Optimal configuration and scheduling strategy of BIPV public building in V2B scenario

Abstract:

The integration of mobile energy storage capabilities of electric vehicles (EVs) into building energy system scheduling has gradually become a significant measure for advancing the green and low-carbon development of the construction sector, which can effectively enhance the energy efficiency of buildings while reducing operational costs. For large-scale building integrated photovoltaic (BIPV) public buildings, a two-level optimization configuration and scheduling method for BIPV building energy systems, considering EV integration, is proposed. First, a Gaussian mixture distribution model is used to fit the daily travel behavior of EVs, establishing an EV travel pattern model based on public buildings. Next, to simultaneously determine the configuration and scheduling results of the system, a two-level optimization model is established: the upper level aims to minimize the annual planning cost of the system to obtain configuration results, while the lower level aims to minimize the daily operational cost of the system to obtain power load scheduling results. Finally, a solution method for the two-level optimization model is provided, and a case study is conducted using typical daily weather load data from the heating season of an office building on a university campus. The results indicate that configuring and scheduling the building energy system according to the solution results can effectively improve photovoltaic utilization and extend the service life of energy storage equipment. Furthermore, by comparing different energy storage schemes in the system, it is found that utilizing only EV energy storage is more advantageous in both long-term and short-term economics, and achieve good system operational performance.