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The structure of renewable energy (RE) development varies substantially across China's provinces, and the spatio-temporal pattern evolution is too pronounced to allow direct comparisons. Therefore, a reasonable method for RE efficiency estimation is important. Markov and spatial Markov chains can be used to analyze the evolution of the temporal and spatial patterns of provincial RE. Simultaneously, data envelopment analysis game cross-efficiency evaluation can quantify the RE generation efficiency of each province from the perspective of competition. Nine factors were selected to identify the key influencing factors the RE generation efficiency. From the perspective of spatio-temporal heterogeneity, a geographically and temporally weighted regression model was combined for spatial modeling. Results show a significant change in the categories of wind and solar power installations, a medium change in biomass installations, and a small change in hydropower installations. Two-thirds of the provincial RE generation efficiency increased from 2015 to 2020. There is spatio-temporal heterogeneity regarding the impact of various factors on the RE generation efficiency: The impact of technology market transactions exhibits the greatest inter-provincial variation and the impact of electricity industry investment exhibits the smallest inter-provincial variation. [ABSTRACT FROM AUTHOR]

• Establishing HWPS investment limitation and suitability assessment indicator systems. • Determination of expert weights using dynamic social networks. • TIFN was used to quantify the qualitative indicators. • Combining BWM and CRITIC combination weighting and TODIM to rank the alternatives. • Investment suitability assessment of 62 completed hydropower plants in China. The hydropower-wind-photovoltaic-storage (HWPS) complementary system is one of the essential ways for China to build a new type of power system and to realize the dual-carbon goal. However, China's HWPS complementary system is still in the exploratory stage, and it is important to propose a rational multi-attribute decision-making (MADM) framework for investment suitability assessment based on completed hydropower plants. Therefore, this study first established a limitation indicator system for preliminary screening hydropower plants and an HWPS investment suitability assessment indicator system containing six dimensions: nature, market, infrastructure, land, society, and environment. Second, the weights among experts were determined based on the dynamic social network, and a mechanism for updating expert weights was proposed. Again, triangular intuitionistic fuzzy number (TIFN) was used to quantify the qualitative indicators and combined the weights according to the best-worst method (BWM) and criteria importance through intercriteria correlation (CRITIC) methods. Finally, the TODIM (an acronym in Portuguese for interactive and MADM) method was used for scheme suitability assessment with sensitivity analysis and method comparison. The results show that 62 eligible hydropower plants were preliminarily screened out of 647 completed medium- and large-scale hydropower plants in China by combining GIS technology. Natural factors are the most important of the six dimensions, followed by social factors. According to the suitability assessment results of TODIM, #23 hydropower station has the highest suitability for HWPSCS investment, which provides a reference for the layout of China's HWPS complementary system. With different decision makers' risk preferences and different MADM methods, #23 hydropower plant is still the best investment option, which proves the effectiveness of the MADM framework proposed in this study. [ABSTRACT FROM AUTHOR]