This paper takes the industrial innovation ecosystem as the research object and the realization of green development as the goal, discussing the temporal and spatial evolution of coupling coordination degree of industrial innovation ecosystem from the perspective of system view. Based on the data of 30 provinces in China from 2010 to 2021, the spatial and temporal pattern distribution and spatial connection evolution of synergy among the three subsystems of industrial innovation ecosystem are studied by using coupling coordination degree model, trend surface model and gravity model. It is found that during the study period, the coupling relationship between the three subsystems is in a dynamic upward state. The regions with high values and rapid growth are distributed in the key areas of the national economic development strategy. At the same time, they have the characteristics of “positive U-shaped first and then inverted U-shaped” in the east-west and north-south directions; the spatial connection strength of coupling coordination degree shows that the spatial connection strength of the eastern region is significantly greater than that of the western region. With the improvement of spatial connection strength, a radial coupling network centered on Beijing Tianjin Tangshan region and the Yangtze River Delta is formed, which is of core significance to promote the coordinated development of industrial innovation ecosystem.
In this paper, we provide theoretical and policy support for quota-allocation strategies based on a national unified renewable energy (RE) power market. Renewable portfolio standards (RPSs) are of great significance in promoting the stable development of renewable energy and improving power market decision making in China’s power industry. To resolve the geographical, resource allocation, and power-grid problems of multi-regional RE power generation, we constructed a regional distribution optimization model with the lowest cost under the RPS policy and designed a set of dynamic distribution mechanisms based on the renewable energy power quota index. The results show that it is necessary to prioritize development of wind-generated power on the North China and Northeast Power Grids, solar energy on the Northwest Power Grid, and biomass energy generation on grids in other regions to plan specific task undertakings and allocate RE power generation to each grid. We propose a multi-regional power distribution model at the lowest cost under the RPS policy to provide solutions and references for renewable energy power market quota allocation.
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