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Green growth has become an increasingly important paradigm for sustainable economic growth, resource development, and environmental protection. As the main focus in energy led green growth is a move away from fossil energy to clean energy, sustainable green growth resource development needs to measure both energy and environmental efficiencies. As the largest global energy consumer and carbon emitter, China has had to deal with serious energy and environmental issues in recent years, with its regional green growth performances being poorly assessed. Therefore, green growth clean energy-environmental efficiency assessments were examined in this paper, for which an integrated principal component analysis-data envelopment analysis based analysis approach was developed. It was found that while China's green growth has had a significant increasing trend in recent years, overall it was still at a low level, with the imbalances in China's regional economic development being reflected in its green growth. However, the excellent development and utilization of clean energy in most regions have significantly promoted a continuous improvement in China's green growth and the move toward sustainable resource development and utilization is contributing to long-term green growth. Green growth has also placed new demands on sustainable resource development in China. Therefore, underdeveloped regions that have sustainable resource endowments need to develop industrial systems that have clean energy as the main axis, and developed regions need to develop high-end industries that have low energy consumption and encourage mutual support systems between regions to ensure optimal sustainable resource, green growth development patterns. [ABSTRACT FROM AUTHOR]

As the largest energy consumption country, China now pays more and more attention to photovoltaic power generation because solar energy is the largest renewable and sustainable energy reserve in the world. In this case, the photovoltaic power generation plant project plays a crucial role in sustainable development, especially in the underdeveloped northwest region of China. This paper focuses on applying bi-level programing to the multimode resource-constrained project scheduling problem (MRCPSP) in photovoltaic power generation plant construction, which simultaneously considers the practical hierarchical organization structure and an uncertain decision-making environment. A bi-level fuzzy random multiple objective model is developed, wherein the government agency is in the upper decision level, while the contractor is in the lower decision level. Then, motivated by the particular mathematical nature of the proposed bi-level MRCPSP model, a hybrid intelligent algorithm is designed. Finally, a practical case from the Shenneng Futa Kashi-Tashi-Kuergan photovoltaic power generation plant project in a Chinese energy company is applied, and the results validate the practicability of the proposed model and solution algorithm for solving practical photovoltaic power plant project scheduling problems. [ABSTRACT FROM AUTHOR]