SYSTEMS AND METHODS FOR REAL-TIME FORECASTING AND PREDICTING OF ELECTRICAL PEAKS AND MANAGING THE ENERGY, HEALTH, RELIABILITY, AND PERFORMANCE OF ELECTRICAL POWER SYSTEMS BASED ON AN ARTIFICIAL ADAPTIVE NEURAL NETWORK

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United States of America Patent

SERIAL NO

12267346

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Abstract

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A system for utilizing a neural network to make real-time predictions about the health, reliability, and performance of a monitored system are disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, an adaptive prediction engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The adaptive prediction engine can be configured to forecast an aspect of the monitored system using a neural network algorithm. The adaptive prediction engine is further configured to process the real-time data output and automatically optimize the neural network algorithm by minimizing a measure of error between the real-time data output and an estimated data output predicted by the neural network algorithm.

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Patent Owner(s)

Patent OwnerAddress
POWER ANALYTICS CORPORATION9208 FALLS OF THE NEUSE ROAD SUITE 215 RALEIGH NC 27615

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Nasle, Adib Poway, US 43 2746
Nasle, Ali San Diego, US 18 610

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