Jing Li

As China confronts an unprecedented surge in decommissioned photovoltaic (PV) modules, establishing a robust and comprehensive recycling mode has become an urgent task. However, the existing literature lacks a systematic investigation into multi-stakeholder responsibility models for end-of-life PV management. To bridge this critical gap, firstly, this study conceptualized three multi-stakeholder PV recycling modes and developed an 11-parameter cost–benefit analysis model to dynamically evaluate their economic disparities under varying scenarios. Secondly, the framework is applied to a regional case involving 55 prefecture-level cities in the Shandong, Jiangsu, Anhui, and Zhejiang provinces in China. The results showed that the collaborative recycling mode involving retailers and third parties achieved optimal economic performance, incurring a lower cost (64.30 million CNY) than the alternative modes (70.41 and 80.25 million CNY, respectively). Cost structural analysis revealed that the collection, storage, transportation, and processing stages were the critical bottlenecks for cost control across all three modes. Scenario simulations further indicated a non-linear dynamic: while expanding the recovery scale enhanced profitability, excessive network optimization (beyond 20%) or prolonged storage durations yielded diminishing returns. Comprehensively, the maximum net benefit was achieved by synergizing scale expansion with moderate network optimization and a strict 30-day storage limit. Ultimately, these findings demonstrate the economic feasibility of multi-entity responsibility modes, providing a universal methodological framework for other regions and countries to construct efficient, low-cost PV recycling systems.

To address the limitations of single evaluation methods, complex risk factors, and subjective weight allocation in university mining lab safety management, this study proposes an improved EW-FCE model integrating entropy weighting and fuzzy comprehensive evaluation. A multi-level evaluation index system was developed, covering personnel status, hazardous objects, operating environment, and lab standardization (4 secondary and 24 tertiary indicators). By combining objective entropy weights with quantitative risk affiliation from fuzzy evaluation, the model overcomes traditional subjectivity. Applied to a key mining lab in Shanxi, it calculated indicator weights and overall risk values using survey data. Key risk factors identified include special equipment operation certification (weight 0.0909), heavy machinery maintenance records (0.0813), and radioactivity detector qualification (0.0761). The model enables scientific risk ranking and aligns closely with actual lab safety conditions, offering a practical tool for safety management and supporting AI-assisted decision-making in engineering universities.

Load forecasting plays a crucial role in power system planning and operational dispatch management. Accurate load prediction is essential for enhancing power system reliability and facilitating the local integration of renewable energy. This paper proposes a hybrid approach combining traditional time series models (ARIMA) with machine learning models (SVR). The particle swarm optimization (PSO) algorithm is improved by adjusting its elastic momentum, and the enhanced APSO algorithm is employed to optimize the adaptive weights of the hybrid model. Consequently, an elastic momentum-enhanced adaptive weighted load forecasting model (APSO-ARIMA-SVR) is developed. Numerical simulations using real-world datasets validate the model’s effectiveness. Results demonstrate that the proposed APSO-ARIMA-SVR model achieves optimal fitting performance, with prediction errors of 274.23 (MAE) and 321.50 (RMSE), representing the lowest errors among all comparative models.

【目的】针对光伏产业可持续发展面临的政策协同不足问题，本文从生命周期视角探索多重政策组合对光伏产业经济环境协同发展的作用机制，设计可推动光伏全产业链高质量发展的政策组合。【方法】基于全生命周期的经济收益与成本、环境影响和政策制定等多方面因素构建了光伏产业高质量发展系统动力学模型，模拟了技术进步、发电激励、碳交易、税收优惠、回收补贴等单一政策及组合政策下2011—2030年中国光伏产业-经济-环境协同发展趋势。【结果】①基准情景下，到2030年中国光伏装机容量将达到2374.19 GW，贡献28.26亿t碳减排，面临20.96 GW废弃物。②在单一政策情景下，各项政策均可在不同程度上提高光伏装机容量、废弃物回收规模、利润水平以及产能投资，推动碳减排。同时，随着政策实施力度的逐步增强，其促进效应也越显著。其中，技术进步政策实施成效最为突出。③组合政策效果比单一政策产生的效果更显著。在各类组合政策中，技术进步与税收优惠组合对推动光伏产业高质量发展展现出了最为突出的效果。【结论】组合政策可为光伏产业-经济-环境协同发展提供持续的动力支持。根据其在产业规模、减排、回收等方面的作用效果差异，应精准运用多样化政策工具。在光伏产业的全生命周期各阶段，均需持续推进技术进步政策的实施，通过创新工艺降低组件成本、延长寿命以及提升效率，驱动光伏产业全生命周期高质量发展。