This study investigates the benefits of introducing Li-ion batteries as energy storage unit in the commercial sector by considering a representative building with a photovoltaic system. Only the costs and revenues related to the installation and operation of the battery are considered in this study. The operational strategy of the battery consists in balancing the following processes through day-ahead forecasts for both electricity consumption and photovoltaic production: shaving a targeted peak, performing price arbitrage, and increasing photovoltaic self-consumption. By reviewing the electricity price cost for commercial buildings from several companies around the world, a general electricity price structure is defined. Afterwards, a Monte Carlo Analysis is applied for three locations with different solar irradiation levels to study the impact of climate, electricity price components, and other seven sensitive parameters on the economic viability of Li-ion batteries. The Monte Carlo Analysis shows that the most sensitive parameters for the net present value are the battery capacity, the battery price, and the component of the electricity price that relates to the peak power consumption. For Stockholm, one of the investigated locations, the corresponding Pearson correlation coefficients are −0.67, −0.66, and 0.19 for the case were no photovoltaic system is installed. For the considered battery operational strategies, the current investment and annual operation costs for the Li-ion battery always lead to negative net present values independently of the location. Battery prices lower than 250 US$/kWh start to manifest positive net present values when combining peak shaving, price arbitrage, and photovoltaic self-consumption. However, the integration of a photovoltaic system leads to a reduced economic viability of the battery by reducing the revenues generated by the battery while performing peak shaving.
|Titolo:||Li-ion batteries for peak shaving, price arbitrage, and photovoltaic self-consumption in commercial buildings: A Monte Carlo Analysis|
|Data di pubblicazione:||2021|
|Appare nelle tipologie:||1.1 Articolo in rivista|