Shifting Optimization Algorithm for Flattening the Electricity Consumption Peak of Residential Communities

Nowadays, consumers are more and more active in managing electricity consumption because of the progress of the IT & C technologies, sensors, modern appliances and incentives that can be achieved by means of demand-side management strategies. By implementing time-of-use tariffs that encourage the consumption at certain time intervals, the consumers are stimulated to shift or adjust their consumption to reduce the electricity bills and to reduce the consumption peak. Consuming from locally generated energy is also a way to reduce the electricity bill, increase the integration of renewable sources and reduce the stress on the public grid infrastructure avoiding long transmission of electricity from remotely located large power plants to the consumers. In this paper, we propose a shifting optimization algorithm that is implemented for a small community of ll modern houses with 8 generating photovoltaics and smart appliances that can be remotely controlled via tablets or mobile phones. The simulations are performed for a 24-hour dataset and for an entire year, to sustain the performance of the algorithm.