Abstract
As is known, a reduction in CO 2" role="presentation" style="max-height: none; display: inline; line-height: normal; text-align: left; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border-width: 0px; border-style: initial; position: relative;">2 emissions is closely related to the improvement of energy efficiency and the increasing use of renewable energy sources in building stock due to its high contribution to worldwide energy consumption. The retail sector has become particularly interesting in this sense, because commercial buildings are no longer just places where a variety of services are offered to customers. In fact, they can be beacons of energy efficiency. In this paper, we propose a predictive energy control strategy that, through the combination of production and demand forecasting, can effectively shave and shift the peak consumption of shopping malls equipped with battery energy storage systems (BESS). The adopted optimization strategy takes into account the variability of electricity tariffs over time, as is customary in some European countries. The performed energy and economic simulations based on the experimental data collected in an Italian shopping mall clearly highlight the benefits in terms of energy and economic savings. Moreover, the reported results lead to the conclusion that BESS management, photovoltaic (PV) generation, and peak switch strategies can have a reasonable pay-back investment time even for buildings with a large energy demand