A low complexity residential demand response strategy using binary particle swarm optimization

Demand management is mechanism to shift the demand of electricity from peak to off-peak to use the available energy as efficiently as possible without requiring additional generation capacity or transmission and distribution infrastructure. Demand response is a special type of demand management which motivates the customers to respond to electricity prices over time. The recently proposed demand response strategies aim at reducing the energy cost of the whole system by shifting energy consumption from peak to off-peak. These methodologies are complex and resource consuming as they try to reach a global optimum for a large group of residences. The paper proposes a simpler demand response strategy to minimize the energy cost in each residence independently using binary particle swarm optimization (BPSO) that schedules the electricity consumption of the shiftable loads in each residence. The paper also proposes a modification of the BPSO algorithm that assists the scheduling algorithm to converge quickly.