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多微电网系统中共享储能的最优配置:融合电池退役价值与可再生能源经济性消纳
Optimal configuration of shared energy storage for multi-microgrid systems: Integrating battery decommissioning value and renewable energy economic consumption
| 作者 | Yaoyao He · Yifan Zhang |
| 期刊 | Energy Conversion and Management |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 343 卷 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 微电网 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | Novel bi-level model for shared energy storage stations in multi-microgrids. |
语言:
中文摘要
摘要 随着能源结构的演变和共享经济的兴起,共享储能有望成为应对风能和太阳能波动、管理能源需求并提升系统灵活性的标准手段。本文提出一种面向多微电网系统的共享储能配置双层优化方法,聚焦于冷热电联供(CCHP)系统的经济效率。该方法考虑退役电池的残余价值,以促进未来电池回收利用并提高能源利用效率。上层模型解决储能容量配置问题,下层模型优化系统运行策略。通过引入Karush–Kuhn–Tucker(KKT)条件,将下层模型的约束条件嵌入上层模型,并采用大M法(Big-M method)实现线性化处理。通过四个场景的仿真验证了模型的有效性,结果表明,共享储能可使可再生能源消纳率从73.05%提升至99.93%,显著降低年均运行成本,并在4.44年内实现成本回收。然而,电池退化程度高于预期,当考虑电池寿命时,需增加17.6%的容量配置。服务提供商应采购低衰减、高性能的电池,并规划在第十二年左右实施电池退役,以最大化其残值,从而实现用户与服务提供方的双赢局面。
English Abstract
Abstract With the evolution of energy structures and the rise of the sharing economy, shared energy storage is poised to become a standard for managing energy demand and enhancing flexibility amidst wind and solar variability. This paper introduces a two-layer optimization method for shared energy storage configuration in multi-microgrids, focusing on economic efficiency in combined cooling, heating, and power (CCHP) systems. It accounts for the residual value of retired batteries to facilitate future battery recycling and improve energy utilization. The upper layer addresses capacity allocation, while the lower layer optimizes system operations. Using the Karush–Kuhn–Tucker conditions, the lower layer’s constraints are integrated into the upper layer, with the Big-M method applied for linearization. The model’s effectiveness is demonstrated through four scenarios, showing that shared energy storage increases renewable energy consumption from 73.05% to 99.93%, reduces annual operating costs, and achieves cost recovery in 4.44 years. However, battery degradation is higher than anticipated, necessitating an 17.6% increase in capacity allocation when battery life is considered. Service providers should procure low-degradation, high-performance batteries and plan battery retirement around the twelfth year to maximize residual value, fostering a beneficial scenario for both users and providers.
S
SunView 深度解读
该共享储能优化配置研究对阳光电源ST系列PCS及PowerTitan储能系统具有重要应用价值。论文提出的退役电池残值评估模型可指导我司储能系统全生命周期管理策略,特别是12年退役节点规划与梯次利用。双层优化方法可集成至iSolarCloud平台,实现多微网场景下的容量配置与运行优化。研究显示共享模式下新能源消纳率提升至99.93%,验证了我司储能系统在冷热电联供场景的经济性。建议结合我司低衰减电池技术,优化容量配置算法,缩短投资回收期,并开发面向共享储能的智能调度功能模块。