上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (9): 1146-1155.doi: 10.16183/j.cnki.jsjtu.2022.269

所属专题: 《上海交通大学学报》2023年“新型电力系统与综合能源”专题

• 新型电力系统与综合能源 • 上一篇    下一篇

面向高比例清洁能源消纳的含灵活性资源电力系统规划方案优选

郭咏涛, 向月(), 刘俊勇   

  1. 四川大学 电气工程学院,成都 610065
  • 收稿日期:2022-07-12 修回日期:2022-07-27 接受日期:2022-08-16 出版日期:2023-09-28 发布日期:2023-09-27
  • 通讯作者: 向月 E-mail:xiang@scu.edu.cn
  • 作者简介:郭咏涛,硕士生,从事综合能源系统规划研究.
  • 基金资助:
    国家自然科学基金(U2166211)

Optimal Planning of Power Systems with Flexible Resources for High Penetrated Renewable Energy Accommodation

GUO Yongtao, XIANG Yue(), LIU Junyong   

  1. College of Electrical Engineering, Sichuan University, Chengdu 610065, China
  • Received:2022-07-12 Revised:2022-07-27 Accepted:2022-08-16 Online:2023-09-28 Published:2023-09-27
  • Contact: XIANG Yue E-mail:xiang@scu.edu.cn

摘要:

高比例清洁能源具有波动性及间歇性等特点,其大规模接入给电力系统灵活性带来巨大挑战.为提升系统可再生能源消纳能力,考虑火电灵活性改造、投建燃气机组和投建储能的多种灵活性资源,建立一种计及多类型灵活性资源功率特性的电力系统规划方案优选模型.通过改进的IEEE 24节点电力系统和12节点天然气互联系统进行仿真分析,验证所提模型的有效性,并从经济性、消纳能力、低碳性等角度对灵活性规划方案进行优选以满足不同的规划需求.

关键词: 高比例清洁能源, 灵活性资源, 电力系统规划, 方案优选

Abstract:

High penetrated renewable energy has brought great challenges to the flexibility of the power system due to its volatility and intermittency. To improve the capacity of renewable energy accommodation, the flexibility reformation of thermal power units, the construction of gas-fired units, and the electrical energy storage installation are considered as effective solutions. Thus, an optimization model for power system planning scheme considering multi-type flexible resources with their different output characteristics is established. The simulation results on a modified IEEE 24-bus power system and 12-node natural gas system demonstrate the effectiveness of the proposed model. In addition, the applicability of different flexible resource planning schemes is comprehensively evaluated from the perspectives of economy, accommodation capacity, and carbon reduction, so as to meet the different planning goals.

Key words: high penetrated renewable energy, flexibility resources, power system planning, scheme optimization

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