Time of Use Based Load Scheduling in Smart Homes Including both Storage Device and PHEV

Abstract

Demand response (DR) pricing strategies plays a major role in supplying and consuming
power economically. Although DR implementation is economical there are a lot of
challenges and difficulties faced by consumers in responding manually to the dynamic
pricing. A proposal is made on optimum load scheduling in a residential area to get bill
reduction by using the Automatic Load Commitment (ALC) algorithm. The decision
variables considered in the proposed ALC algorithm are the status of shiftable devices,
storage device and Plug-in Hybrid Electric Vehicles (PHEVs) charging as-well-as
discharging cycles. Due to the usage of battery storage and PHEVs the customers can avoid
using grid power during high pricing hours. Also, the customers can sell excess power to
the utility. This ALC algorithm is used to schedule the shiftable or controllable loads from
peak hours to a low peak hour period. So the objective of this work is to reschedule the time
of operation of household devices subjected to several practical constraints. Apart from
scheduling the appliances the proposed algorithm also concentrates on energy management
by using battery storage and PHEVs along with selling back of energy to the utility.
Moreover, to enhance the operation using ALC, the Time of Use (TOU) pricing strategy
using particle swarm optimization is adapted which varies as block rate