Multi-objective coordinated energy management method and system for optical storage integrated power station
CN121965481BActive Publication Date: 2026-10-16ELECTRIC POWER PLANNING & ENG INST CO LTD +1
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Patent Information
- Application Number
- CN202511944132.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-22
- Publication Date
- 2026-10-16
- Estimated Expiration
- 2045-12-22
AI Technical Summary
Technical Problem
例如,在电网支撑场景下,若仅调节逆变器无功输出而忽略储能功率的配合,可能因调节容量不足导致电压恢复效果受限;在提升光伏消纳率时,若未同步优化储能充放电时序与负荷需求的匹配度,可能加剧弃光现象
Benefits of technology
1. 通过实时计算运行效能、储能寿命衰减及电网支撑能力评估值,构建动态优先级权重分配机制,有效解决了传统多目标优化中权重固化导致的调节滞后问题。当电网频率或电压越限时,优先提升电网支撑权重并生成快速调节指令,确保毫秒级响应电网波动;当储能荷电状态临近安全边界时,自动切换至寿命保护模式,通过限制充放电倍率与深度延缓电池衰减;在稳态工况下,动态优化光储协同效率与光伏消纳率,实现经济性目标主导。该策略显著提升了多目标优化的实时性与场景适配性,使电站综合性能提升15%以上;
✦ Generated by Eureka AI based on patent content.
Abstract
The application discloses a kind of multi-objective collaborative energy management methods and systems for light storage integrated power station, method includes: obtaining the real-time operation data of light storage integrated power station current detection period;Based on real-time operation data, the operating efficiency evaluation value of light storage integrated power station, energy storage device life attenuation evaluation value and power grid support ability evaluation value are calculated;Based on real-time calculation result, multi-objective collaborative optimization instruction is generated using dynamic priority strategy;Multi-objective collaborative optimization instruction is decomposed, and photovoltaic inverter output instruction, energy storage device charge-discharge power instruction and grid-connected power instruction are obtained, and light storage integrated power station is operated according to photovoltaic inverter output instruction, energy storage device charge-discharge power instruction and grid-connected power instruction.By constructing dynamic priority strategy, adaptive switching of multi-objective weight is realized, and problems such as equipment wear and tear intensification and power grid support lag caused by single-objective optimization are effectively solved.
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