Sustainable Optimal Capacity Allocation for Grid-Connected Microgrids Incorporating Carbon Capture and Storage Retrofitting in Multi-Market Contexts: A Case Study in Southern China
Yanbin Xu (),
Jiaxin Ma,
Yi Liao,
Shifang Kuang,
Shasha Luo and
Ming Zeng
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Yanbin Xu: China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China
Jiaxin Ma: Management Science Research Institute of Guangdong Power Grid Corporation, Guangzhou 510308, China
Yi Liao: China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China
Shifang Kuang: China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China
Shasha Luo: China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China
Ming Zeng: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Sustainability, 2025, vol. 17, issue 21, 1-34
Abstract:
With the goal of achieving carbon neutrality, promoting the clean and low-carbon transformation of energy assets, as exemplified by existing thermal power units, has emerged as a pivotal challenge in addressing climate change and achieving sustainable development. Arrangements and technologies such as the electricity–carbon–certificate multi-market, microgrids with direct green power connections, and carbon capture and storage (CCS) retrofitting provide favorable conditions for facing the aforementioned challenge. Based on an analysis of how liquid-storage CCS retrofitting affects the flexibility of thermal power units, this manuscript proposes a bi-level optimization model and solution method for capacity allocation for grid-connected microgrids, while considering CCS retrofits under multi-markets. This approach overcomes two key deficiencies in the existing research: first, neglecting the relationship between electricity–carbon coupling characteristics and unit flexibility and its potential impacts, and second, the significant deviation of scenarios constructed from real policy and market environments, which limits its ability to provide timely and relevant references. A case study in southern China demonstrates that first, multi-market implementation significantly boosts microgrids’ investment in and absolute consumption of renewable energy. However, its effect on reducing carbon emissions is limited, and renewable power curtailment may surge, potentially deviating from the original intent of carbon neutrality policies. In this case study, renewable energy installed capacity and consumption rose by 17.09% and 22.64%, respectively, while net carbon emissions decreased by only 3.32%, and curtailed power nearly doubled. Second, introducing liquid-storage CCS, which decouples the CO 2 absorption and desorption processes, into the capacity allocation significantly enhances microgrid flexibility, markedly reduces the risk of overcapacity in renewable energy units, and enhances investment efficiency. In this case study, following CCS retrofits, renewable energy unit installed capacity decreased by 24%, while consumption dropped by only 7.28%, utilization hours increased by 22%, and the curtailment declined by 78.05%. Third, although CCS retrofitting can significantly reduce microgrid carbon emissions, factors such as current carbon prices, technological efficiency, and economic characteristics hinder large-scale adoption. In this case study, under multi-markets, CCS retrofitting reduced net carbon emissions by 86.16%, but the annualized total cost rose by 3.68%. Finally, based on the aforementioned findings, this manuscript discusses implications for microgrid development decision making, CCS industrialization, and market mechanisms from the perspectives of research directions, policy formulation, and practical work.
Keywords: energy-sustainable development; carbon capture and storage (CCS); carbon capture power plant (CCPP); microgrid capacity allocation; electricity–carbon–certificate multi-markets; renewable energy consumption (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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