| 龚桃荣,王舒杨,代勇奇,梁 琛.基于分级风险管理的冷链物流园区多目标优化运行策略[J].电力需求侧管理,2025,27(6):23-30 |
| 基于分级风险管理的冷链物流园区多目标优化运行策略 |
| Distributed PV accommodation strategy for cold chain logistics parks based on hierarchical risk management |
| 投稿时间：2025-07-29 修订日期：2025-08-29 |
| DOI：10. 3969 / j. issn. 1009-1831. 2025. 06. 004 |
| 中文关键词: 冷链物流 分布式光伏 微电网优化 下行风险 多目标优化 |
| 英文关键词: cold chain logistics distributed photovoltaic microgrid optimization downside risk multi-objective optimization |
| 基金项目:国家电网公司总部科技项目（5400-202433204A-1-1-ZN） |
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| 中文摘要: |
| 针对含分布式光伏的冷链物流园区微电网协同优化问题，冷链园区因制冷系统需24小时连续运行维持严格温控（-18±2 °C），而光伏出力集中在日间10:00—15:00时，物流作业多在凌晨和傍晚进行，这种用电时序与光伏出力的错配导致光伏消纳困难。提出一种兼顾光伏消纳率与运行经济性的调度策略，以解决光伏出力强随机性导致的高弃光率问题，以及多目标协同优化的复杂性挑战。在构建‘源-荷-储’3侧协同架构的基础上，采用k-means聚类生成典型出力场景及概率分布，通过下行风险约束量化场景概率下的成本波动风险，提供从风险规避到风险中性的连续调控空间。建立光伏消纳率最大化与综合成本最小化的多目标模型，提出基于目标函数变化率的动态权重理想点法，并设计改进逃生算法求解该模型。算例表明，在确定风险调控下，园区光伏消纳率达95.13%，日运行成本降至7 356元，较优化前成本降低21.60%。验证了所提协同优化方法能有效提升分布式光伏消纳能力与运行经济性，为含高比例新能源及温控负荷的复杂微电网调度提供了可行的解决方案和理论支撑。 |
| 英文摘要: |
| To address the collaborative optimization challenges of microgrids containing distributed photovoltaics（PV）in cold chain logistics parks, where the refrigeration systems require 24-hour continuous operation to maintain strict temperature control（-18°C±2°C）while PV output concentrates during 10:00—15:00 and logistics operations mainly occur in early morning and evening, this temporal mismatch between power demand and PV generation leads to severe PV curtailment. Proposing a scheduling strategy that balances PV consumption rate and operational economy. This strategy tackles the issues of high PV curtailment caused by strong PV output randomness and the complexity of multi-objective cooperative optimization. A tripartite collaborative architecture of“source-load-storage”is constructed. Typical PV output scenarios and their probability distributions are generated using the k-means clustering algorithm. Downside risk constraints are employed to quantify the cost fluctuation risk under these scenario probabilities, providing a continuous regulation space spanning from risk aversion to risk neutrality. A multi-objective optimization model is established to maximize the PV consumption rate and minimize the comprehensive operational cost. A dynamic-weight ideal point method based on the rate of change of the objective functions is proposed.An improved escape algorithm is designed to solve this model. Case studies demonstrate that under a defined risk regulation level, the park’s PV consumption rate reaches 95.13% , and the daily operating cost is reduced to RMB 7 356, representing a cost reduction of 21.60% compared to pre- optimization levels. The results verify that the proposed collaborative optimization method can effectively enhance distributed PV consumption capability and operational economy. It provides a viable solution and theoretical foundation for scheduling complex microgrids containing high-penetration renewable energy and thermostatically controlled loads. |
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