| 引用本文: | 吕斌,黄丹,丁宏,吕朋朋.基于共享储能的台区多元负荷协同控制策略[J].电力自动化设备,2024,44(1):32-39. |
| Lü Bin,HUANG Dan,DING Hong,Lü Pengpeng.Multivariate load collaborative control strategy in transformer district based on shared energy storage[J].Electric Power Automation Equipment,2024,44(1):32-39. |
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| 摘要: |
| 大规模不确定可再生能源的接入，对台区电网负荷的灵活性调整提出了更高的要求。基于共享储能的商业模式，考虑各类电器设备的用电及功能特性，提出了台区多元负荷协同控制策略。提出了基于共享储能的台区多元负荷协同优化框架，并详细阐述了多元负荷的协同控制过程；根据负荷的可调特性，对用户负荷进行分类，建立负荷功率模型和舒适度成本模型；建立了以用电综合成本最低为目标的用户层优化模型和以调峰为目标的台区层优化模型。基于实际数据进行仿真验证，结果表明所提控制策略可以有效保证新能源的消纳，降低峰值负荷，并协助用户参与电力辅助服务市场。 |
| 关键词: 共享储能 可再生能源消纳 多元负荷 需求响应 调峰辅助服务 协同控制 |
| DOI：10.16081/j.epae.202302007 |
| 分类号:TM73 |
| 基金项目: |
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| Multivariate load collaborative control strategy in transformer district based on shared energy storage |
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Lü Bin1, HUANG Dan2, DING Hong3, Lü Pengpeng3
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1.State Grid Anhui Electric Power Co.,Ltd.,Hefei 230022, China;2.Marketing Service Center of State Grid Anhui Power Co.,Ltd.,Hefei 230088, China;3.State Grid Electric Power Research Institute, Nanjing 211106, China
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| Abstract: |
| The access of large-scale uncertain renewable energy puts forward higher requirements for the flexibility adjustment of power grid load in the transformer district. Based on the business modes of shared energy storage and considering the power consumption and functional characteristics of various electrical equipment, a multivariate load collaborative control strategy is proposed for the transformer district. A collaborative optimization framework of multivariate load based on the shared energy storage is proposed and the collaborative control process of multivariate load is elaborated. According to the adjustable characteristics of load, the user load is classified and the load power model and the comfort cost model are established. The user layer optimization model with the lowest comprehensive cost of power consumption as the objective and the transformer district layer optimization model with the peak-shaving as the objective are established. Based on the actual data, the simulative results show that the proposed control strategy can effectively ensure the consumption of renewable energy, reduce the peak load, and assist users to participate in the power auxiliary service market. |
| Key words: shared energy storage renewable energy consumption multivariate load demand response peak-shaving auxiliary service collaborative control |
