Developing Energy Control and Optimisation methodology for Built Environment of the future

A built environment is formed by the buildings and other structures constructed by humans including water and drainage systems, power systems, communication systems and transportation systems; whereas building itself account for 30% - 40% of total global energy consumption. This implies that controlling and optimising the amount of energy consumed or utilised in buildings is the first step in realising an energy efficient built environment. This will not only save cost by minimising the level of re-enforcement on the supply system or reduction in the bills incurred by the occupant, but ultimately reduces the amount of CO2 emission. Generally, energy efficiency strategies in buildings can be broadly classified into passive and active measures. Passive energy efficiency strategies rely on materials or system that consumes less energy to perform their function such as the use highly efficient thermal insulations, building retrofitting, glazing, passive heating and cooling; and among others. Active energy efficiency seeks to use and optimise energy more intelligently, to achieve the same results; they rely on sensors that gather data on occupants such as behaviour and activities, big data analytics, predictive algorithms, internet of things, wireless sensor networks, and among others. This paper explored these methods and proposed a hybrid of both passive and active energy efficiency strategies; together with occupant’s awareness and feedback in optimising energy usage in buildings while ensuring flexibility and level of comfort on the part of the occupants.