Inter-Provincial Electricity Trading and Its Effects on Carbon Emissions from the Power Industry

Abstract

Electricity trading is an effective measure to minimize carbon emissions and alleviate the imbalance between reverse distribution of regional energy resources and power load. However, the effects of China’s electricity trading on carbon emissions have not been fully explored due to lack of complete and balanced inter-provincial power transmission data. Therefore, the electricity generation–consumption downscaling model, logarithmic mean Divisia index (LMDI) model, and random forest clustering algorithm within a general framework were used in the present study to explore the effect of electricity trading on level of carbon emissions. Comprehensive inter-provincial electricity transmission data were generated, driving factors including electricity imports and exports were decomposed at the national and provincial scales, and clustered provincial policy implications were evaluated. The results revealed that: (i) although economic activities were the main driving factor for increase in carbon emissions at the national level, 382.95 million tons carbon emissions were offset from 2005 to 2019 due to inter-provincial electricity importation, whereas electricity export increased carbon emission by 230.30 million tons; (ii) analysis at the provincial level showed that electricity exports from Sichuan and Yunnan provinces accounted for more than 20% of the nation’s total electricity flow. Notably, this high level of exports did not significantly increase carbon emissions in these provinces owing to the abundant hydropower resources; (iii) emission reductions were only observed at the national level if the carbon intensity of the exporting provinces was lower compared with that of importing provinces, or if the electricity trading was generated from renewable sources; (iv) the effect of electricity import on emissions reduction was markedly higher relative to the effect of electricity export in most provinces, which reflected the actual situation of sustaining optimization of electricity generation structure in provincial grids of China. These findings provide a basis for decision makers to understand the contributions of electricity trading to the changes in carbon emissions from electricity generation, as well as form a foundation to explore practicable carbon emission mitigation strategies in the power industry.

Balancing the Water-Carbon Trade-Off: Development of a Bi-Level Source-Grid-Load Synergistic Optimization Model for Multi-Regional Electric Power System

“…This study investigates three spatial scales of China's power grids: the National Grid (NG), Subnational Grids (SNGs), and Provincial Grids (PGs) [25]. Figure 1 shows the study area of China's electric power system, including seven State Grid Networks (SNGs): the North China Grid (NCG), the Northeast China Grid (NEG), the East China Grid (ECG), the Central China Grid (CCG), the Northwest China Grid (NWG), the Southwest China Grid (SWG), and the China Southern Power Grid (CSG).…”

“…Furthermore, 117 inter-provincial electricity transmission relationships are incorporated, based on previous research. On the load side, this study considers various electricity demand sectors, including agriculture, industry, construction, transportation, service, residents, and others [25]. The electricity demand sectors considered on the load side include agriculture, industry, construction, transportation, service, residents, and others.…”

“…While phasing out or upgrading outdated thermal power plants and expanding the use of renewable energy sources like wind and solar power can mitigate both carbon emissions and water usage, some technologies, such as dry cooling systems, may indirectly lead to higher carbon emissions despite saving water [23,24]. Additionally, regional disparities in economic development, technological capabilities, and resource availability result in uneven electricity generation and demand across different regions [25]. In China, the mismatch between the distribution of primary energy sources (e.g., coal, natural gas, and hydropower) and spatially diverse power consumption patterns poses a challenge.…”

Research on the Impact of Industrial enterprises Participation in the Peak shaving Auxiliary Service Market on Carbon Dioxide Emission

“…Enterprises join in the electricity trading is an effective measure to minimize carbon emissions [2]. Some scholars have studied the synergistic mechanism between the electricity market and the carbon market.…”