Journal of Shanghai Jiao Tong University ›› 2024, Vol. 58 ›› Issue (12): 1835-1845.doi: 10.16183/j.cnki.jsjtu.2023.217

• New Type Power System and the Integrated Energy •     Next Articles

Assessment Model for Interregional Electricity Price Difference and Cross-Regional Electricity Trading Volume Considering Carbon Cost

LI Wei, LI Ran(), HU Yan, WANG Xiwei, XIONG Kang   

  1. Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China
  • Received:2023-05-31 Revised:2023-08-22 Accepted:2023-08-31 Online:2024-12-28 Published:2025-01-06

Abstract:

In the context of achieving the “dual carbon” goal, the task of carbon emission reduction in the power industry urgently needs to be completed. Cross-regional electricity trading can facilitate the remote consumption of surplus renewable resources and contribute to the low-carbon transformation of the power system. Due to the inherent differences in power generation structures across interconnected regions, the impact of carbon costs on the clearing electricity prices within regions varies, leading to dynamic price differences between regions, which, in turn, affects the outcomes of cross-regional electricity trading, and further exacerbates the differences in power generation structures, thereby impacting interval electricity price differences. To address these complexities, this paper proposes an assessment model which considers both carbon costs and interval electricity price differences in evaluating cross-regional electricity trading volumes. The model aims to establish a coherent relationship between interval price differences and cross-regional electricity trading by incorporating carbon costs into the power system production process. It uses the dynamic interval price difference as a signal to determine the trading volume between regions in the evaluation of cross-regional electricity trading volumes. In assessing interval price differences, the model updates the intra-region power generation structure based on unit revenue rates, and contrasts the price differences before and after these structural iterations. Taking the cross-regional electricity trading between two interconnected areas as an example, the results of the computational simulations demonstrate that the proposed model effectively evaluates the dynamic price differences between regions and cross-regional electricity trading volumes. Additionally, it quantifies the impact of power generation structure evolution on interval price differences.

Key words: carbon cost, interregional electricity price difference, cross-regional electricity trading, power generation structure

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