Abstract
AbstractRenewable energy generation techniques have received a lot of attention and development in recent years. As a key source of renewable energy, distributed generation (DG) is effective. These contrasting assets are able to combine as a hybrid energy system with a micro-grid, delivering electric power with the option of cooling or heating. The biggest issue with this type of DG is islanding. When DG deliveries power to loads once severing from the grid, islanding occurs. For islanding detection of distributed generation, the Eradicate Liability Passive Islanding Detection (ELPID) methodologies of Point of Common Coupling (PCC), Rate of Change of Frequency (ROCOF), and Rate of Change of Frequency (ROCOF) are utilized in this study.KeywordsDistributed generation (DG)Eradicate liability passive islanding detection (ELPID)Micro-gridIslanding detectionNon-detection zoneThresholdArtificial neural networkDecision treeMultilayer perceptron neural network
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