Non-technical losses (NTL) in electric power grids arise through electricity theft, broken electric meters or billing errors. They can harm the power supplier as well as the whole economy of a country through losses of up to 40% of the total power distribution. For NTL detection, researchers use artificial intelligence to analyse data. This work is about improving the extraction of more meaningful features from a data set. With these features, the prediction quality will increase.

Electricity Theft Detection using Machine Learning

Identifying electricity theft using machine learning

This work presents the design and construction of a smart energy theft detector on distribution lines. The escalating challenge of power theft within distribution lines necessitates innovative solutions to safeguard the integrity of power distribution networks. Atmega328-P, Arduino-uno Micro-processor was interphase with Bluetooth module to detect energy theft. Proteus professional software was deployed to determine the functionality of the smart energy theft detector. The work was tested and the result obtained showed a stand-alone system capable of detecting energy theft on different phases of the distribution network. The information sent to the utility operator’s liquid crystal display (LCD) indicates theft detected on either red, blue or yellow phase. 

Design and Construction of a Smart Energy Theft Detector on Distribution Lines

Electricity theft is a significant occurrence that is happening about all nations from one side of the planet to the other. This adversely affects the nation's economy. Theft identification in the power sector is a difficult task for power distribution organizations overall, since this power theft prompts to monetary losses just as loss of electric energy. There are numerous ways by which power is stolen like controlling energy meters or tapping cables at the consumer's end, and so on. Since this robbery is going on in enormous amount, manual examination of such burglary is a hectic task. So, automatic detection of power theft is a vital need of the hour. This paper presents an electricity theft detection model using smart grid meter data dependent on Extreme Gradient Boosting (XGBoost) and OCR. Feature Selection is made used of in the model in order to pick the most relevant features from the dataset to that of our electricity theft detection model. XGBoost is remarkable as it utilizes a more regularized model formalization to have command over-fitting which results in better execution significantly quicker. OCR is employed in order to know what object led to electricity theft detection.

/pdf/an-efficient-electricity-theft-detection-using-xg-boost-2nbe4h1k.pdf

An efficient electricity theft detection using xg boost

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Disha Mhaske

Author Tools

Chat about Author

Papers

An efficient electricity theft detection using xg boost