Cleberton Reiz

Abstract
Over time, distribution systems have progressed from small-scale systems to complex networks, requiring modernization to adapt to these increasing levels of active loads and devices. It is essential to manage the capacity of distribution networks to support all these new technologies. This work, therefore, presents a method for evaluating the impact of optimal allocation and sizing of DGs and load shedding for response demand programs on distribution networks to improve the reliability and financial performance of electric power systems. The proposed optimization tool uses the Greedy Randomized Adaptive Search Procedure and Tabu Search algorithms. The combined optimization of DG allocation simultaneously with load shedding, reliability indices, load transference, and the possibility of islanded operation significantly improves the quality of the planning proposals obtained by the developed method. The results demonstrate the efficiency and robustness of the proposed method, improving the voltage profile by up to 2.02%, relieving the network capacity, and increasing the load restoration capability and reliability. Statistical analysis is also carried out to highlight the performance of the proposed methodology.

Abstract
Electrical distribution companies have been investing in modernizing their structures, especially operation automation. The integration of information technologies and communications makes fast power restoration during fault events, providing better profit to companies and a more reliable and safe distribution network for customers. A self-healing strategy can be implemented for protection and control devices to work cooperatively, achieving the global purpose of automatic distribution system restoration. Thus, this work proposes a methodology for short-circuit fault detection, isolation of the faulted section, and restoration of downstream sections using neighbor feeders. The protection devices use standardized IEC and ANSI/IEEE functions to sensitize faults in the system and to promote adequate isolation, allowing the consequent restorative process. A genetic algorithm optimizes the devices’ parameters used in the protection scheme, making fastest the isolation process and ensuring the protection system coordination and selectivity. Results obtained using Simulink® allows for verifying the proposed methodology’s behavior and efficiency.

Abstract
Protection and control systems represent an essential part of distribution networks, ensuring the physical integrity of components and improving system reliability. Protection devices isolate a portion of the network affected by a fault, while control devices reduce the number of de-energized loads by transferring loads to neighboring feeders. The integration of distributed generation has the potential to improve the continuity of energy services through islanding operation during outage conditions. In this context, this paper presents a multi-objective optimization approach for the size and allocation of protection and control devices in distribution networks with microgrids supplied by renewable energy sources. Reclosers, fuses, remote-controlled switches, and directional relays are considered in the formulation. The demand and generation uncertainties define the islanding operation and the load transfer possibilities. A genetic algorithm is presented to solve the allocation problem. The compromise programming is performed to choose the best solution from the Pareto front. Results show interesting setups for the protection system and viability of islanding operation.

Abstract
Microgrids are promising to enhance power distribution systems' efficiency, quality, sustainability, and reliability. However, microgrids operation can impose several challenges to traditional protection schemes, like changes in the power flow direction and an increase in short-circuit currents. Microgrids can include several distributed generation technologies with different behaviours during short-circuit conditions, requiring additional protection schemes and devices. In this way, the optimized coordination of reclosers and fuses in distribution networks with directional overcurrent relays, which operate as interconnection devices, might overcome many imposed protection challenges. Regarding different generation technologies, voltage-restrained overcurrent relays and frequency relays are presented as local microgrid protection for rotative and inverter-based distributed generators, respectively. The optimized coordination of these protection devices maximizes microgrid benefits and minimizes operation drawbacks by reducing interruptions impacts and energy not supplied to consumers. This work proposes, thus, a mathematical model for the optimal coordination of protection devices in distribution networks with distributed energy resources operating in grid-connected and islanded modes. The minimization technique of operating times using an elitist genetic algorithm with variable crossover and mutation processes is proposed, as well. The results show adequate coordination using passive and low-cost protection devices.

Abstract
The sustainable development of power distribution systems must evolve into smart grids, where advanced automation with fast communication channels is essential. The analysis of their behavior uses the Hardware-In-the-Loop simulation for studying normal and critical operating conditions. In this work, we propose a hybrid technique for transient simulation in distribution systems by combining the high sample rate of the time domain models for voltage profile and electrical current monitoring with the processing speed of algorithms that operate the quasi-stationary, or permanent, phasor models. The proposed simulation platform is also based on the state of the art of standardized communication protocols of the power system. Its evaluation is performed using the comparison with specialized commercial software to assess the transient simulation. The time overcurrent protection function and the verification of messages exchanged between the simulator and the tested device highlights the applicability of the proposed methodology.