Abstract
This paper aims at using electric spring to reduce the monthly electricity bill by developing its optimal operational strategy to capitalize on the variable energy cost over a day. An hourly-sampled optimization algorithm is presented to devise an optimum daily strategy for electric spring as a tool to smartly manage energy among the loads, utility, and storage devices, provided that load and solar power forecasts are available. Uncertainty in forecasts is dealt with by embedding certain stochastic processes with the proposed optimization algorithm to identify an envelope of probable operational strategies. The development and deployment of the proposed optimization algorithm are presented on a realistic load profile of a typical net-zero energy house in South Australia. The obtained results are analyzed under different connection configurations. Consequently, a significant reduction in the monthly electricity bill is realized.
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