计及深度调峰辅助服务与多典型日的年度发电计划优化模型
作者:
作者单位:

1.重庆电力交易中心有限公司;2.重庆大学 输配电装备及系统安全与新技术国家重点实验室

作者简介:

通讯作者:

中图分类号:

TM732??????????

基金项目:


Annual power generation plan optimization model considering deep peak regulation auxiliary services and multiple typical days
Author:
Affiliation:

1.Chongqing Electric Power Trading Center Co,Ltd;2.State Key Laboratory of Power Transmission Equipment System Security and New Technology,Chongqing University

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    在调峰市场背景下,机组调峰成本与辅助服务费用对发电企业影响较大,据此,提出了计及深度调峰辅助服务与多典型日的年度发电计划优化模型。在场景获取方面,提出了考虑负荷与风电耦合的典型场景聚类方法,有效解决了月内多个典型日场景的模拟问题。在模型方面,考虑了深度调峰成本、辅助服务补偿费用、售电利益与碳交易成本,建立了发电企业参与深度调峰辅助服务市场的收益约束,确保市场各主体能从中获利。考虑到该模型属于非线性混合整数规划问题,结合线性化策略和CPLEX求解器实现了高效求解。最后,基于修正算例系统进行了仿真分析,验证了所提模型的有效性。

    Abstract:

    Under the background of the deep peak regulation auxiliary service market, unit peak regulation costs and auxiliary service fees have a great impact on power generation companies. Based on this issue, this paper proposed an annual generation plan optimization model considering deep peak regulation auxiliary services and multiple typical days. In terms of scene acquisition, a typical scene clustering method considering the coupling of load and wind power was proposed, which effectively solves the simulation problem of multiple typical daily scenes in a month. In terms of the model, considering the deep peak regulation cost, auxiliary services compensation, benefit of electricity sales and carbon trading cost, the income constraints of generation companies participating in the auxiliary service market were established to ensure that market entities can profit from it. Considering that the model is a nonlinear mixed integer programming problem, this paper used linearization strategy and CPLEX solver to achieve an efficient solution. Finally, this paper carried out simulation analysis based on the modified example system, which verified the effectiveness of the proposed model.

    参考文献
    相似文献
    引证文献
引用本文
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2021-04-30
  • 最后修改日期:2021-10-28
  • 录用日期:2021-10-28
  • 在线发布日期:
  • 出版日期: