节点文献

利用云储能租赁服务的风电场储能容量优化配置

Optimized configuration of energy storage capacity of wind farms using cloud energy storage leasing services

  • 推荐 CAJ下载
  • PDF下载
  • 不支持迅雷等下载工具,请取消加速工具后下载。

【作者】 唐夏菲吴献祥任青青曹俊波周博洋李斌周任军

【Author】 TANG Xiafei;WU Xianxiang;REN Qingqing;CAO Junbo;ZHOU Boyang;LI Bin;ZHOU Renjun;Hunan Collaborative Innovation Center for Clean Energy and Smart Grid (Changsha University of Science and Technology);State Grid Jiangxi Electric Power Co., Ltd.Pingxiang Power Supply Branch;State Grid Shandong Electric Power Company Zaozhuang Power Supply Company;

【通讯作者】 周任军;

【机构】 长沙理工大学湖南省清洁能源与智能电网协同创新中心国网江西省电力有限公司萍乡供电分公司国网山东省电力公司枣庄供电公司

【摘要】 云储能聚合了大量分布式储能与集中式储能的控制信息,风电场通过租赁云储能和自建实体储能可实现出力功率可控。为延长自建储能设备使用寿命,设计了功率分配策略。以自建储能设备全寿命周期成本、云储能租赁费用、弃风惩罚成本、缺电惩罚成本最小为目标函数,建立风电场自建储能与租赁云储能容量最优配置模型。仿真分析表明,不同的云储能租赁单价,将影响云储能利用和充放电结果,从而影响自建储能的最优配置容量。云储能租赁和自建实体储能的合理配置,具有良好有效的经济性和实用性。

【Abstract】 Cloud energy storage can aggregate a large amount of distributed energy storage and centralized energy storage control information. The wind farm can realize the controllability of the output power by renting cloud energy storage and self-built physical energy storage. In order to extend the service life of self-built energy storage equipment, a power allocation strategy is designed. Based on the life cycle cost of self-built energy storage equipment, cloud energy storage energy lease cost, abandoned wind penalty cost, and minimum power shortage penalty cost, the optimal configuration model of the self-built energy storage and the leased cloud energy storage capacity is established for a wind farm. Simulation analysis shows that the energy rental unit prices of different cloud energy storage will affect the cloud energy storage energy utilization, charge and discharge results, thus affecting the optimal configuration capacity of self-builtenergy storage. The reasonable allocation of cloud energy storage energy lease and self-built physical energy storage has good economy and practicality.

【基金】 湖南省自然科学基金(2019JJ40302)
  • 【文献出处】 电力科学与技术学报 ,Journal of Electric Power Science and Technology , 编辑部邮箱 ,2020年01期
  • 【分类号】TM614
  • 【被引频次】15
  • 【下载频次】421
节点文献中: 

本文链接的文献网络图示:

本文的引文网络