中国电力 ›› 2022, Vol. 55 ›› Issue (6): 53-64.DOI: 10.11930/j.issn.1004-9649.202107019

• 电力市场模型研究及应用 • 上一篇    下一篇

考虑需求侧灵活性资源的区域电能共享市场模型

艾欣, 徐立敏   

  1. 华北电力大学 电气与电子工程学院,北京 102206
  • 收稿日期:2021-07-06 修回日期:2022-03-23 出版日期:2022-06-28 发布日期:2022-06-18
  • 作者简介:艾欣(1964—),男,通信作者,教授,博士生导师,从事新能源电力系统及微网技术研究,E-mail:aixin@ncepu.edu.cn;徐立敏(1996—),女,硕士研究生,从事电力系统分析与控制技术研究,E-mail:15010972855@163.com
  • 基金资助:
    国家重点研发计划资助项目(支撑低碳冬奥的智能电网综合示范工程,2016YFB0900500)。

Community Energy Sharing Market Model Considering Flexible Resources on Demand Side

AI Xin, XU Limin   

  1. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China
  • Received:2021-07-06 Revised:2022-03-23 Online:2022-06-28 Published:2022-06-18
  • Supported by:
    This work is supported by National Key R&D Program of China (Smart Grid Demonstration Project to Supporting the Low-Carbon Winter Olympics, No.2016YFB0900500).

摘要: 提出考虑需求侧灵活性资源、用于区域电能共享市场的双侧竞拍机制,市场内包含分布式太阳能产消者和消费者。假设所有产消者和消费者形成的代理商拥有灵活的可按需求响应利用的聚合电动汽车和储能设备。首先,采用鲁棒虚拟电池模型描述价格激励下聚合电动汽车灵活性,实现可靠经济地扩大储能容量。然后,代理商在区域电能共享中设置最优的储能系统充放电计划,降低用电成本。之后,将管理好的产消者和消费者用于市场,为计算双侧竞拍市场的现货价格,所有区域产消者和消费者采用非合作博弈。提出迭代算法用于出清市场和最小化供需电能不确定性。最后,以区域内10个代理商为例,验证描述需求侧灵活性资源的虚拟电池模型和区域电能共享市场模型有效性。

关键词: 需求侧灵活性资源, 鲁棒虚拟电池, 区域电能共享市场, 非合作博弈, 双侧竞拍

Abstract: A two-sided bidding mechanism considering flexible resources on the demand side is proposed for the community energy sharing market, and prosumers and consumers of distributed solar energy are included in the market. It is assumed that the agents formed by all consumers and prosumers have flexible aggregated electric vehicles (EVs) and energy storage equipment that can be used in demand response. Firstly, a robust virtual battery (VB) model is used to describe the flexibility of aggregated EVs under price incentives to achieve reliable and economic expansion of energy storage capacity. Then, agents set the optimal charging and discharging plan for the energy storage system in the community energy sharing market to reduce the cost of electricity. After that, the managed prosumers and consumers are applied in the market, and the non-cooperative game is employed by all community consumers and prosumers to calculate the spot price in the two-sided bidding market. An iterative algorithm is presented to clear the market and minimize the uncertainty of power supply and demand. Finally, ten agents in the community are taken as examples to verify the effectiveness of the VB model for describing the flexible resources on the demand side and the community energy sharing market model.

Key words: flexible resources on the demand side, robust virtual battery, community energy sharing market, non-cooperative game, two-sided bidding