Detection of unintentional islanding is critical in microgrids in order to guarantee personal safety and avoid equipment damage. Most islanding detection techniques are based on monitoring and detecting abnormalities in magnitudes such as frequency, voltage, current and power. However, in normal operation, the utility grid has fluctuations in voltage and frequency, and grid codes establish that local generators must remain connected if deviations from the nominal values do not exceed the defined thresholds and ramps. This means that islanding detection methods could not detect islanding if there are fluctuations that do not exceed the grid code requirements, known as the non-detection zone (NDZ). A survey on the benefits of islanding detection techniques is provided, showing the advantages and disadvantages of each one. NDZs size of the most common passive islanding detection methods are calculated and obtained by simulation and compared with the limits obtained by ENTSO-E and islanding standards in the function of grid codes requirements in order to compare the effectiveness of different techniques and the suitability of each one.

Stand-alone hybrid power plants based on renewable energy sources are becoming a more and more interesting alternative. However, their management is a complex task because there are many variables, requirements and restrictions as well as a wide variety of possible scenarios. Though a proper sizing of the power plant is necessary to obtain a competitive cost of the energy, smart management is key to guarantee the power supply at a minimum cost. In this work, a novel hybrid power plant control strategy is designed, implemented and simulated under a wide variety of scenarios. Thereby, the proposed control algorithm aims to achieve maximum integration of renewable energy, reducing the usage of non-renewable generators as much as possible and guaranteeing the stability of the microgrid. Different scenarios and case studies have been analyzed by dynamic simulation to verify the proper operation of the power plant controller. The main novelties of this work are: (i) the stand-alone hybrid power plant management regarding a battery energy storage system as a part of the spinning reserve, (ii) the characterization of the largest loads as non-priority loads, (iii) the minimization of the needed spinning reserve and fuel consumption from diesel generators.