Green energy sources are implemented for the generation of power due to their substantial
advantages. Wind generation is the best among renewable options for power generation …

Biomethane production by anaerobic digestion has an important role in disposal of waste
and renewable energy recovery. By conducting the appropriate experimental analysis to …

Air pollution consists of harmful gases and fine Particulate Matter (PM2. 5) which affect the
quality of air. This has not only become the key issues in scientific research but also turned …

The main purpose of this paper is to develop an efficient machine learning model to estimate
the electric power load. The developed machine learning model can be used by electric …

To enhance the reliability and resilience of power systems and achieve reliable delivery of
power to end users, smart distribution networks (SDNs) play a vital role. The conventional …

Electrical load forecasting study is required in electric power systems for different
applications with respect to the specific time horizon, such as optimal operations, grid …

Electric load estimation is an important activity for electrical power system operators to
operate the system stably and optimally. This paper develops a machine learning model …

Despite advancements in smart grid (SG) technology, effective load forecasting utilizing big
data or large-scale datasets remains a complex task for energy management, planning, and …

针对短期负荷预测精细化的需求, 提出一种基于虚拟相似日与双阶段注意力机制的长短期时序
神经网络(DA-LSTPNet) 的地区级短期负荷预测方法. 为获得与负荷相匹配的细粒度实时气象 …

Electric power load forecasting is an essential task in the power system restructured
environment for successful trading of power in energy exchange and economic operation. In …