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基于微网群与共享储能的主动配电网优化调度策略
Optimization schedule strategy of active distribution network based on microgrid group and shared energy storage
| 作者 | Jinpeng Qiao · Yang Mi · Jie Shen · Changkun Lu · Pengcheng Cai · Siyuan Ma · Peng Wang |
| 期刊 | Applied Energy |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 377 卷 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 微电网 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | A master-slave game schedule strategy is proposed for ADN based on microgrid group and SES to solve the problem of pricing and optimization in multi-entity game. |
语言:
中文摘要
摘要 随着微网群与共享储能系统越来越多地接入主动配电网(ADN),亟需对这些复杂的能源要素进行有效协调。为此,本文构建了一种基于微网群与共享储能的主动配电网主从博弈调度策略。由主动配电网作为主导方确定分时电价,微网群与共享储能作为从属方响应电价信号,并考虑系统的安全运行与削峰填谷调度需求。此外,基于分时电价机制,提出了微网群与共享储能之间的两阶段电力交互策略。在第一阶段,通过多目标优化算法计算微网群的储能租赁需求,并据此制定共享储能的充放电策略,使其在满足微网群用电需求的同时,利用剩余容量响应配电网的调度要求。在第二阶段,针对微网群内部各微网间的功率交互,制定了合作联盟的调度策略及相应的收益分配机制。进一步地,采用嵌套cplex求解器的量子粒子群优化算法(QPSO)求解主从博弈的均衡解。最后,通过改进的IEEE 33节点系统验证了所提策略的有效性与合理性。
English Abstract
Abstract Due to the increasing microgrid group and shared energy storage integration into active distribution network (ADN), it is necessary to effectively coordinate these complexity energy elements. Therefore, a master-slave game schedule strategy is constructed for ADN based on microgrid group and shared energy storage. The time-of-use electricity price is decided by the ADN as the main body, so the microgrid group and shared energy storage should respond to the electricity price as the subordinate body, which may consider the safe operation and the peak shaving schedule. Moreover, the two-stage power interaction strategy between the microgrid group and shared energy storage is developed by the time-of-use electricity price. In the first stage, the energy storage leasing demand of microgrid group can be calculated through multi-objective optimization algorithms. Then, the charging and discharging strategy is formulated for the shared energy storage which can meet the power demand of the microgrid group and respond to distribution network schedule by the remaining capacity. In the second stage, a schedule strategy is formulated for the cooperative alliance considering power interaction among microgrids and a mechanism of benefit allocation. Furthermore, the equilibrium solution of the master-slave game may be solved through the Quantum Particle Swarm Optimization (QPSO) algorithm nested with the cplex solver. At last, the effectiveness and rationality of the proposed strategy can be verified by the improved IEEE33 bus system.
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SunView 深度解读
该主从博弈调度策略对阳光电源ST系列储能变流器和PowerTitan系统具有重要应用价值。文中提出的共享储能两阶段功率交互机制,可直接应用于阳光电源微电网群储能解决方案,通过QPSO算法优化分时电价响应策略,提升储能系统削峰填谷效率。该研究为阳光电源iSolarCloud平台的多微网协同调度功能提供理论支撑,可结合GFM控制技术实现主动配电网的安全经济运行,推动储能系统从单体优化向群组协同演进,增强产品在主动配电网场景的市场竞争力。