Zero-carbon community (ZCC) is essential in addressing critical social and environmental challenges, particularly in reducing energy consumption, lowering carbon emissions, and decreasing reliance on fossil fuels. However, several issues are still unclear, including inconsistent definitions of ZCC, the lack of detailed policy analyses, and limited exploration of implementation challenges and solutions persist. This study addresses these gaps by conducting a comprehensive analysis of the drivers and barriers to ZCC development in China. It begins with a detailed review of the definitions of ZCC, comparing and contrasting them from both domestic and international perspectives. Then, it evaluates existing incentives, categorizes them into policy documents, laws, and standards while assessing their evolution and real-world applications. This study also presents case studies of exemplary ZCC, including the Beddington Community in the UK and the Zero Carbon Pavilion at the Shanghai World Expo Park in China. These cases offer insights into practical approaches, societal impacts, and advanced practices, proposing a ZCC construction model tailored to China’s unique economic and policy environment. Furthermore, the study identifies key barriers to adopting ZCC in China and proposes targeted recommendations across five domains: administrative, economic, technological, socio-cultural, and environmental. A “macro-meso-micro” implementation pathway is developed, emphasizing stakeholder collaboration as a core element for successful execution. This study systematically reviews and critically analyzes current policies and practices related to ZCC, and offering valuable theoretical guidance for developing regulations and standards, along with practical solutions to address current implementation challenges.@en

The distribution network (DN) reconfiguration is a well-known optimal power flow (OPF) problem. However, with the transition of DN from 'passive' to 'active', new technical challenges arise in DN reconfiguration. This article addresses two key issues in this regard. Firstly, the integration of local renewable generation (LRG) introduces uncertainty into the system-wide power flow of the DN. Secondly, the coupling between DN and the external power grid (EPG) affects the determination of DN root voltage. Consequently, a novel DN reconfiguration approach is proposed in this article. To begin with, an explicit mixed-integer convex OPF model is constructed that incorporates both the EPG and DN sides. Notably, the OPF model embeds the function of local droop control that is provided by LRG. Subsequently, the original OPF model is decomposed, and the distributed optimization methods based on the augmented Lagrangian relaxation are employed. The article comprehensively discusses parallel processing and asynchronous implementation as parts of the distributed optimization procedure. Furthermore, to address the uncertainty related to LRG integration, the extreme scenario method is used to provide a robust decision regarding DN reconfiguration. The application of the extreme scenario method in the distributed OPF model concerning DN reconfiguration is successively developed. Finally, numerical results are presented to demonstrate the acceptable performance of the distributed optimization methods, in terms of optimality and convergence. Also, these are validated that the proposed DN reconfiguration approach exhibits robustness to LRG integration, the system-wide voltage profile is improved, and the active power loss is effectively reduced using the proposed DN reconfiguration approach.

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