Optimization strategy for day-ahead bidding of virtual power plants in the provincial spot market

高卫恒; 李有亮; 陈天宇; 黄进; 栾喜臣; 梁肖

doi:10.3969/j.issn.1672-3643.2025.06.001

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

Optimization strategy for day-ahead bidding of virtual power plants in the provincial spot market

更新时间：2026-01-09

- Optimization strategy for day-ahead bidding of virtual power plants in the provincial spot market
- Ningxia Electric Power Issue 6, (2025)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1672-3643.2025.06.001
  CLC：
- Published Online：22 December 2025，
  
  Published：22 December 2025
- 稿件说明：
移动端阅览
高卫恒, 李有亮, 陈天宇, et al. Optimization strategy for day-ahead bidding of virtual power plants in the provincial spot market[J]. Ningxia Electric Power, 2025, (6).
DOI：

高卫恒, 李有亮, 陈天宇, et al. Optimization strategy for day-ahead bidding of virtual power plants in the provincial spot market[J]. Ningxia Electric Power, 2025, (6). DOI： 10.3969/j.issn.1672-3643.2025.06.001.

摘要

针对省间现货市场供需紧张情况下，虚拟电厂如何调用可调资源在省内现货市场申报以获得更多收益这一问题，构建了考虑省间现货市场下的虚拟电厂省内日前现货市场申报策略优化模型。引入双延迟深度确定性策略梯度算法（twin delayed deep deterministic policy gradient

TD3）生成了虚拟电厂内部资源运行策略以及省内现货市场的申报策略。算例结果表明，与不考虑省间现货市场的模型相比，本文所提出的模型能够提升虚拟电厂的经济性。

Abstract

To address how virtual power plants(VPPs)can optimally dispatch adjustable resources for bidding in the provincial spot market to maximize economic benefits under tight interprovincial supply-demand conditions

this paper develops an optimization model for the day-ahead bidding strategy of VPPs within a province

considering the influence of the interprovincial spot market.The twin delayed deep deterministic policy gradient(TD3)algorithm is employed to generate both the internal resource operation strategy of the VPP and its provincial spot market bidding strategy.Simulation results show that

compared with a model neglecting the interprovincial spot market

the proposed method significantly enhances the economic performance of the VPP.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Dynamic reconfiguration strategy for distribution networks under voltage violation constraints based on dueling deep Q-learning network

Related Author

HUANG Sheng

WANG Hongyu

QI Shenglong

LU Xiang

TANG Ting

WEI Tao

Related Institution

Electric Power Research Institute,State Grid Ningxia Electric Power Co .,Ltd .

State Grid Ningxia Electric Power Co .,Ltd .

China Gridcom Co.,Ltd.

AI问答

⁰