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Power generation expansion planning approach considering carbon emission constraints

2023-05-23

山东大学石访等：考虑碳排放约束的电源规划方法

摘要

电力部门碳排放量约占我国总碳排放量的40%，电力部门低碳转型是能源领域实现碳中和的重要环节。因此，综合考虑经济、环境（碳排放）以及技术等因素对演进路径的影响是未来电源规划的关键。本文提出了一种适用于低碳电源规划的混合整数线性优化模型。本模型以系统总运行成本最小为目标函数，将能源发展战略、灵活发电以及资源限制等因素视为约束条件，实现低碳电源规划目标。利用本文所提优化模型对中国电力低碳转型路径进行了分析并与现有电力低碳转型路径比较，进一步剖析现有规划方案的优缺点。研究结果表明，碳排放限制、电力备用系数、资源利用率、燃料消耗以及燃料价格都将深刻影响未来的电源投资决策。最后，结合模型优化结果，从传统电源灵活性改造、新能源参与电力市场机制以及新兴低碳技术综合应用三方面提出了政策建议。上述建议将为能源领域低碳转型并如期实现碳中和目标提供决策参考。

Power generation expansion planning approach considering carbon emission constraints

考虑碳排放约束的电源规划方法

Hasan Mehedi¹, Xiaobin Wang¹, Shilong Ye², Guiting Xue⁴, Islam Md Shariful³, Fang Shi¹

1.School of Electrical Engineering, Shandong University, Jinan 250061, P. R. China

2.College of Letter and Science, University of California Davis, California, USA, 95618

3.School of Economics, Shandong University, Jinan 250100, P. R. China

4.Haidian Electric Power Supply Company of State Grid Beijing Electric Power Company, Beijing 100000, P. R. China

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Power generation expansion planning approach

Abstract

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality. The power sector accounts for approximately 40% of China’s total CO2 emissions. Accordingly, collaborative optimization in power generation expansion planning (GEP) simultaneously considering economic, environmental, and technological concerns as carbon emissions is necessary. This paper proposes a collaborative mixed- integer linear programming optimization approach for GEP. This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies, flexible generation, and resource limitations constraints. This research further analyzes the advantages and disadvantages of current GEP techniques. Results show that the main determinants of new investment decisions are carbon emissions, reserve margins, resource availability, fuel consumption, and fuel price. The proposed optimization method is simulated and validated based on China’s power system data. Finally, this study provides policy recommendations on the flexible management of traditional power sources, the market-oriented mechanism of new energy sources, and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.

Keywords

Low-carbon; Optimization; Generation expansion planning; Long-term planning; Renewable energy.

Fig.1 Overall Optimization framework

Fig.2 Carbon emission for different policy scenarios

Fig.3 Installed capacity of different power plant technologies

Fig.4 Power generation capacity of different power plant technologies

Fig.5 Hourly electricity generation on a typical day from 2020 to 2060

Fig.6 Fossil fuel consumption over time horizon

Fig.7 Newly added renewable energy capacity in planning horizon

Fig.8 Total optimal system cost with predicted future demand

Fig.9 Installed capacity projection based on various modeling cases in 2035

Fig.10 Installed capacity projection between China HP RES and proposed model in 2050

本文引文信息

Mehedi H, Wang XB, Ye SL, et al (2023) Power generation expansion planning approach considering carbon emission constraints. Global Energy Interconnection, 6(2): 127-140

哈桑·迈赫迪，王晓彬，叶世龙等 (2023) 考虑碳排放约束的电源规划方法. 全球能源互联网（英文）, 6(2): 127-140、

Biographies

Hasan Mehedi

Hasan Mehedi received his B.E. degree in Electrical Electronics and Communication Engineering from Pabna University of Science and Technology, Bangladesh, in 2017. Currently, he is pursuing his M.E. degree in Electrical Engineering under the Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education in Shandong University, Jinan, China. His present research interest is power system planning, modeling, and integration of renewable energy in the distribution grid.

Xiaobin Wang

Xiaobin Wang received his B.E. degree in Electrical Engineering from University of Jinan, Jinan, China. He is currently working toward an M.E. degree in Electrical Engineering with the Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education in Shandong University, Jinan, China. His research interests include fault locations in distribution networks.

Shilong Ye

Shilong Ye majors in applied math, college of letter and science, University of California Davis, California, USA. His research interests include power system planning and operation.

Guiting Xue

Guiting Xue received his Ph.D. from Shanghai Jiao Tong University in 2014. He works as a senior engineer at the Haidian Branch of Beijing Electric Power Company, Beijing, China. His research interests include power system stability and control and PMU technology and its applications.

Islam Md Shariful

Islam Md Shariful received his M.A. in Economics from Shandong University, China in 2021. He is currently pursuing his Ph.D. in Economics at the School of Economics, Shandong University, Jinan, China. His present research areas are international trade, energy security, and renewable energy in Belt and Road Initiative (BRI) countries.

Fang Shi

Fang Shi received his B.E. degree in Electrical Engineering from the China University of Petroleum, Dongying, China in 2006; M.E. degree in Electrical Engineering from the State Grid Electric Power Research Institute, Nanjing, China in 2009; and Ph.D. from Shanghai Jiao Tong University, Shanghai, China in 2014. He is currently an Associate Professor in the Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education, Shandong University, Jinan, China. His research interests include power system stability and control and phasor measurement units (PMU) technology and its applications.

编辑：刘通明

审核：王伟

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