During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …

The building energy (BE) management plays an essential role in urban sustainability and
smart cities. Recently, the novel data science and data-driven technologies have shown …

The rapid increase in human population and development in technology have sharply
raised power consumption in today's world. Since electricity is consumed simultaneously as …

In the integrated energy system with small samples, insufficient data limits the accuracy of
energy load forecasting and thereafter affects the system's economic operation and optimal …

Photovoltaic (PV) solar power generation is always associated with uncertainties due to
weather parameters intermittency. This poses difficulties in grid management as solar …

Accurate forecasting of the combined loads of electricity, heat, cooling and gas in the
integrated energy system is the key to improve the comprehensive efficiency and gain more …

The nonlinear regression estimation issues are solved by successful application of a novel
neural network technique termed as support vector machines (SVMs). Evaluation of …

Load forecasting is one of the main required studies for power system expansion planning
and operation. In order to capture the nonlinear and complex pattern in yearly peak load and …

The growing demand for energy in urban areas has led to the development of a variety of
methodologies for modelling energy in buildings at large scale. However, their accuracy has …

Modern cities dynamically face several challenges including digitalization, sustainability,
resilience and economic development. Urban planners and designers must develop urban …