An efficient scheme for residential load scheduling integrated with demand side programs and small-scale distributed renewable energy generation and storage
John Wiley and Sons Ltd
School of Engineering
This paper proposes an efficient scheme for residential load scheduling integrated with a demand response program. It is a comprehensive solution, which is capable of automatically managing and controlling small-scale renewable energy generation facilities and energy storage system including batteries and plug-in vehicles, and household smart appliances in flexible cooperation with advanced metering infrastructure to deliver time-based price messages from utilities to the end users. Therefore, the multi-variable single-objective optimisation scheme by genetic algorithm is proposed to reshape the end-user's consumption profile according to the available generation, grid requests, and consumer's preferences, while simultaneously helping to compensate for the volatility of output power in renewable energy sources alongside a local energy storage system. The approach aims to minimise the overall daily electricity cost of household appliances and keep the power consumption below a demand limit. The obtained simulation results are presented to demonstrate the effectiveness and applicability of the proposed residential load scheduling algorithm, which has proven to be effective in optimising the consumer comfort level by maximising the operation of the household appliances within the preferred comfort level mode and minimising their operation in the allowable comfort level mode. The results also show that when the energy storage system includes a plug-in electric vehicle as storage, the level of violation is reduced close to the original settings compared with when the electric vehicle battery is not used as energy storage. © 2018 John Wiley & Sons, Ltd.