Population mobility network and spatial accessibility based on peer-to-peer interactive energy management

Abstract

With the advancement of science and technology and the development of the world economy, the global demand for energy is increasing day by day. Therefore, it is necessary to reduce the utilization rate of fossil fuels. The key is to promote the rapid development of renewable energy and increase the proportion of new energy consumption. Therefore, accelerating the transformation and upgrading of the energy structure has become the top priority of future energy policies, and energy management has also become a hot topic in contemporary times. The high-speed and free population flow between cities has promoted the flow of production factors within the region, and a population flow network is slowly forming. The spatial accessibility index is used to evaluate the rationality of the spatial layout of urban facilities, and can also be used to test the service efficiency and the fairness of spatial distribution. This paper explores population mobility networks and spatial accessibility based on peer-to-peer interactive energy management. The purpose is to propose a good population flow network and spatial accessibility research method to explore the urban population flow characteristics and spatial characteristics with higher efficiency. This paper first introduces related methods for interactive energy management, population mobility networks, and spatial accessibility. A network analysis model of population flow is proposed, and the evaluation index and method of spatial accessibility are proposed. Finally, two experiments are done in this paper. First, we study the population mobility network in Beijing, Shanghai, Guangzhou, and Chongqing. The result is a correlation between the average distance of the network edges and the node degree value. The larger the degree value, the larger the average distance. The second experiment investigates the spatial accessibility of commercial facilities in Hangzhou. It is concluded that the difference between the maximum and minimum values of Hangzhou's total clustering degree is 86.3, and the standard deviation is 38.98. It proves that the global integration of Hangzhou is unbalanced and the degree of agglomeration is not high.