An approach to implement electricity metering in real-time using artificial neural networks

Abstract

As many utilities move toward deregulation, the research focus on spot pricing of electricity has led to the development of complex spot pricing-based electricity rate models. As research matures to implementation stages, approaches to meter the actual power consumption in real time are required. In this work, we model a real-time electric power metering approach based on neural networks. A carefully designed artificial neural network (ANN) is trained to recognize the complex optimal operating point of an all-thermal electricity generating utility. A real-time rate is allocated to each bus for a given power system's loading pattern and the recall process is instantaneous. The proposed approach is tested using a spot pricing model on five-and 14-bus electric power systems. Different loading levels are used for each bus.

A Simple Method for Power System Harmonic Analysis

“…The neutral network technique is also superior to the FFT when it is used for suppressing the electric energy fluctuation. Likely its computational complexity is much higher, ASIC implementation is costly as well [7], [8].…”