A Building Integrated Energy System Scheduling Strategy Considering Wind and Photovoltaic Output Correlation Based on Improved Information Gap Decision Theory

The Building Integrated Energy System (BIES) is a useful approach to realise low-carbon buildings. In order to constrain the building carbon emissions and cope with the uncertainty of renewable energy and loads within the building, a scheduling strategy for the BIES in accordance with the improved Information Gap Decision Theory (IGDT) is proposed. Firstly, the wind and photovoltaic output correlation constraints are introduced on the energy supply side, and combined with the multi-type demand response of cooling, heating and electricity on the load side, the deterministic low-carbon dispatch model is designed to minimize both the daily operating costs for building users and the associated carbon emissions costs. Secondly, considering the uncertainty at both ends of the building source and load, the improved IGDT is used to describe the uncertainty variables, and the risk aversion model is constructed to explore the scheduling scheme under different risk attitudes of the BIES, which provides guidance for the dynamic operation of the system. Finally, the efficiency of the suggested strategy in terms of cost-saving, low carbon and flexibility is verified by the arithmetic simulation results.