English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Currently the state electricity enterprise, known as PLN, monitors the active power of customers by recording meters every month and is still prone to electricity theft because of location of the electricity measuring devices placed in each customer’s home. In this paper, we propose an electric theft detection device with an ARM microcontroller, placed centrally on the side of distribution transformer panel to measure active power in each customer and total active power in distribution transformer. The total active power of all customers is used to predict total active power in distribution transformer by the neural network method. By comparing the active power measured in distribution transformer with prediction of the active power from the neural network method and comparing the total active power of all customers with the total active power in the distribution transformer, devices that have been made are capable of detecting electrical theft if there is percentage of error between predicted value of active power on IED Master and active power measured on IED Master above 1 percent, and also the percentage of errors between the total active power from 2 pieces of IED Slave and active power measured in IED Masters above 1 percent.

Consumer power prediction based on neural network for electricity theft detection