1.河南科技大学应用工程学院,河南省 三门峡市 472000
2.三门峡职业技术学院, 河南省 三门峡市 472000
3.郑州浪潮数据技术有限公司,河南省 郑州市 450000
4.河南省机器人与智能系统重点实验室,河南省 洛阳市 471000
陈锋(1987),男,硕士,副教授,高级工程师,研究方向为高比例新能源新型电力系统优化运行与智能控制,chenfeng@smxpt.edu.cn;
路小敏(1989),女,硕士,工程师,研究方向为大数据与云计算,252991887@qq.com;
沈冰(1977),男,博士,教授,研究方向为新能源、分布式发电和智能微电网建模与控制等,750762185@qq.com;
王军鹏(1979),男,硕士,教授,研究方向为新能源、分布式发电和智能微电网建模与控制等,342717571@qq.com。
收稿:2025-04-29,
修回:2025-06-06,
纸质出版:2025-12-31
移动端阅览
陈锋,路小敏,沈冰等.基于消纳-保供博弈的分布式储能双层规划模型[J].发电技术,2025,46(06):1133-1143.
CHEN Feng,LU Xiaomin,SHEN Bing,et al.Bi-Level Planning Model for Distributed Energy Storage Based on Accommodation-Supply Security Game[J].Power Generation Technology,2025,46(06):1133-1143.
陈锋,路小敏,沈冰等.基于消纳-保供博弈的分布式储能双层规划模型[J].发电技术,2025,46(06):1133-1143. DOI: 10.12096/j.2096-4528.pgt.25195.
CHEN Feng,LU Xiaomin,SHEN Bing,et al.Bi-Level Planning Model for Distributed Energy Storage Based on Accommodation-Supply Security Game[J].Power Generation Technology,2025,46(06):1133-1143. DOI: 10.12096/j.2096-4528.pgt.25195.
目的
2
为解决分布式储能系统在“新能源消纳最大化”与“供电可靠性保障”之间的目标冲突,提出一种兼顾经济性与韧性的协同规划方法。
方法
2
构建一种动态Stackelberg博弈驱动的双层规划模型,将Stackelberg博弈与鲁棒优化组合,用来解决规划-运行跨层耦合问题;协调规划-运行-市场多方利益,优化储能容量配置与充放电策略,提高供电可靠性;通过双层优化实现规划-运行协同,量化消纳与保供的权衡关系;提出Pareto最优解集,实现最低投资成本、最高新能源消纳率。
结果
2
通过开发的多指标优化的双层模型快速求解算法,提出了“动态电价-容量补贴”联动机制,有效平衡了规划与运行中的多方利益冲突;将Stackelberg博弈与鲁棒优化组合,解决了规划-运行跨层耦合难题。仿真算例表明,所提出的双层博弈模型在性能上显著优于传统规划方法,验证了动态博弈机制的长期经济性,并揭示了新能源消纳与电力保供之间存在非线性权衡关系。
结论
2
基于消纳-保供博弈协同的双层规划模型,能够显著提升系统的新能源消纳率与供电可靠性,同时降低储能投资成本及用户用电成本。
Objectives
2
To address the conflicting objectives between “maximizing renewable energy accommodation” and “ensuring power supply reliability” in distributed energy storage systems
a coordinated planning method that balances economic efficiency and resilience is proposed.
Methods
2
A dynamic Stackelberg game-driven bi-level planning model is established
integrating Stackelberg game theory with robust optimization to address the cross-level coupling problem between planning and operation. The model coordinates the interests of planning
operation
and market stakeholders to optimize energy storage capacity allocation and charging/discharging strategies
thereby enhancing power supply reliability. Through bi-level optimization
coordination between planning and operation is achieved
and the trade-off between accommodation and supply security is quantified
with Pareto-optimal solutions derived to achieve the lowest investment costs and highest renewable energy accommodation rates.
Results
2
A rapid solution algorithm for a bi-level model incorporating multi-objective optimization is developed
and a “dynamic pricing-capacity subsidy” linkage mechanism is proposed. This mechanism effectively balances the conflicting interests among multiple stakeholders in planning and operation. By integrating Stackelberg game theory with robust optimization
the cross-level coupling problem between planning and operation is solved. The simulation cases demonstrate that the proposed bi-level game model significantly outperforms conventional planning methods
validating the long-term economic efficiency of the dynamic game mechanism. Furthermore
a nonlinear trade-off relationship between renewable energy accommodation and power supply security is revealed.
Conclusions
2
The bi-level planning model based on accommodation-supply security game coordination can significantly enhance the system’s renewable energy accommodation rate and power supply reliability
while reducing energy storage system investment costs and user electricity costs.
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