Optimization of Energy Use for Zero-Carbon Buildings Considering Intraday Source-Load Uncertainties

Building operational energy consumption accounts for a significant share of global energy consumption, and it is crucial to promote renewable energy self-sufficiency and operational optimization for zero-carbon buildings. However, scheduling strategies relying on day-ahead forecasts have limitations, and ignoring the ambiguity of short-term source-load forecasts is prone to the risk of scheduling failures. To address this issue, this study proposes an intraday optimization method for zero-carbon buildings under the source-load fuzzy space, which innovatively constructs a fuzzy chance constraint model of Photovoltaic (PV) output and load demand, enforces energy self-sufficiency as a constraint, and establishes a multi-objective optimization framework with thermal comfort as the main objective and power adjustment balance as the sub-objective, so as to quantify the decision risk through intraday energy optimization. Experiments show that the proposed method quantifies the decision-maker’s risk preference through fuzzy opportunity constraints, balances conservatism and aggressive strategies, and improves thermal comfort while safeguarding energy independence, providing a risk-controllable scheduling paradigm for the decarbonized operation of buildings.