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低碳电力系统中的能源-水关联:基于模拟的非精确优化模型

Energy-water nexus in low-carbon electric power systems: A simulation-based inexact optimization model.

作者信息

Huang Jie, Tan Qian, Zhang Tianyuan, Wang Shuping

机构信息

Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.

Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, 510006, China.

出版信息

J Environ Manage. 2023 Jul 15;338:117744. doi: 10.1016/j.jenvman.2023.117744. Epub 2023 Mar 30.

Abstract

Energy and water resources are closely linked in electric power systems, and the application of low-carbon technologies further affects electricity generation and water consumption in those systems. The holistic optimization of electric power systems, including generation and decarbonization processes, is necessary. Few studies have considered the uncertainty associated with the application of low-carbon technologies in electric power systems optimization from an energy-water nexus perspective. To fill such a gap, this study developed a simulation-based low-carbon energy structure optimization model to address the uncertainty in power systems with low-carbon technologies and generate electricity generation plans. Specifically, LMDI, STIRPAT and grey model were integrated to simulate the carbon emissions from the electric power systems under different socio-economic development levels. Furthermore, a copula-based chance-constrained interval mixed-integer programming model was proposed to quantify the energy-water nexus as the joint violation risk and generate risk-based low-carbon generation schemes. The model was applied to support the management of electric power systems in the Pearl River Delta of China. Results indicate that, the optimized plans could mitigate CO emission by up to 37.93% over 15 years. Under all scenarios, more low-carbon power conversion facilities would be established. The application of carbon capture and storage would increase energy and water consumption by up to [0.24, 7.35] × 10 tce and [0.16, 1.12] × 10 m, respectively. The optimization of the energy structure based on energy-water joint violation risk could reduce the water utilization rate and the carbon emission rate by up to 0.38 m/10 kWh and 0.04 ton-CO/10 kWh, respectively.

摘要

能源和水资源在电力系统中紧密相连,低碳技术的应用进一步影响着这些系统中的发电和用水情况。对电力系统进行整体优化,包括发电和脱碳过程,是很有必要的。很少有研究从能源-水关联的角度考虑低碳技术在电力系统优化应用中的不确定性。为了填补这一空白,本研究开发了一个基于模拟的低碳能源结构优化模型,以解决采用低碳技术的电力系统中的不确定性问题,并制定发电计划。具体而言,将对数平均迪氏指数分解法(LMDI)、随机环境影响回归模型(STIRPAT)和灰色模型相结合,来模拟不同社会经济发展水平下电力系统的碳排放。此外,还提出了一种基于Copula的机会约束区间混合整数规划模型,将能源-水关联量化为联合违约风险,并生成基于风险的低碳发电方案。该模型被应用于支持中国珠江三角洲地区的电力系统管理。结果表明,优化后的计划在15年内可将二氧化碳排放量最多减少37.93%。在所有情景下,将建设更多的低碳电力转换设施。碳捕获与封存技术的应用将使能源消耗和用水量分别最多增加[0.24, 7.35]×10吨标准煤和[0.16, 1.12]×10立方米。基于能源-水联合违约风险的能源结构优化可使水资源利用率和碳排放率分别最多降低0.38立方米/10千瓦时和0.04吨二氧化碳/10千瓦时。

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