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.
1. Introduction
Due to fossil fuels depletion and global warming, energy cost and pollution reduction are two worldwide popular issues [1]. The UK Climate Change Programming, for example, aims to cut down 80% of carbon emissions by 2050 based on Climate Change Act 2008 [2]. In particular, in UK the energy sector is responsible of the highest amount of greenhouse gases to the atmosphere (i.e. 30%) [3]. At present, electrical supply systems are mainly based on relatively few large plants using conventional fossil fuels and operating in central locations. The power is then distributed to the final user via distribution and transmission networks. Centralised systems show overall energy losses of 65% or more, including losses during electricity generation, transmission and distribution [4].
6. Concluding remarks
An MILP model has been proposed to schedule the energy consumption of smart homes within a microgrid. Both environmental and economic minimisations are addressed in a multi-objective optimisation with e-constraint method. The model has been implemented on a case study of 30 smart homes with the same living habits under three price schemes. Twelve domestic electrical tasks are scheduled together with DER operation in the shared microgrid. Electricity tariff and CO2 emission intensity are assumed to be available for the optimal scheduling of the smart homes. Data profiles for a typical summer day in the UK are applied. Optimal results with trade-off between economic cost and environmental emissions are obtained.
