文章摘要
梁浚杰,兰飞,黎静华.以光伏为主的配电网储能容量需求的网格化场景评估方法[J].电力系统自动化,2018,42(23):40-47. DOI: 10.7500/AEPS20180313011.
LIANG Junjie,LAN Fei,LI Jinghua.Gridding Scenario Evaluation Method for Energy Storage Capacity Demand of Photovoltaic Based Distribution Network[J].Automation of Electric Power Systems,2018,42(23):40-47. DOI: 10.7500/AEPS20180313011.
以光伏为主的配电网储能容量需求的网格化场景评估方法
Gridding Scenario Evaluation Method for Energy Storage Capacity Demand of Photovoltaic Based Distribution Network
DOI:10.7500/AEPS20180313011
关键词: 储能容量  配电网  高比例可再生能源  网格化场景
KeyWords: energy storage capacity  distribution network  high-proportion renewable energy  gridding scenario
上网日期:2018-09-21
基金项目:国家重点研发计划资助项目(2016YFB0900100);国家自然科学基金资助项目(51377027)
作者单位E-mail
梁浚杰 广西电力系统最优化与节能技术重点实验室(广西大学), 广西壮族自治区南宁市 530004  
兰飞 广西电力系统最优化与节能技术重点实验室(广西大学), 广西壮族自治区南宁市 530004 lanfeigxu@163.com 
黎静华 广西电力系统最优化与节能技术重点实验室(广西大学), 广西壮族自治区南宁市 530004  
摘要:
      当前,如何确定光伏渗透率较高的配电网所需的储能容量是关键问题。对于包含多种功率调节手段的配电网来说,直接建立满足多种运行约束的储能容量需求优化模型较为复杂,解算不易。因此提出一种实用的网格化场景分析方法,该方法将包括储能在内的各种给定的运行条件在其取值范围内进行等格划分,将各种运行条件的取值相互组合形成网格场景。通过计算每种场景下的技术性指标,获得不同运行条件下的储能容量需求关系图。根据给定的运行条件和运行指标要求,从储能容量需求关系图获取相应的储能容量需求,从而避免了复杂的优化模型计算。最后,以改造后的IEEE 33节点配电网为例,演示了应用所述方法确定储能容量需求的过程,并对所确定的方案进行评估分析,验证了该方法的有效性。
Abstract:
      At present, the key issue is how to determine the demand of energy storage in the distribution network with high photovoltaic penetration. However, it is complex to directly model for the distribution network which contains various power regulation methods, and the model is difficult to solve. Therefore, a practical gridding scenario analysis method is proposed. Firstly, the proposed method evenly divides every given operation condition within corresponding ranges, and then combines all given operation conditions to generate grid scenarios. Secondly, the technical indices of each scenario are calculated, and the relation diagrams of energy storage demand under different operation conditions are further obtained. As a result, the demand of energy storage is obtained by the relation diagram with given operation conditions and indices, which avoids the complex establishment and calculation of the optimization model. Finally, the modified IEEE 33-node distribution system is taken as an example and the process of determining the energy storage demand by the proposed method is demonstrated. The simulation results show the procedure, evaluation and analysis of proposed scheme, which verifies the effectiveness of the proposed method.
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