Exploring the Impact of Energy Interconnection on Renewable Energy, Electricity Load, and the Power Grid

Abstract This study aims to advance the integration of renewable energy, meet regional electricity demands, and promote the development of an interconnected grid system. Using China as a case study, the spatial and temporal variations in renewable energy generation and electricity consumption across the country are analyzed. Additionally, the role of energy interconnection in mitigating these variations is explored. Specifically, Inner Mongolia is examined as a case example to highlight the importance of a joint power supply system between two grids within the context of energy interconnection. Spatial and temporal discrepancies in renewable energy generation primarily arise from the contrasting seasonal patterns of wind power in Inner Mongolia and hydropower in the Yangtze River Basin. Wind power in Inner Mongolia follows a “winter peak, summer dip” pattern, whereas hydropower in the Yangtze River Basin follows an inverse pattern with a “summer peak, winter dip.” The complementarity between these two energy sources is significant. By leveraging energy interconnection technologies to facilitate the transmission of “winter wind power southward” and “summer hydropower northward,” the proportion of renewable energy consumed can be substantially increased. Longitudinal differences are mainly driven by variations in solar power generation time spans. For example, there is a 2 h time difference in solar power generation between Hami in Xinjiang and Tongliao in Inner Mongolia. Achieving a high degree of interconnection between these regions could generate a complementary effect, thereby extending the overall duration of solar power production across both locations. Discrepancies in electricity load are primarily influenced by factors such as regional economic development, climatic conditions, and the share of residential electricity consumption. For instance, in North, Central, and East China, if each region were to generate power independently, the maximum load would reach 68,218 MW. However, the implementation of regional interconnection reduces this maximum load to 64,249 MW. A fully interconnected system across these three regions further decreases the maximum load to 62,739 MW. Thus, broader interconnection of electricity loads results in a reduction in the maximum power demand for each region. In the context of energy interconnection, establishing a joint power supply system between the two grids in Inner Mongolia would effectively address the current fragmentation within the regional grid. This approach would also expand the market potential of both grids and significantly enhance the overall integration of renewable energy in Inner Mongolia.

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Publication Details

Journal
Journal of energy resources technology.
Published
2025-05-29
DOI
https://doi.org/10.1115/1.4068773
Primary Topic
Smart Grid Energy Management
Type
article
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article

Exploring the Impact of Energy Interconnection on Renewable Energy, Electricity Load, and the Power Grid

Wenbo Hu, Youhua Si, Haipeng Yu, Hongyang Liu et al.
Journal of energy resources technology.
Smart Grid Energy Management
article

Exploring the Impact of Energy Interconnection on Renewable Energy, Electricity Load, and the Power Grid

Wenbo Hu, Youhua Si, Haipeng Yu, Hongyang Liu, Yunfei Xu
article en

Abstract

Abstract This study aims to advance the integration of renewable energy, meet regional electricity demands, and promote the development of an interconnected grid system. Using China as a case study, the spatial and temporal variations in renewable energy generation and electricity consumption across the country are analyzed. Additionally, the role of energy interconnection in mitigating these variations is explored. Specifically, Inner Mongolia is examined as a case example to highlight the importance of a joint power supply system between two grids within the context of energy interconnection. Spatial and temporal discrepancies in renewable energy generation primarily arise from the contrasting seasonal patterns of wind power in Inner Mongolia and hydropower in the Yangtze River Basin. Wind power in Inner Mongolia follows a “winter peak, summer dip” pattern, whereas hydropower in the Yangtze River Basin follows an inverse pattern with a “summer peak, winter dip.” The complementarity between these two energy sources is significant. By leveraging energy interconnection technologies to facilitate the transmission of “winter wind power southward” and “summer hydropower northward,” the proportion of renewable energy consumed can be substantially increased. Longitudinal differences are mainly driven by variations in solar power generation time spans. For example, there is a 2 h time difference in solar power generation between Hami in Xinjiang and Tongliao in Inner Mongolia. Achieving a high degree of interconnection between these regions could generate a complementary effect, thereby extending the overall duration of solar power production across both locations. Discrepancies in electricity load are primarily influenced by factors such as regional economic development, climatic conditions, and the share of residential electricity consumption. For instance, in North, Central, and East China, if each region were to generate power independently, the maximum load would reach 68,218 MW. However, the implementation of regional interconnection reduces this maximum load to 64,249 MW. A fully interconnected system across these three regions further decreases the maximum load to 62,739 MW. Thus, broader interconnection of electricity loads results in a reduction in the maximum power demand for each region. In the context of energy interconnection, establishing a joint power supply system between the two grids in Inner Mongolia would effectively address the current fragmentation within the regional grid. This approach would also expand the market potential of both grids and significantly enhance the overall integration of renewable energy in Inner Mongolia.

Journal of energy resources technology.Vol. 1(5)
Openalex Percentile: Top 90%
Smart Grid Energy Management
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