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• Long-term operational monitoring of a Zero Emission Building (ZEB) in Beijing. • An existing building being retrofitted into a Zero Emission Building (ZEB). • Key Building Mounted Photovoltaic (BMPV) technologies are practically utilized and their effects are estimated. • The ZEB realized its own net-zero carbon emission and net energy production. • The ZEB could be a comprehensive experimental platform. Building mounted photovoltaic (BMPV) technology is a promised way to achieve carbon peak in building sector. Focused on the influence of heat from PV modules on building envelope's heat transfer and energy saving performance, and the power generation, the coupling mechanism of power generation and heat transfer of integrated photovoltaic technology on building façades has been investigated. The synergy of solar energy generation and building energy consumption have been studied in this paper. The installation method of building PV system was proposed, with which can achieve the maximum energy saving. Furthermore, the achievements have been applied in Zero Emission Building (ZEB) of China Academy of Building Research (CABR), demonstrating way to realize zero carbon building by integration of photovoltaic technology. Total of 236.1 kWp PV systems were installed in ZEB. Monitoring data shows that the annual power generation of ZEB could reach 212,382 kWh, and the power generation per building area is 73.79 kWh/m2, which could meet all the energy demands. In addition, it can supply extra power to surrounding buildings. The ZEB can provide experience and practice data supporting carbon peak in building sector. [ABSTRACT FROM AUTHOR]

• Spectrally resolved DNI was tested for an entire year in Beijing. • The spectra can be represented in five-dimensional data by an autoencoder. • Hierarchical clustering was adopted to obtain ten reference spectra in the case. • Novel local reference spectra can characterize solar resources throughout the year. • The superiority of the new reference spectra over ASTM AM1.5D was verified. The established reference spectrum (ASTM AM1.5) based on mid-latitudes is still the most frequently used standard in design and simulation in various fields worldwide, however, the solar spectrum varies with climate and time, which significantly affects the evaluations of solar energy utilization. This study proposes a novel reference spectrum analysis method to establish several local reference spectra, in this case, based on 147,374 spectra in Beijing, which can characterize solar resources throughout the year. The dataset consists of spectra of direct normal irradiance, and a deep learning autoencoder is adopted to extract the intrinsic features of each spectrum for clustering. 10 clusters are finally divided by agglomerative hierarchical clustering, and 10 local reference spectra were identified from each cluster by correlation analysis. The results show that the shape of new reference spectra shifts to the short wave as the irradiance increases, and the average photon energy increases from 1.069 eV to 1.456 eV. The new local reference spectra are compared with the standard spectrum AM1.5D to show the influence of shape variations, and it reveals 61% maximum differences among photovoltaic applications. The superiority verified new reference spectra could be further used to optimize local solar technologies design and guide photovoltaic material development. [ABSTRACT FROM AUTHOR]

Fine description for regional solar spectra has always been critical for improving solar energy utilization. However, it is difficult and complex to implement due to large amount and high-dimensional characteristics of the measured solar spectra. To address the above challenges, this study proposed a data-driven method to describe regional solar spectra using 211,877 global horizontal irradiance spectra in Beijing area as case data. Firstly, the dimensions of each measured spectrum were reduced from 2,221 to six using the deep autoencoder. Then, all dimensionality-reduced measured spectra were categorized into five clusters using the agglomerative hierarchical clustering. The clustering results exhibited notable variations across different months and dates. Finally, the local reference spectra were determined based on clustering results, and their effects on the performance of typical photovoltaic materials were analyzed. The maximum mismatch factor for typical photovoltaic materials under local reference spectra can reach up to 21 %. The comparisons with standard spectrum highlighted that the superior capacity of local reference spectra to describe the configuration of regional solar energy. This study provides a novel insight into the fine description for regional solar spectra, which sets a new direction for innovation in photovoltaic technology and promotes the sustainable utilization of renewable energy. [ABSTRACT FROM AUTHOR]

Fine description for regional solar spectra has always been critical for improving solar energy utilization. However, it is difficult and complex to implement due to large amount and high-dimensional characteristics of the measured solar spectra. To address the above challenges, this study proposed a data-driven method to describe regional solar spectra using 211,877 global horizontal irradiance spectra in Beijing area as case data. Firstly, the dimensions of each measured spectrum were reduced from 2,221 to six using the deep autoencoder. Then, all dimensionality-reduced measured spectra were categorized into five clusters using the agglomerative hierarchical clustering. The clustering results exhibited notable variations across different months and dates. Finally, the local reference spectra were determined based on clustering results, and their effects on the performance of typical photovoltaic materials were analyzed. The maximum mismatch factor for typical photovoltaic materials under local reference spectra can reach up to 21 %. The comparisons with standard spectrum highlighted that the superior capacity of local reference spectra to describe the configuration of regional solar energy. This study provides a novel insight into the fine description for regional solar spectra, which sets a new direction for innovation in photovoltaic technology and promotes the sustainable utilization of renewable energy. [ABSTRACT FROM AUTHOR]

Integrated energy system (IES) is characterized by high self-consumption ratio of on-site generated renewable energy, high efficiency of conventional energy utilization and possesses a significant flexibility in its operation. This overall, constitute to the foundation of low-carbon communities. Considering economic and environmental benefits, this paper proposes a two-layer co-optimization model with the upper layer optimizing the IES configuration and the lower layer optimizing IES operation. A community in Beijing is introduced as a case study to analyze the benefits of IES and compared with the conventional energy system. Multiple scenarios are researched, including (a) IES for low-carbon communities with PV roof area limitation, (b) IES for each of the four building types with PV roof area limitation, (c) IES for low-carbon communities without PV roof area limitation. The results indicate that the optimized IES for community can reduce the cost by 25% and CO 2 emissions by 32% per year by considering the limitation of roof area for the PV system. Without this constraint, the costs and emissions could be reduced by 20% and 62%, respectively. In addition, IES is more appropriate for office and commercial buildings since their load characteristics allow for load shifting and community-level IES costs and emissions are 8% and 10% lower than building-level due to the complementary of community load. This study provides suggestions for the IES planning and application in low-carbon community. [Display omitted] • An IES with multiple renewable energy and energy storage subsystems is proposed. • A two-layer co-optimization model of IES design and operation is developed. • IES optimization results for building-level and community-level are compared. • Impact of roof area limitation for PV on IES optimization results is investigated. [ABSTRACT FROM AUTHOR]