• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2020, Vol. 41 ›› Issue (10): 98-105.doi: 10.12204/j.issn.1000-7229.2020.10.011

• 智能电网 • 上一篇    下一篇

偏差电量考核机制下售电公司CCHP系统运行优化模型

喻理, 李成鑫, 张宇, 刘宜成   

  1. 四川大学电气工程学院, 成都市 610065
  • 收稿日期:2020-06-03 出版日期:2020-10-01 发布日期:2020-09-30
  • 通讯作者: 李成鑫
  • 作者简介:喻理(1995),男,硕士研究生,主要研究方向为综合能源服务;|张宇(1996),男,硕士研究生,主要研究方向为综合能源服务;|刘宜成(1975),男,副教授,主要研究方向为机器人、无人飞行器、非线性控制。
  • 基金资助:
    国家自然科学基金项目(51807125)

Optimal Model for CCHP of Power Retailer Considering the Daily Deviation Penalty

YU Li, LI Chengxin, ZHANG Yu, LIU Yicheng   

  1. College of Electrical Engineering, Sichuan University, Chengdu 610065, China
  • Received:2020-06-03 Online:2020-10-01 Published:2020-09-30
  • Contact: LI Chengxin
  • Supported by:
    National Natural Science Foundation of China(51807125)

摘要:

针对我国电力现货市场形成前的过渡阶段售电公司偏差电量考核风险问题,提出利用冷热电联供(combined cooling, heating and power, CCHP)系统的可控出力特性,将其作为降低偏差电量的有效手段。同时,在日结算周期的偏差电量考核机制下,提出了计及偏差电量考核成本的售电公司CCHP滚动优化模型,解决了降低偏差电量的可操作性问题。以某售电公司代理用户负荷数据为例的仿真算例表明,不管在正偏差还是负偏差情况下,通过滚动优化调节CCHP的出力,可在降低偏差电量考核成本的同时,提高售电公司的整体盈利。

关键词: 偏差电量考核, 售电公司, 冷热电联供系统, 滚动优化

Abstract:

The power retailers face the risk of electricity deviation penalty in the transitional period before the formation of the spot market of electric power in China. In this paper, the CCHP system is provided as an effective means to reduce the deviation power because of its controllable output. At the same time, the rolling optimal model of the CCHP considering the cost of deviation power penalty is proposed under the daily deviation penalty mechanism, which solves the operability problem of reducing the deviation power. The simulation is performed on the basis of the load of a power retailer. The simulation results show that, no matter in the case of positive deviation or negative deviation, by rolling optimization of the operation mode of CCHP, the cost of deviation penalty can be reduced and the overall revenue of the power retailer can be improved.

Key words: deviation penalty, power retailer, CCHP system, rolling optimization

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