The rapid increase in urbanization has resulted in a significant rise in electricity
consumption, which resulted in a wide gap between the amount of electricity generated and …

Load forecasting models are of great importance in Electricity Markets and a wide range of
techniques have been developed according to the objective being pursued. The increase of …

Predicting electricity consumption is not an easy task depending on many factors that affect
energy consumption. Therefore, electricity utilities and governments are always searching …

This paper presents a method to predict the load current harmonics injected into micro grid
power systems using Nonlinear Auto Regressive neural networks with eXogenous input …

Prediction of heat demand using artificial neural networks has attracted enormous research
attention. Weather conditions, such as direct solar irradiance and wind speed, have been …

The rapid development of population, economy and technology currently has led to the fast
increase in electric consumption. Therefore, efficient energy management and load …

With the technological advancements and enhanced emphasis on harnessing renewable
power, electricity demand forecasting has become quite challenging from the aspect of …

This paper proposes a multi-step prediction method for the total harmonic distortion (THD) in
three-phase networks with nonlinear loads using a nonlinear autoregressive network with …

In the current scenario of the deregulated Indian electricity market where the power demand
and its availability vary remarkably, the factors playing a significant role in demand …

As aerosols in the air have a great influence on the health of residents of coal resource-
based cities, these municipalities are confronting the dilemma of air pollution that is caused …