Cross-scale building energy-saving potential assessment through constructing a multi-level energy-saving scenarios (MLESS) Database

Revealing the energy-saving potential of urban existing buildings lies significant foundation for enhancing building energy efficiency and realizing low-carbon city transformation. Based on the previously developed Standard Database, this study newly constructs a multi-level energy-saving scenarios (MLESS) Database to assess building energy-saving potential of city block units. First, the influences of four primary impact factors on building energy consumption (BEC) are discussed through 99 simulation sets. Then the grey relational analysis (GRA) is applied to rank impact factors from four aspects, which informs the construction of the MLESS Database. Through the compared data of Standard Database and MLESS Database, a series of building energy consumption and the building energy-saving potential maps on block-scale across the whole Guangzhou city are obtained. Results show external wall types can reduce BEC by 6.615% to 25.874%, external window types can reduce BEC by 7.688% to 53.985%, air conditioning temperature can reduce BEC by 12.632% to 40.276%, air conditioning operating time can reduce by 9.151% to 47.980%. Through GRA, a total of 26 groups of energy-saving scenarios at multiple levels are designed. Spatial maps show that blocks of densely-built LCZs demonstrate significant building energy-saving potential. Specially, among all the LCZ types, the blocks of LCZ 1 presents the most significant energy-saving potential with a range of 4,431~26,726 MWh, followed by blocks of LCZ 4 and LCZ 5 ranging of approximately 100~2,500 MWh. Overall, the proposed MLESS Database is expected to be a practical tool for revealing building energy-saving potential of cross-scale urban regions.