Estimating the impacts of a new power system on electricity prices under dual carbon targets

被引:11
|
作者
Li, Ru [1 ]
Hu, Yujie [1 ]
Wang, Xiangyu [1 ]
Zhang, Boyan [2 ]
Chen, Hao [2 ]
机构
[1] Chengdu Univ Technol, Sch Business, Chengdu 610059, Peoples R China
[2] Renmin Univ China, Dual Carbon Res Inst, Beijing 100872, Peoples R China
基金
中国国家自然科学基金;
关键词
Electricity price; New power system; Carbon peaking; Carbon neutrality; Ancillary service; CHINA; GENERATION; EMISSIONS; MODEL;
D O I
10.1016/j.jclepro.2024.140583
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The construction of a new power system dominated by renewables is crucial for achieving China's goals of carbon emission peaking and carbon neutrality. While numerous studies have investigated grid parity for largescale renewables, some have overlooked the fact that the integration of variable renewable energy requires coordination with regulating resources. This coordination introduces additional costs, leading to subsequent increases in electricity prices. Our study comprehensively considers the total system costs and proposes a dynamic recursive linear optimization model. This model aims to simulate both short-term and long-term impacts of constructing a new power system on electricity prices in China. It evaluates the short-term effects of the Russia-Ukraine conflict and the COVID-19 pandemic on energy prices and demand, as well as the long-term effects of renewable energy penetration on ancillary service costs and technological progress on system costs. The results show that China's electricity price is projected to rise by 10.2% in 2030 for carbon peaking. By 2060, with an 83.3% renewable energy penetration for carbon neutrality, the electricity price will reach 0.859 CNY/ kWh, representing a 27.2% increase. Ancillary service costs will experience the highest growth rate, accounting for 15.5% of system costs by 2060. Our study also proposes optimal technological pathways for the new power system and provides valuable data to support the development of effective electricity price mechanisms.
引用
收藏
页数:13
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