Artificial Intelligence for Automatic Load Management

Abstract

Demand-side management (DSM) means the load or consumer side management of electric energy for the optimum efficiency of the power system. DSM helps the electric utility by satisfying the requirements of a larger number of consumers with the existing generation capability and it also decreases the requirement for new generation capacity. Demand side management programs can be of great use to the electrical utilities as they eradicate the need to develop new transmission and distribution structures and power plants and it also motivates the consumer to use less energy during the time when demand is maximum. There are many DSM techniques, but load shifting proves to be the best fit to meet the above-mentioned criteria. The existing demand-side strategies need a human operator to carry out the load management process through certain DSM algorithms. This paper presents a model for automatic load management with the help of artificial intelligence to reduce human efforts and eradicate human error. The proposed model with the help of artificial neural networks (ANN) can predict the hourly power consumption of the load shifted curve of the next week with the help of recorded exponential moving averages. The proposed model can benefit the electric utility by automizing the load management process, reducing human involvement, and mitigating human error.