含光热电站的虚拟电厂多时间尺度热电联合优化调度

张国斌; 朱岑; 袁桂丽; 付余; 李洪波; 杭晨辉

doi:10.19725/j.cnki.1007-2322.2023.0380

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含光热电站的虚拟电厂多时间尺度热电联合优化调度

新能源电力系统 | 更新时间：2026-04-02

- 含光热电站的虚拟电厂多时间尺度热电联合优化调度
- Multi-time Scale Thermoelectric Joint Optimal Dispatching of Virtual Power Plant With Solar-thermal Power Station
- 现代电力 2026年43卷第2期页码：265-275
- 作者机构：
  
  1. 内蒙古电力(集团)有限责任公司内蒙古电力科学研究院分公司, 内蒙古自治区,呼和浩特市,010020
  2. 华北电力大学控制与计算机工程学院, 北京市昌平区,102206
  3. 内蒙古电力(集团)有限责任公司电力调度控制分公司, 内蒙古自治区,呼和浩特市,010010
- 作者简介：
  
  [ "张国斌(1972)，男，硕士，教授级高级工程师，研究方向为火电厂热工自动化控制，E-mail：zgb7230@163.com" ]
  [ "朱岑(1999)，女，硕士研究生，研究方向为虚拟电厂优化调度，E-mail：zczl4183@163.com" ]
  [ "袁桂丽(1971)，女，博士，教授，主要研究方向为信息控制、先进控制策略及其应用、电力系统控制与优化调度，E-mail：guili_yuan@163.com" ]
- 基金信息：
  
  内蒙古自治区科技重大专项项目(2021ZD0026)。
- DOI：10.19725/j.cnki.1007-2322.2023.0380
  中图分类号： 2
- 纸质出版：2026
- 稿件说明：
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张国斌, 朱岑, 袁桂丽, 等. 含光热电站的虚拟电厂多时间尺度热电联合优化调度[J]. 现代电力, 2026,43(2):265-275.

ZHANG Guobin, ZHU Cen, YUAN Guili, et al. Multi-time Scale Thermoelectric Joint Optimal Dispatching of Virtual Power Plant With Solar-thermal Power Station[J]. 2026, 43(2): 265-275.
张国斌, 朱岑, 袁桂丽, 等. 含光热电站的虚拟电厂多时间尺度热电联合优化调度[J]. 现代电力, 2026,43(2):265-275. DOI： 10.19725/j.cnki.1007-2322.2023.0380.

ZHANG Guobin, ZHU Cen, YUAN Guili, et al. Multi-time Scale Thermoelectric Joint Optimal Dispatching of Virtual Power Plant With Solar-thermal Power Station[J]. 2026, 43(2): 265-275. DOI： 10.19725/j.cnki.1007-2322.2023.0380.

摘要

为提高虚拟电厂调度计划的精确性，充分挖掘虚拟电厂内灵活性资源的调节潜力，该文提出一种日前–日内多时间尺度优化调度方法，对风光出力和负荷分别进行日前预测和日内预测。采用储能电池对日内风光出力波动进行平抑。利用光热电站对热电机组解耦，降低热电机组最小出力，考虑不同响应速度的需求响应资源，建立含光热电站的虚拟电厂多时间尺度热电联合优化调度模型，采用自适应遗传算法求解。算例仿真结果表明：相较于传统日前调度，多时间尺度优化调度能够获得更加精细的调度计划，进一步促进风光消纳，降低虚拟电厂出力偏差，提高虚拟电厂经济性。

Abstract

To enhance the accuracy of the virtual power plant scheduling plan and fully exploit the adjustment potential of flexible resources in the virtual power plant

in this paper we propose a day-ahead and intraday multi-time scale optimization scheduling method that makes both day-ahead and intraday forecast of wind and solar output as well as load. Additionally

we utilize energy storage batteries to smooth the fluctuations of intraday wind and solar output

employ solar-thermal power station to decouple the thermoelectric units with the aim of mitigating their minimum output

and consider demand response resources with varying response speeds. A multi-time scale thermoelectric joint optimization scheduling model for virtual power plants containing solar-thermal power stations is established

and the adaptive genetic algorithm is employed to solve it. The simulation results of the example show that

compared to traditional day-ahead scheduling

the multi-time scale optimal dispatching enables a more refined dispatching plan

thereby further promoting wind and solar consumption

reducing the output deviation of the virtual power plant

and improving the economy of the virtual power plant.

关键词

Keywords

references

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