An optimized demand response strategy for electric water heaters and the associated impact on power system operational reliability

Aggregated Electric Water Heaters (EWHs) are ideal candidates for demand response (DR) resources considering that EWHs account for a huge percentage of energy consumption among all the home appliances and their heat storage capability. Power system reliability could be affected by the power consumption pattern of massive households. In this paper, a Binary Particle Swarm Optimization (BPSO) algorithm using Time-Of-Use (TOU) electricity rate as DR incentive is utilized to perform the power usage optimization of EWHs, considering the customers' electricity cost and the hot water demand. In this way, EWHs would be able to react to the optimal operation signal without affecting customers' comfort and convenience. Furthermore, aggregating thousands of EWHs may have positive influences on power system reliability considering their operating reserve capacity as interruptible loads. A Reliability T est System is modified to test the capacity of aggregated EWHs in this paper. The Unit Commitment Risk (UCR) reduction is used to indicate the influence of aggregated EWHs on power system reliability.