While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …

Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …

The power system worldwide is going through a revolutionary transformation due to the
integration with various distributed components, including advanced metering infrastructure …

The purpose of smart city is to enhance the optimal utilization of scarce resources and
improve the resident's quality of live. The smart cities employed Internet of Things (IoT) to …

In recent power grids, the need for having a two-way flow of information and electricity is
crucial. This provides the opportunity for suppliers and customers to better communicate with …

Electricity load forecasting has been a substantial problem in the electric power system
management process. An accurate forecasting model is essential to avoid imprecise …

Smart grids are able to forecast customers' consumption patterns, ie, their energy demand,
and consequently electricity can be transmitted after taking into account the expected …

In view of scarcity of traditional energy resources and environmental issues, renewable
energy resources (RERs) are introduced to fulfill the electricity requirement of growing world …

In this study, we present an empirical comparison of statistical models and machine learning
models for daily electricity price forecasting in the New Zealand electricity market. We …

Unexpected fluctuations associated with electricity load consumption patterns pose a
significant threat to the stability, efficiency, and sustainability of modernized energy systems …