| 引用本文: | 周天娇,周任军,黄婧杰,秦子恺,杨洪明.储能聚合商自营共享模式下电能交易方法[J].电力自动化设备,2023,43(5): |
| ZHOU Tianjiao,ZHOU Renjun,HUANG Jingjie,QIN Zikai,YANG Hongming.Energy trading method of energy storage aggregators under self-operating and sharing mode[J].Electric Power Automation Equipment,2023,43(5): |
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| 摘要: |
| 针对用户侧分布式储能成本较高、利用率低、运营模式单一等问题，提出了一种兼具电能自营和储能共享模式的储能聚合商(ESA)自营共享电能交易方法，ESA分别从与电网公司、用户的电能交易中获益。基于分时电价和用户负荷预测，建立ESA控制储能充放电的日前优化模型，以ESA与电网之间的交易成本最小化为目标，获得ESA日前各时段的充放电电量，并将其作为ESA实时优化和定价的储能控制策略。以最大化ESA效益为主目标、最大化用户日效益为从目标，以内部电价为控制变量、用户用电量为状态变量，以内部电价限价、用电刚性需求等为约束，建立一种基于主从博弈的电能交易实时优化模型。算例仿真表明：ESA对日前储能充放电的决策获得了最低购电成本；主从博弈优化的电能交易决策了内部电价，提升了ESA和用户的经济效益。ESA自营共享电能交易方法是电力系统在共享经济模式下的有效尝试。 |
| 关键词: 储能共享 分布式储能 聚合商 运营模式 主从博弈 电能交易 |
| DOI：10.16081/j.epae.202302020 |
| 分类号:F426.61;TM732 |
| 基金项目:国家自然科学基金资助项目(52077009)；湖南省自然科学基金资助项目(2022JJ40478) |
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| Energy trading method of energy storage aggregators under self-operating and sharing mode |
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ZHOU Tianjiao, ZHOU Renjun, HUANG Jingjie, QIN Zikai, YANG Hongming
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Hunan Province Collaborative Innovation Center of Clean Energy and Smart Grid, Changsha University of Science and Technology, Changsha 410114, China
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| Abstract: |
| Aiming at the problems of high cost, low utilization rate and single operation mode of user-side distributed energy storage, a self-operating and sharing energy trading method of energy storage aggregator(ESA) is proposed, which combines energy self-operating mode and energy storage sharing mode. ESA benefits from energy trading with power grid companies and users respectively. Based on the time-of-use electricity price and user load prediction, the day-ahead optimization model of ESA controlling energy storage charging and discharging is established. Aiming at minimizing the trading cost between ESA and power grid, the day-ahead charging and discharging quantity of ESA in each period is obtained, which is used as the energy storage control strategy for real-time optimization and pricing of ESA. With the maximization of ESA benefit as the primary objective, the maximization of users’ daily benefit as the secondary objective, the internal electricity price as the control variable, the users’ electricity consumption as the state variable, and the internal electricity price limit and rigid demand of power consumption as the constraints, a Stackelberg game-based real-time optimization model of energy trading is established. The simulative results show that ESA achieves the lowest power purchase cost from the decision of day-ahead energy storage charging and discharging. The energy trading optimized by Stackelberg game determines the internal electricity price and improves the economic benefits of ESA and users. The self-operating and sharing energy trading method of ESA is an effective attempt of power system under the sharing economy mode. |
| Key words: energy storage sharing distributed energy storage aggregator operation mode Stackelberg game energy trading |
