP type is proposed to coordinate these voltage control means. It shows if it is not able to remove the voltage constraint with OLTC and reactive power regulation, then it must reduce the active power of DG. In order not to reduce active power of DG, the flexible demand is considered as an active source to take part in voltage control. The demand response (DR) modulation using thermal loads is thus proposed for voltage control. For the thermal load, the cold load pick-up (CLPU) effect must be taken into account in order not to affect the voltage profile after DR action. This work allows us to consider a voltage control strategy more active in smart distribution network and improve the flexibility of network.