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The grid penetration of distributed generation systems is rapidly increasing to meet the energy demands. In the grid connected operation of these systems, the islanding scenarios are considered as a critical threat for stable operation of the utility. This paper aims at developing an islanding classification technique to efficiently detect the grid abnormalities and classify the islanding scenario. The process involves generation of data sets corresponding to various grid abnormalities, and training them with a machine learning classifier. To realize this development, a 10 kW three-phase grid connected photovoltaic (PV) system is simulated and compiled in Typhoon hardware-in-loop (HIL) environment to get different data sets for grid abnormality conditions. Further, the data is trained with the k-nearest neighbor (kNN) classified to develop the islanding classification mechanism. The efficiency of trained classifier is 94.2 %, and has the capability for efficient classification at a speed of approximately 17000 observations per second.

The usage of the Photovoltaic (PV) power systems has been increased dramatically, due to the abundant of the solar irradiation, and the government incentives everywhere. In most of the developed countries, the standards for connecting the PV systems to the grid has been set and is already applied. The incentives and regulations that supports PV systems are increasing day by day in Turkey. Because of this regulations more and more PV systems are connecting to the grid. Such high penetration of the PV systems in the distribution network leads to voltage disturbances. This paper studies the causes and effects of the voltage problem and proposes the best solutions to; mitigate the voltage disturbances and increase the distribution network stability. © 2021 IEEE.

This work presents the mapping of grid-connected photovoltaic systems supported by the Normative Resolution (NR) of the National Agency of Electric Energy (ANEEL) No 482/2012 in the city of Curitiba. Firstly, a brief introduction was made justifying the reasons that led to the development of this study, followed by the explanation about the methodology, procedures and criteria adopted in the study. A general mapping of all on-grid photovoltaic systems supported by NR No 482/2012 installed in the city of Curitiba, identified by class, is presented, indicating how the urban distribution of these photovoltaic systems occurs, and it is possible to observe in which regions the highest prevalence of installations occurs. From this, the general characterization of these photovoltaic systems is performed, classifying them by class, number of installed systems, power, number of modules, total occupied area, average power of modules and average efficiency of photovoltaic systems. Considerations are also raised regarding the reliability of the Database of Distributed Generation Consumer Units made available by ANEEL.

This is a study that contemplates the analysis of the main characteristics of 8 grid connected photovoltaic systems (GCPVS), 3 of which are located in the city of Curitiba-PR and 5 located in the city of Blumenau-SC. Data were collected on irradiation in the horizontal plane, generated energy and rainfall, being the first two to calculate the merit indexes, such as Yield, Performance Ratio and Capacity Factor - of those on grid connected Photovoltaic systems.

The last 20 years have presented a favorable scenario for the incorporation of renewable energy sources into the energy matrix of developing countries. This situation promoted grid connected photovoltaic generation systems (GCPVS) to become one of the main protagonists in this new concept of energy matrix. In some developing countries the use of such systems is in its beginning. Promotion policies and technical as well as regulatory conditions for their installation have just started to be defined. In this context, there exists in Argentina a legal and regulatory framework for the implementation of large photovoltaic plants but there is a lack of such legal framework for distributed generation (DG) by means of grid connected photovoltaic into the medium and low voltage distribution networks. This situation led research centers, together with private and provincial Energy Agencies to install pilot systems in order to identify and characterize their impact on the low voltage distribution network, taking into account the local grid capacity and characteristics of each province. In this paper the implications of different degrees of penetration of solar photovoltaic power generation evaluated using technical parameters of the network is presented. A set of examples of residential users connected to a distribution substation in the city of Corrientes is analyzed by means of a simulation using real grid data with the incorporation of GCPVS generation. The simulation results show that both the level of penetration of GCPVS systems as well as location where these distributed energy sources should couple to the distribution grid must be carefully assessed to maximize the benefits of the inclusion of distributed generation in urban environments.

This paper presents a methodology associated to a set of explicit equations aimed to translate point-to-point the generated power to standard test conditions and its application to a real situation. Such equations are employed for monitoring and diagnostic of grid connected photovoltaic systems. The proposed method is based in the data analysis through statistical methods and it allows diagnosis or detection of instant decreases of generated power. The Experimental results are compared with other procedure of characterization of the nominal power of large photovoltaic generators under real operation conditions which are based on protocols similar to the one proposed in this paper. Results show differences less to 3% between both methods. In conclusion, the methodology presented is useful for real time diagnose of power decrease, when variation of maximum power with temperature is not known or in cases where catalog parameters are not available.