Economic and environmental scheduling of smart homes with microgrid: DER operation and electrical tasks

Abstract

Microgrids are promising in reducing energy consumption and carbon emissions, compared with the current centralised energy generation systems. Smart homes are becoming popular for their lower energy cost and provision of comfort. Flexible energy-consuming household tasks can be scheduled co-ordinately among multiple smart homes to reduce economic cost and CO2. However, the electricity tariff is not always positively correlated with CO2 intensity. In this work, a mixed integer linear programming (MILP) model is proposed to schedule the energy consumption within smart homes using a microgrid system. The daily power consumption tasks are scheduled by coupling environmental and economic sustainability in a multi-objective optimisation with ε-constraint method. The two conflicting objectives are to minimise the daily energy cost and CO2 emissions. Distributed energy resources (DER) operation and electricity-consumption household tasks are scheduled based on electricity tariff, CO2 intensity and electricity task time window. The proposed model is implemented on a smart building of 30 homes under three different price schemes. Electricity tariff and CO2 intensity profiles of the UK are employed for the case study. The Pareto curves for cost and CO2 emissions present the trade-off between the two conflicting objectives.