重庆理工大学学报2025，Vol.39Issue(5)：195-205,11.DOI:10.3969/j.issn.1674-8425(z).2025.03.025
计及绿证-碳交易的综合能源系统鲁棒经济优化调度
Robust economic optimization scheduling of integrated energy systems considering green certificates and carbon trading
摘要
Abstract
Along with the global green energy transformation and the implementation of"dual carbon"strategy,integrated energy systems(IES)emerge as a crucial pathway to achieve a low-carbon economy.Governments worldwide set carbon emission targets and enforce green low-carbon policies while promoting large-scale integration of renewable energy.They optimize energy system scheduling to reduce carbon emissions,ensure system stability,and maintain economic efficiency.Significant challenges still exist as current methods struggle with limitations in mechanism design and uncertainties,making it hard to address the complex and dynamic changes in energy systems.Designing an optimization scheduling strategy that balances low-carbon performance,economic efficiency and robustness becomes imperative. Focus has been primarily on the individual functions of carbon trading mechanisms or green certificate trading,often ignoring the synergistic benefits that arise when both mechanisms operate in tandem.Carbon trading reduces carbon emissions by assigning a price to carbon dioxide and incentivizes the development of low-carbon technologies.Green certificate trading motivates renewable energy consumption by offering economic rewards.Although each mechanism has made significant achievements in its own domain,researchers recognize that their independent application fails to fully unlock potential benefits.Collaborative operation between carbon trading and green certificate trading may enhance renewable energy uptake while achieving more effective carbon reduction.Therefore,designing a trading mechanism that integrates the strengths of both approaches represents a key challenge for future energy system optimization.Traditional optimization scheduling models reveal notable drawbacks when confronting uncertainties,such as the volatility of renewable energy outputs and market price fluctuations.Stochastic programming methods depend on precise probability distributions,yet insufficient data and inherent uncertainties often prevent researchers from obtaining reliable distributions.Classic robust optimization models adopt worst-case scenarios to manage uncertainties.This approach guarantees system safety but frequently sacrifices economic efficiency because of its overly conservative nature.Maintaining system safety and reliability while optimizing economic performance in a fluctuating market remains a pressing challenge. Multi-energy coupling devices,such as power-to-gas(P2G)systems and energy storage units,possess huge potentials for flexible adjustment.These devices serve as bridges among various energy forms,actively regulating and optimizing system operations to improve flexibility and stability.Research rarely explores how these devices collaborate with carbon trading and green certificate trading mechanisms or how scheduling optimizations span different time scales.The lack of dynamic response mechanisms and multi-energy collaborative scheduling models complicates efforts to balance economic performance,low-carbon objectives and robustness. To overcome these challenges,we propose a robust economic optimization scheduling strategy for integrated energy systems that incorporates thermal power's flexible response capabilities along with a stepwise green certificate-carbon trading mechanism.The strategy enhances system flexibility against uncertainties by designing dynamic response capabilities for combined heat and power(CHP)units and integrating hydrogen energy utilization equipment.This approach actively improves scheduling flexibility and reduces the impact of renewable energy fluctuations on system stability. The strategy begins with modifications to traditional CHP units by integrating Kalina cycle technology,which delivers flexible response performance.It further exploits the complementary characteristics of hydrogen energy through multi-energy integration.This solution directly addresses the inherent volatility of renewable energy sources,such as wind and solar power.Then,a fuzzy set model is introduced based on a non-precise Dirichlet framework to represent uncertainties in wind and solar outputs.A distributionally robust optimization model builds preset spinning reserves that quickly counter forecast errors within an acceptable operating range.When forecast errors exceed this range,the system curbs wind and solar inputs or sheds load,with economic losses serving as the risk metric. To reap low-carbon economic benefits,we analyze both carbon trading and green certificate trading mechanisms and propose a stepwise green certificate-carbon fusion mechanism.It well balances low-carbon economic outcomes while promoting a transition toward a low-carbon energy structure and reducing costs.Finally,we develop a multi-objective economic-robust optimization model that minimizes total system costs while maximizing robustness.The Non-dominated Sorting Genetic Algorithm Ⅱ are integrated with the Wolf Pack Algorithm(NSGA-Ⅱ-WPA)to derive optimal scheduling schemes for integrated energy systems.The integrated algorithm offers a wide search range and superior search efficiency,providing decision-makers with solutions that simultaneously meet economic,low-carbon,and robust goals.关键词
综合能源系统/阶梯绿证-碳融合交易/多目标优化调度/分布鲁棒优化/热电灵活响应Key words
integrated energy system/stepwise green certificate-carbon integrated trading/multi-objective optimization scheduling/distributionally robust optimization/flexible combined heat and power response分类
信息技术与安全科学引用本文复制引用
赵国,任祁源,田爱娜,张驰,饶章展鹏..计及绿证-碳交易的综合能源系统鲁棒经济优化调度[J].重庆理工大学学报,2025,39(5):195-205,11.基金项目
国家自然科学基金项目(52207233) （52207233）
