The building sector accounts for 30% of final energy consumption and 28% global energy-related carbon dioxide emissions, with space heating cooling consuming a large share total buildings’ consumption. Building stock modelling prediction provides critical insights on the aid retrofit policy-making process evaluation energy-saving potential. By combining physical approach data-driven approach, h...

Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time dom...

In smart buildings, cooling load prediction is important and essential in the sense of energy efficiency especially in hot countries. Indeed, prediction is required in order to provide the occupant by his consumption and incite him to take right decisions that would potentially decrease his energy demand. In some existing models, prediction is based on a selected reference day. This selection d...

in this paper, we are going to improve the energy efficiency of an industrial c 3 mr base load lng plant by changing its refrigerant components and its mole fractions in liquefaction and subcooling cycles based on the cooling curves generated in the main liquefaction and subcooling heat exchangers. later on, selection features of the elements will be discussed. first, non-optimized c 3 mr plant...