发电技术 ›› 2022, Vol. 43 ›› Issue (3): 485-491.DOI: 10.12096/j.2096-4528.pgt.20083

• 智能电网 • 上一篇    下一篇

计及风电预测误差的柔性负荷日内调度模型

雷旭1, 马鹏飞1, 宋智帅2, 李卫东3   

  1. 1.神华宝日希勒能源有限公司,内蒙古自治区 呼伦贝尔市 021000
    2.呼伦贝尔职业技术学院,内蒙古自治区 呼伦贝尔市 021000
    3.国网冀北电力有限公司承德供电公司,河北省 承德市 067000
  • 收稿日期:2021-07-18 出版日期:2022-06-30 发布日期:2022-07-06
  • 作者简介:雷旭(1988),男,工程师,研究方向为微网优化规划设计,175196248@qq.com
    马鹏飞(1986),男,工程师,研究方向为市电网规划和配电系统自动化,295059404@qq.com
    宋智帅(1987),女,助理讲师,研究方向为分布式发电,769611848@qq.com
    李卫东(1995),男,硕士,研究方向为综合能源系统优化,liweidong13579@163.com

A Flexible Intraday Load Dispatch Model Considering Wind Power Prediction Errors

Xu LEI1, Pengfei MA1, Zhishuai SONG2, Weidong LI3   

  1. 1.Shenhua Baorixile Energy Industry Co. , Ltd. , Hulunbuir 021000, Inner Mongolia Autonomous Region, China
    2.Hulunbuir Vocational Technical Collage, Hulunbuir 021000, Inner Mongolia Autonomous Region, China
    3.State Grid Chengde Power Supply Company, Chengde 067000, Hebei Province, China
  • Received:2021-07-18 Published:2022-06-30 Online:2022-07-06

摘要:

由于风电的不确定性与随机性导致风电出力难以精确预测,进而导致依据风电预测值所建立的日前调度模型存在一定的局限性,为解决此问题并提升风电消纳比例,提出一种计及风电预测误差的柔性负荷日内调度模型。首先,对储能和工业高载能负荷等可控柔性负荷进行建模;然后,考虑风电预测误差的概率分布特性,并基于日前调度计划建立以风电消纳量最高为目标的日内调度模型;最后,在保证系统安全可靠基础上,通过基于MATLAB的遗传算法进行优化。仿真结果表明:与日前调度计划相比,日内调度模型风电消纳比例提升了1.83%,验证了所提调度模型的有效性;通过对柔性负荷的超短期调度,可有效解决仅依据日前计划进行调度易出现电力系统功率不平衡的问题,提高电力系统稳定性。

关键词: 风电预测, 调度模型, 柔性负荷, 风电消纳, 遗传算法(GA)

Abstract:

Due to the uncertainty and randomicity of wind power, it is difficult to accurately predict wind power, which leads to certain limitations of day-ahead dispatch model established based on wind power prediction. In order to solve this problem and improve wind power accommodation ratio, a flexible load day-ahead dispatch model considering wind power prediction error was proposed. Firstly, the controllable flexible loads, such as energy storage and industrial high load load, were modeled. Secondly, the probabilistic distribution characteristics of wind power prediction errors were considered, and a day-ahead dispatch model aiming at the maximum wind power accommodation was established. Finally, based on ensuring the safety and reliability of the system, the dispatch model was optimized by genetic algorithm based on MATLAB. The simulation results show that compared with the day-ahead dispatch model, the wind power accommodation is increased by 1.83%, and the efficiency of the proposed dispatch model is verified. Moreover, the imbalance problems of power system power is solved effectively by the short-term scheduling of the flexible load. The stability of power system is improved.

Key words: wind power predictioin, dispatch model, flexible load, wind power accommodation, genetic algorithm(GA)

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