储能科学与技术 ›› 2023, Vol. 12 ›› Issue (4): 1204-1214.doi: 10.19799/j.cnki.2095-4239.2022.0754

• 储能系统与工程 • 上一篇    下一篇

基于分时电价与储能充放电策略的台区可调控资源聚合及调度

汪锋1(), 刘智强1, 张克勇1, 王冠瑞1, 殷红德1, 贾子昊1, 赵海辉2(), 米阳2   

  1. 1.国网平顶山供电公司,河南 平顶山 467002
    2.上海电力大学电气工程学院,上海 200090
  • 收稿日期:2022-12-16 修回日期:2023-01-11 出版日期:2023-04-05 发布日期:2023-05-08
  • 通讯作者: 赵海辉 E-mail:2979587791@qq.com;962541526@qq.com
  • 作者简介:汪锋(1971—),男,高级工程师,从事配电网研究,E-mail:2979587791@qq.com
  • 基金资助:
    国网河南省电力公司科技项目(521760220003)

Adjustable resource aggregation and scheduling in distribution transformer station areas based on time-of-use price and charge-discharge strategy of energy storage

Feng WANG1(), Zhiqiang LIU1, Keyong ZHANG1, Guanrui WANG1, Hongde YIN1, Zihao JIA1, Haihui ZHAO2(), Yang MI2   

  1. 1.State Grid Pingdingshan Municipal Electric Power Company, Pingdingshan 467002, Henan, China
    2.College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
  • Received:2022-12-16 Revised:2023-01-11 Online:2023-04-05 Published:2023-05-08
  • Contact: Haihui ZHAO E-mail:2979587791@qq.com;962541526@qq.com

摘要:

能源互联网背景下,为实现台区可调控资源的协调调度及不同类型能量单元的协调优化,本文提出一种计及用户用电成本及用能舒适度的基于分时电价与分布式储能充放电策略的台区可调控资源聚合方法及协调调度策略。首先,遵循配电物联网体系架构,基于“云-边”协同技术构建了台区用能管控系统框架;然后,根据响应不确定性对台区负荷进行分类并利用蒙特卡洛算法对典型可调控资源进行功率聚合并分析聚合模型有效性;最后,引入负荷聚合商与台区进行互动,利用线性加权法计及用户用电成本与用能舒适度并结合分布式储能充放电策略对台区可调控资源调度模型建模,采用差分进化算法对模型求解。通过算例分析表明,本文所提可调控资源聚合模型及协调调度策略可以有效降低用户用能成本、提高用能舒适度,促进了用户参与电网响应的积极性,提升了台区对可调控资源的管控能力。

关键词: 配电物联网, 台区用能管控, 可调控资源聚合, 负荷聚合商, 协调调度

Abstract:

This paper proposes an adjustable resource aggregation method and a coordinated scheduling strategy in distribution transformer station area based on time-of-use price and charge-discharge strategy for distributed energy storage considering the user's electricity cost and energy comfort. The proposed methods can realize the coordinated scheduling of adjustable resources and the coordinated optimization of different types of energy units in the distribution transformer station areas. First, the framework of the platform energy use management and control system is constructed, following the architecture of the distribution Internet of Things and based on the "cloud-edge" collaborative technology. Then, the platform loads are classified according to the response uncertainty, and the Monte Carlo algorithm is used to aggregate the power of typical adjustable resources. The effectiveness of the aggregation model is then analyzed. Finally, the load aggregator is introduced to interact with the station area. The linear weighting method is used to calculate the electricity cost and energy consumption comfort level of users, and the charge-discharge strategy of distributed energy storage is combined to model the adjustable resource scheduling model of the distribution transformer station area. The differential evolution algorithm is then used to solve the model. The example analysis shows that the adjustable resource aggregation model and the coordinated scheduling strategy proposed in this paper can effectively reduce the energy consumption cost of users, improve the energy consumption comfort level, promote the enthusiasm of users to participate in grid response and improve the station area's ability to control the adjustable resources.

Key words: distribution internet of things, power consumption control in distribution transformer station area, adjustable resources aggregation, load aggregators, coordinated scheduling

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