Ji Ling, Jia Xiaoping, Chiu Anthony S F, Xu Ming
School of Economics and Management, Beijing University of Technology, Beijing, China.
School of Environment and Safety Engineering, Qingdao University of Science & Technology, Qingdao, China.
PLoS One. 2016 Aug 9;11(8):e0160869. doi: 10.1371/journal.pone.0160869. eCollection 2016.
Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions.
各国之间的电力贸易日益频繁,了解全球电网结构有助于确定对电网可靠性至关重要的国家。本研究将全球电网视为一个以国家为节点、国际电力贸易为链路的网络。我们分析了全球电力贸易网络的结构,发现该网络由四个子网络组成,并对最大的网络——欧亚网络进行了详细分析。俄罗斯、中国、乌克兰和阿塞拜疆在欧亚子网络中的中间中心性较高,表明它们所处位置的中心程度。分析表明,基于网络结构,欧亚子网络由七个社区组成。我们发现这些社区与地理邻近性并不完全一致,并且欧亚子网络目前的国际电力贸易导致额外产生约1100万吨二氧化碳排放。