Abstract
Residential buildings have become an active market participant in future power grid transactions due to the development of smart grid technologies, particularly smart meters. Keeping this in mind, this paper proposes a two-stage stochastic model including day-ahead and real-time local energy markets with the aim of domestic equipment scheduling, which reflects the uncertain mobility pattern of Electric Vehicle (EV) as well as the variability of micro wind turbine generation. The contribution of EV and battery in providing additional flexibility through bi-directional energy trading has been investigated considering deterministic and stochastic EV mobility patterns. Moreover, the smart home is modeled as a price-taker agent in the local market. Hence, different price-based Demand Response (DR) programs can affect its decisions. On this basis, a comprehensive analysis on the participation of a smart home in various price-based DR strategies is carried out with the aim of determining the most effective DR program from smart home owner point of view. The obtained results reveal that the participation of the smart home in Time-of-Use (ToU) pricing scheme not only reduces the operation cost, but also leads to smart home profitability.
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