面向配电系统有序用电的多目标规划算法
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国网无锡供电公司

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国家电网有限公司科技项目资助(项目编号:J2024197)


Multi-objective planning algorithm for orderly power consumption in distribution systems
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    摘要:

    本文针对军用基地配电网中高可靠性供电与战时能源调度的特殊需求,提出一种面向军事应用的优先级装备到微网(P2M)协同优化方法。通过构建有功功率损耗降低指数(PLR)与无功功率损耗降低指数(QLR),结合军用场景下电动装备充放电的动态约束,提升军事基地微电网在战时复杂负荷下的运行稳定性、可靠性和抗毁性。采用改进的最有价值球员(MVP)算法,以最小化负荷方差、PLR及QLR为目标,实现军事基地配电网中电动装备充放电的多目标协同规划。仿真基于标准IEEE 69总线系统,对比实验表明:所提方法在削峰填谷模式下,可将负荷方差降低29.2%,功率损耗指数优化效率优于传统算法(如GA、PSO等),计算时间缩短至113秒,显著提升战时电力调度响应速度。此外,通过优先级调度策略,低电量军用车辆可优先充电,高电能车辆动态回馈电能至微网,有效缓解战时峰值负荷压力,保障关键设施稳定供电。研究成果为能源系统的智能化管理与应急电力保障提供了理论支撑与技术路径。

    Abstract:

    This paper addresses the special requirements for high-reliability power supply and wartime energy scheduling in military base distribution grids, proposing a priority equipment-to-microgrid (P2M) collaborative optimization method tailored for military applications. By establishing the active power loss reduction index (PLR) and reactive power loss reduction index (QLR), and combining them with the dynamic constraints of electric equipment charging and discharging in military scenarios, the stability, reliability, and resilience of military base microgrids under complex loads during wartime are enhanced. An improved Most Valuable Player (MVP) algorithm is adopted, with the objectives of minimizing load variance, PLR, and QLR, to achieve multi-objective collaborative planning for the charging and discharging of electric equipment in the military base distribution network. Simulations are based on the standard IEEE 69 bus system. Comparative experiments show that under peak shaving and valley filling mode, the proposed method can reduce load variance by 29.2%, with power loss index optimization efficiency superior to traditional algorithms (such as GA and PSO), and computation time reduced to 113 seconds, significantly improving the response speed of power dispatch during wartime. Additionally, through a priority scheduling strategy, military vehicles with low battery levels can be charged first, while vehicles with high energy levels dynamically feed power back into the microgrid, effectively alleviating peak load pressure during wartime and ensuring stable power supply to critical facilities. The research findings provide theoretical support and technical pathways for the intelligent management of energy systems and emergency power supply.

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  • 收稿日期:2025-07-07
  • 最后修改日期:2025-07-09
  • 录用日期:2025-07-10
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